1.1.1.1.1.1
Phase 1 Data Management Plan
Heart of Iowa Regional Transit Agency
ITS4US Deployment Project
www.its.dot.gov/index.htm
Final Report — December 15, 2021
FHWA-JPO-21-867
Produced by Heart of Iowa Regional Transit Agency ITS4US Deployment Phase 1
U.S. Department of Transportation
Intelligent Transportation Systems Joint Program Office
Federal Highway Administration
Office of the Assistant Secretary for Research and Technology
Federal Transit Administration
Notice
This document is disseminated under the sponsorship of the Department of
Transportation in the interest of information exchange. The United States
Government assumes no liability for its contents or use thereof.
The U.S. Government is not endorsing any manufacturers, products, or services
cited herein and any trade name that may appear in the work has been included
only because it is essential to the contents of the work.
Technical Report Documentation Page
1. Report No.
FHWA-JPO-21-867
2. Government Accession No.
3. Recipient’s Catalog No.
4. Title and Subtitle
Phase 1 Data Management Plan
Heart of Iowa Regional Transit Agency ITS4US Deployment Project
5. Report Date
December 15, 2021
6. Performing Organization Code
N/A
7. Author(s)
Santosh Mishra, Tom Coogan, Brooke Ramsey
8. Performing Organization Report No.
N/A
9. Performing Organization Name and Address
Heart of Iowa Regional Transit Agency (HIRTA)
2824 104th St
Urbandale, IA 50322
10. Work Unit No. (TRAIS)
11. Contract or Grant No.
693JJ321C000006
12. Sponsoring Agency Name and Address
U.S. Department of Transportation
ITS Joint Program Office
1200 New Jersey Avenue, SE
Washington, DC 20590
13. Type of Report and Period Covered
Final, Phase 1 (3/2021-2/2022)
14. Sponsoring Agency Code
HOIT-1
15. Supplementary Notes
Fred Bowers (FHWA)
16. Abstract
The Heart of Iowa Regional Transit Agency (HIRTA) is one of the 5 awardees for Phase 1 of the Complete Trip –
ITS4US contract for its proposed concept “Health Connector for the Most Vulnerable: An Inclusive Mobility
Experience from Beginning to End” (Health Connector) by the United States Department of Transportation
(USDOT). Per the goals of the program, the Health Connector project is focused on improving transportation access to
healthcare for underserved groups in Dallas County, IA. The Data Management Plan (DMP) identifies the data to be
collected, how the data will further the goals of the USDOT and the Complete Trip-ITS4US program, how the data will
be managed, how the data will be made accessible, how the data will be stored, and what data standard(s) will be
used. Researchers, including, HIRTA partner Iowa State University (ISU), Independent Evaluators and the USDOT will
be provided access to data as described in this document when it starts to become available in Phase 2 during initial
system deployment and testing.
17. Keywords
ITS4US; Complete Trip; Deployment; ITS; Intelligent
Transportation Systems; NEMT, Data, Systems Engineering
18. Distribution Statement
No restrictions
19. Security Classif. (of this report)
Unclassified
20. Security Classif. (of this page)
Unclassified
21. No. of Pages
93
22. Price
Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
Revision History
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | i
Revision History
Name
Date
Version
Summary of
Changes
Approver
Santosh Mishra, IBI
Group
2 Aug 2021
1.0
Initial Draft
Brooke Ramsey
Santosh Mishra, IBI
Group
30 Aug 2021
2.0
Updated to
address USDOT
comments
Brooke Ramsey
Santosh Mishra, IBI
Group
22 Oct 2021
3.0
Updated to
address USDOT
comments
Brooke Ramsey
Santosh Mishra, IBI
Group
29 Nov 2021
4.0
Updated to
address USDOT
comments
Brooke Ramsey
Santosh Mishra, IBI
Group
15 Dec 2021
5.0
Updated to
address USDOT
comments and
Section 508
compliance
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | iii
Table of Contents
Revision History ....................................................................................................................... i
Table of Contents ................................................................................................................... iii
1 Introduction ........................................................................................................................ 1
1.1 Project Background ............................................................................................................................. 3
1.2 Document Overview ............................................................................................................................ 5
2 Project Overview ............................................................................................................... 7
2.1 Change Control .................................................................................................................................. 11
2.2 Relevant Sources .............................................................................................................................. 12
2.3 Data Schedule ................................................................................................................................... 12
3 Data Overview .................................................................................................................. 16
3.1 Data Needs Summary ....................................................................................................................... 16
3.2 Data Overview ................................................................................................................................... 23
4 Data Stewardship ............................................................................................................ 39
4.1 Data Owner and Stewardship ........................................................................................................... 39
4.2 Access Level ...................................................................................................................................... 41
4.2.1 Public/Open Datasets .......................................................................................................... 41
4.2.2 Private Datasets................................................................................................................... 45
4.2.3 Access Request ................................................................................................................... 58
4.2.4 Related Tools, Software and/or Code ................................................................................. 58
4.2.5 Relevant Privacy and/or Security Agreements ................................................................... 58
4.3 Re-Use, Redistribution, and Derivative Products Polices ................................................................ 59
4.4 Data Storage and Retention .............................................................................................................. 61
4.4.1 Storage Systems ................................................................................................................. 62
4.4.2 Data Storage System Description ....................................................................................... 64
4.4.3 Cybersecurity Policies ......................................................................................................... 64
4.4.4 Data Security Policies and Procedures .............................................................................. 64
4.4.5 Back-up and Recovery Policies and Procedures ............................................................... 66
5 Data Standards ................................................................................................................ 69
5.1 Data Standards .................................................................................................................................. 69
5.1.1 Vehicle Data Standards ....................................................................................................... 69
5.1.2 Data Communication Standards ......................................................................................... 69
5.1.3 Data Access Protocols ........................................................................................................ 69
5.1.4 Data Sharing Standards ...................................................................................................... 70
5.1.5 Open Data Standards for Transactional Data .................................................................... 70
Table of Contents
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
iv
| Phase 1 Data Management Plan - HIRTA
5.1.6 Open API.............................................................................................................................. 70
5.2 Versioning .......................................................................................................................................... 71
5.3 Metadata ............................................................................................................................................ 71
5.3.1 Metadata Types ................................................................................................................... 71
5.3.2 Metadata Structure .............................................................................................................. 75
5.3.3 Metadata Update Process ................................................................................................... 75
Appendix A. Acronyms and Glossary ................................................................................. 77
Table of Contents
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | v
List of Tables
Table 1. Health Connector System Goals and Objectives ............................................................... 7
Table 2. HIRTA DMP Schedule ....................................................................................................... 13
Table 3. Data Needs Summary ....................................................................................................... 21
Table 4. Data Overview .................................................................................................................. 25
Table 5. Data Owner and Steward Information .......................................................................... 40
Table 6. Health Connector Open Data Scope ................................................................................ 43
Table 7. Scope and Availably of Private Datasets .......................................................................... 47
Table 8. Licensing for Private Data ................................................................................................. 60
Table 9. Summary of Storage Systems .......................................................................................... 63
Table 10. Trip-Level Data Description ............................................................................................ 72
List of Figures
Figure 1. Overview of Health Connector System Concept (Source: HIRTA team) .......................... 2
Figure 2. Health Connector Overview (Source: HIRTA team) .......................................................... 4
Figure 3. Tiered Framework for Metrics in MPM Report (Source: FTA) ......................................... 10
Figure 4. Health Connector Deployment Schedule (Source: HIRTA team) .................................... 13
Figure 5. High-level System Context Diagram for Health Connector (Source: HIRTA team) ........ 20
Figure 6. TMS reporting for Data Access (Source: Uber Technologies) ........................................ 42
Figure 7. Snapshot of TMS reporting used to Access Driver, Trip Level and Program Level Data
(Source: Uber Technologies) .................................................................................................... 45
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | vi
1. Introduction
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 1
1 Introduction
The Heart of Iowa Regional Transit Agency (HIRTA) is one of the 5 awardees for Phase 1 of the
Complete Trip – ITS4US contract for its proposed concept “Health Connector for the Most
Vulnerable: An Inclusive Mobility Experience from Beginning to End” (Health Connector) by
the United States Department of Transportation (USDOT).
The Health Connector solution intends to demonstrate an innovative concept that will address
various bottlenecks associated with healthcare access for HIRTA communities. Some of these
challenges are the key reason behind missed appointments or unacceptable level of preventive
or as-needed healthcare in HIRTA service area. For this deployment, the HIRTA team plan to
implement a scalable and replicable solution that enables inclusive access to non-emergency
medical transportation for all underserved populations and their caregivers by resolving access
barriers with the use of advanced technologies. This solution will allow Dallas County residents
without access to transportation who may be seeking a medical appointment to explore their
transportation alternatives and book both medical and transportation appointments at the same
time. Further, this solution will include information and wayfinding services to guide them at every
step of their trip.
The referenced underserved populations’ mobility needs vary based on the individual. This
deployment will provide enhanced access to healthcare options for “all travelers” in Dallas County
with a specific focus on underserved communities, including persons with disabilities, low income,
rural, older adults, veterans, and persons with limited English proficiency.
In addition to addressing mobility needs, the proposed deployment will recognize the net impact
that access to health services have on patient health care outcomes as well as both the financial
and health outcomes from the perspective of the health care community/Dallas County Health
Department (DCHD).
Figure 1 provides an overview of the Health Connector concept.
1. Introduction
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
2
| Phase 1 Data Management Plan - HIRTA
Figure 1. Overview of Health Connector System Concept (Source: HIRTA team)
Every step of the trip shown in Figure 1, utilizes tools that require good quality data to function as
follows:
• At pre-trip, the trip planning function will require access to appointment details to find out
applicable transportation alternatives. Booking function will require access to customer
profile with details on customer mobility needs and eligibility for a funding source; vehicle
and driver availability, estimated arrival time, travel time and others. Traveler may also
coordinate with Health Navigators or caregivers who will have access to the data to
provide help related to medical appointment or required transportation.
• During trip, Traveler will need to be notified at every step of their trip on estimated pick-up
time and estimated travel time. This information will be provided using data generated by
the system in real-time on trip performance (e.g., actual time of arrival or trip status).
Travelers will also be able to use the outdoor wayfinding function which will provide
information related to localization and orientation (e.g., locating vehicle at the pickup
spot).
• On arrival, at the healthcare center, systems will use the data available to guide the
Traveler to locate the correct door and entrance and provide step-by-step guidance
indoors if necessary, using the mapping and pathways data available from wayfinding
system. Traveler will also initiate a return trip based on current availability of driver and
vehicle information.
Detailed data needs for the system providing Health Connector functions are summarized in
Table 3 and Table 4 of the DMP. The DMP further describes how the data will further the goals of
the USDOT, how the data will be managed, how the data will be made accessible, how the data
will be stored, and what data standard(s) will be used.
1. Introduction
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 3
Final updates for the Phase 1 to the DMP will be made by December 2021 but will it be a living
document and may be updated based on testing results in Phase 2 and operation and
performance management in Phase 3. A change control process for the DMP is described in
Section 2.1 along with the triggers for the DMP update. Within Phase 1, the document will be
further updated based on the findings from Institutional Review Board (IRB) approval process and
through the preparation of Human Use Summary document (HUA), and as part of the
development of the Performance Management and Evaluation Support Plan (PMESP), Systems
Requirements Development (SysRS), and Integrated Completed Trip Deployment Plan (ICTDP).
Researchers, including, HIRTA partner Iowa State University (ISU), Independent Evaluators and
USDOT will be provided access to the data as described in this document as it starts to become
available in Phase 2 during initial system deployment and testing.
1.1 Project Background
The Health Connector solution intends to demonstrate an innovative concept that will address
various bottlenecks associated with healthcare access for HIRTA communities. Some of these
challenges are the key reason behind missed appointments or unacceptable level of preventive
or as-needed healthcare in HIRTA service area. For this deployment, the HIRTA team plans to
implement a scalable and replicable solution that enables inclusive access to non-emergency
medical transportation (NEMT) for all underserved populations and their caregivers by resolving
access barriers with the use of advanced technologies. This solution will allow Dallas County
residents without access to transportation who may be seeking a medical appointment to explore
their transportation alternatives and book both medical and transportation appointments at the
same time. Further, this solution will include information and wayfinding services to guide them at
every step of their trip.
Key capabilities of the proposed technology solution are as follows:
• Enable the customer to use a smart device (e.g., smartphone, smartwatch) application or
equally effective alternate methods to schedule and manage medical appointments and
transportation services all in one location (Health Connector App). Provide customers
options to choose from available providers. Provide same day response if needed by
customers.
• Send customers alerts before arrival and again when the vehicle is approaching.
• Keep customers informed on trip progress at all stages of the complete trip: pre-trip (e.g.,
planning, booking) or trip/en-route (e.g., waiting, boarding, on-board environment, drop off)
and return trip booking.
• Provide directions (audible and visual) on where to meet the vehicle/driver. On arrival,
drivers should have the ability to automatically confirm customer identity and assist with
boarding as needed.
• Provide drivers the capability to request turn-by-turn navigation to a desired destination.
• The Health Connector App will enable the customer to utilize advanced wayfinding
solutions with the help of indoor and outdoor navigation technologies to provide personal
concierge-style travel from origin to destination. This will include:
o Locating the vehicle outside origin and destination locations
1. Introduction
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
4
| Phase 1 Data Management Plan - HIRTA
o Locating healthcare facility when dropped off by vehicles
o Locating desired floor/room when inside the healthcare facility
• Customers will be able to use the Health Connector solution for any contactless payment
needs at any point for transportation-related payments.
• Customers can initiate return trip when the appointment is complete and follow the similar
process as the inbound trip to medical facility to locate and board the vehicle for the return
trip.
If customers or their caregivers desire to book and pay for another local trip as an additional leg
along with the medical trip, they will be able to do that using Health Connector solution.
Figure 2 provides a generic system context diagram with high-level flows. A more granular system
diagram with detailed data flows is provided in Figure 5.
Figure 2. Health Connector Overview (Source: HIRTA team)
HIRTA
Transportation
Management
System
(Routematch/
Uber)
Traveler or Caregiver
Devices (non-Medicaid)
HIRTA Vehicle Systems
Health Connector
Back-end
Wireless Data
Communication
for trip manifest
and details,
including
payment
Trip Requ est for a Medical
Appointment, Customer
Information (via phone)
Provide turn-by-turn
guidance
Trip Requ est for a Medical
Appointment, Customer Information
(via web, smart device)
Trip Request for a
Medical
Appointment,
Cust omer
Information
Trip Request for a Medical
Appointment, C ust ome r
In for mation
Transportation and
Medical Appointment
Availability
Healthcare Operations
EHR Software
Access2Care (Medicaid)
Traveler or Caregiver
Devices (Medicaid)
Automated trip manifest detail
exchange for service delivery
Trip Requ est for a Medical
Appointment, Customer
Information
Third Party
Vehicle Systems
Wireless Data
Communication
for trip manifest
and details,
including
payment
System of Interest
Sensor/Visual
Marker
Wayfinding Web
Application
External Access to Patient/
Traveler Medical Appointment
and Transportation (DCHD,
Healthcare Staff, Health
Navigators, Caregi vers)
Connectivity with
wayfinding sensor/visual
marker
Existing or Planned
HIRTA System
New Development
for Health Connector
External Systems to be
interfaced for Health Connector
Legend:
1. Introduction
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 5
1.2 Document Overview
The DMP provides relevant information, as described earlier, for the data stakeholders that
include the following:
• The USDOT.
• Government and funding agencies as defined in the ConOps.
• Non-government stakeholders, as described in the ConOps.
• Independent Evaluators.
• Researchers.
• Third party developers.
• Future implementers of the system.
The DMP is organized as follows:
• Section 2 provides an overview of the HIRTA ITS4US Complete Trip project.
• Section 3 describes data to be collected as part of the project.
• Section 4 identifies data ownership and describes the process for required data to be
collected, stored and shared as part of the project.
• Section 5 provides information on standards and metadata for the data involved.
2. Project Overvie
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 7
2 Project Overview
The information about the HIRTA Complete Trip-ITS4US deployment project and its goals, as well
as how the project’s data helps achieve USDOT’s research goals is summarized below.
• Project Title: Health Connector for the Most Vulnerable: An Inclusive Mobility Experience
from Beginning to End.
• Project Goals and Objectives: The goals and objectives of this project, developed as
part of the PMESP (USDOT publication number: FHWA-JPO-21-877), are listed in Table
1. The PMESP is currently in the process of being finalized so this section will be updated
to reflect the changes in the final PMESP as completed by mid-November 2021.
Table 1. Health Connector System Goals and Objectives
Goals/Outcomes
Description
Objectives
G1. Improved health
outcomes for Dallas County
residents
Reduction in the number of no-shows
for medical appointments due to
increased access to transportation will
help Dallas County residents,
particularly underserved populations,
make their appointments in a timely
manner. This increased access to
medical services will result in
measurable positive health outcomes.
G1O1. Reduced number of
no-shows for medical
appointments with
availability of increased
access to transportation
options in Dallas County.
G1O2. Increased access
to follow-up care options
through availability of
transportation services and
telehealth (where available
such as Veterans Affairs
and through healthcare
providers).
G1O3. Tracking of
measurable positive
impacts of transportation
access on healthcare
outcomes for Dallas
County residents.
G2. Self-reliance and
spontaneity for underserved
groups
Health Connector will provide tools to
access safe, affordable and reliable
transportation services, and relevant
information/wayfinding as and when
needed by underserved groups.
G2O1. Availability of
reliable tools and services
for underserved groups for
planning, booking,
payment and customer
information for accessing
safe transportation
services with minimal
number of required steps.
2. Project Overvi
U.S. Department of Transportation
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Intelligent Transportation System Joint Program Office
8
| Phase 1 Data Management Plan - HIRTA
Goals/Outcomes
Description
Objectives
G2O2. Availability of
reliable indoor and outdoor
wayfinding tools to assist
underserved travelers
locate vehicles and/or
facilities at destinations in
a safe manner.
G2O3. Delivery of safe
and reliable transportation
services at all times when
needed by underserved
groups for their medical
appointments, return trip
and follow-up care.
G3. Efficient transportation
management capabilities for
medical transportation
services
HIRTA and its contractors,
Access2Care, DCHD, healthcare
providers and funding agencies will
have access to tools and services for
coordinating booking, management,
completion, billing, and payments for
medical transportation in Dallas
County requested by underserved
Travelers.
G3O1. Availability of tools
for managing
transportation services
from multiple service
providers from a
centralized Health
Connector system along
with enabling as-needed
transportation capacity at
all times.
G3O2. Availability of tools
and procedures as
necessary to provide
reliable transportation for
requested trips.
G3O3. Provision of
affordable transportation
through coordination with
funding entities for
subsidizing transportation
for the underserved.
G3O4. Implementation of
automation for required
coordination to reduce the
amount of time needed by
involved staff at HIRTA
and its partners.
G4. Financial sustainability
of medical transportation
programs
Availability of tools to efficiently
coordinate booking and manage
delivery of transportation services
through optimal use of resources will
help in cost-reduction of medical
transportation and will help with
maintaining long term sustainability of
funding programs.
G4O1. Availability of tools
to track cost and revenue
measures along with any
applicable subsidies to
analyze the total cost to
HIRTA and partners for
delivering medical
transportation services.
2. Project Overvie
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 9
Goals/Outcomes
Description
Objectives
G4O2. Implementation of
processes to reduce the
resources spent in
delivering and
administering the trips
funded by various
programs.
G5. Safe medical
transportation services
Availability of advanced tools to
provide trip information and wayfinding
services customized per the needs
underserved groups will help provide
safe transportation options to travelers
who may lack those.
G5O1. Timely and reliable
delivery of required
information on vehicle and
trip status to enhance
perceived safety with the
system.
G5O2. Implementation of
required safety measures
to mitigate the risks of any
accidents, incidents and
related injuries and severe
consequences associated
with trips to medical
facilities, outdoor/indoor
wayfinding and return trips.
• Project Description: The Health Connector solution intends to demonstrate an
innovative concept that will address various bottlenecks associated with healthcare
access for HIRTA communities, with a particular focus on underserved groups. Some of
these challenges are the key reason behind missed appointments or unacceptable level
of preventive or as-needed healthcare in HIRTA service area. For this deployment, the
HIRTA team plans to implement a scalable and replicable solution that enables inclusive
access to non-emergency medical transportation for all underserved populations and
their caregivers by resolving access barriers with the use of advanced technologies. This
solution will allow Dallas County residents, without access to transportation, who may be
seeking a medical appointment to explore their transportation alternatives and book both
medical and transportation appointments at the same time. This will also provide the
capability for transportation, healthcare, and information and referral professionals to
coordinate on a trip. Further, this solution will include information and wayfinding services
to guide Travelers at every step of their trip.
• Project Performance Measurements: Performance measures are based on the goals
and objectives identified according to the needs identified in the ConOps and also builds
upon the preliminary measures that were identified in the ConOps.
The performance measures are also mapped to the Mobility Performance Metrics (MPM),
as described in the FTA Report No. 0152 on Mobility Performance Metrics (MPM) for
Integrated Mobility and Beyond, published 2020. The focus of these measures will be on
measuring the outcome of the project on the 6 target underserved groups identified for
the project that include, persons with disabilities, older adults, veterans, persons with
language barriers, rural populations, and persons with low income. The MPM measures
are identified under the following high-level categories, also illustrated in Figure 3.
2. Project Overvi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
10
| Phase 1 Data Management Plan - HIRTA
• Core Measures: This category includes Traveler-centric measures and related to the
following key aspects associated with a trip: availability of services; reliability of
available services; budget needed/affordability; travel time; and safety.
• Tier 1 Measures: This category indicates system’s ability to deliver on the required
goals and objectives and refers to system capacity; system efficiency, effectiveness,
and cost; utilization; safety; and reliability.
• Tier 2 Measures: This category refers to system’s availability to deliver on the
broader goals of the local community. The measures are related to overall mobility
and safety/health of the members of the community; and financial performance of the
systems and organizations involved.
• Tier 3 Measures: This category refers to system’s ability to contribute to trends
nationally and identifies measures related to financial performance of organizations
delivering services; and safety/health of communities.
Figure 3. Tiered Framework for Metrics in MPM Report (Source: FTA)
For each of these categories, the HIRTA team has defined measures for the 3 stages of a
Complete Trip that include pre-trip, trip/en-route, and post-trip. Initially, the HIRTA project
team identified 57 measures in total and prioritized those as follows:
• High: These measures are highly critical to monitor to evaluate the success of
the program.
• Medium: These measures are significant but a regular monitoring is not required.
• Low: These measures are not necessary for evaluating the success of the
program.
A detailed list of measures is available in the Performance Measurement and Evaluation
Support Plan (PMESP).
2. Project Overvie
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 11
2.1 Change Control
HIRTA, as the system owner, will be in charge of all data generated by the system. In this role,
HIRTA will also keep track of any changes to the system that may impact: 1) data collected; 2)
data quality and integrity; 3) data structure and metadata; 4) access control and other relevant
changes to ensure data stakeholders have complete understanding of the data.
HIRTA has set up a change control board (CCB) for the project as identified for the User Needs
Identification and Requirements Planning (UNIRP). This CCB consists of the lead project staff
that include Project Management Lead (PML), System Development Lead (SDL), Concept
Development Lead (CDL), Healthcare Lead (HL), Technology Lead (TL) and Stakeholder
Engagement Lead (SEL) and Research and Evaluation Lead (REL). This CCB will be engaged in
the management of the DMP as well.
As stated earlier, the DMP is a living document and any updates approved by the CCB will be
made when there are any changes to the data management process. Triggers for changes to the
DMP will be based on the identification of gaps in the DMP in advance of or during the following
activities:
• Testing of system components and features.
• Addition, modification, or deletion of a new feature in one or more system components.
• Replacement of a system component, either due to replacement of a system provider or
due to availability of new/upgraded component from a provider.
• Modification in the server infrastructure used for the storage and providing data access.
• Modification in the schema or structure for data tied to system components, data format
for the data made available and metadata.
• Modifications in policies, system components and tools related to data storage,
management, access and sharing.
HIRTA will follow the following process for the change control of the DMP:
1. Change Identification: HIRTA PML will keep track of any changes to the system that may
impact any aspects of the data management per the triggers identified above.
2. Change Evaluation: In the event of a change identified, the HIRTA PML will consult with the
CCB regarding any need to make changes to the existing DMP.
3. Change Approval: In the event a change is necessary, anticipating any impact on the way
data is accessed and used by external third parties, the CCB will identify the scope of the
changes needed and collectively approve those changes.
4. Document Update: The HIRTA SDL will update the document for approved changes on
behalf of the HIRTA team.
2. Project Overvi
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Intelligent Transportation System Joint Program Office
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| Phase 1 Data Management Plan - HIRTA
5. Notification to DMP Stakeholders: Once the changes are made, the HIRTA PML will notify
the stakeholders about changes in the DMP and share the updated DMP. If there are any
concerns, the HIRTA PML will consult those with the CCB, take appropriate actions and follow
up with stakeholders. Once the stakeholder concerns are addressed, changes to the DMP
will be fully authorized and current version will be shared with the USDOT.
2.2 Relevant Sources
The following documents were referenced when preparing this DMP:
1. USDOT, “Complete Trip- ITS4US Deployment Broad Agency Announcement (693JJ3-20-
BAA-0004),”
2. HIRTA, “HIRTA - USDOT Complete Trip - final Proposal - v1.0 2020-07-31 (Volume 1),” July
2020.
3. Data dictionary for the Routematch software.
4. Data dictionary for Uber Transit.
5. Transit Center, “Mobility Performance Metrics (MPM),” February 2020, Federal Transit
Administration, FTA Report No. 0152
6. Santosh Mishra et al., “Phase 1 Concept of Operations (ConOps), Heart of Iowa Regional
Transit Agency ITS4US Deployment Project,” August 2021, US department of Transportation,
Publication Number: FHWA-JPO-21-859.
7. Santosh Mishra et al., “Phase 1 Performance Management and Evaluation Support Plan
(PMESP),” Heart of Iowa Regional Transit Agency ITS4US Deployment Project, August 2021,
US department of Transportation. Publication Number: FHWA-JPO-21-877.
8. Santosh Mishra et al., “Phase 1 Systems Requirements (SysRS) Document,” Heart of Iowa
Regional Transit Agency ITS4US Deployment Project,” October 2021 (expected), US
department of Transportation. Publication Number: FHWA-JPO-21-882.
9. Santosh Mishra et al., “Phase 1 Integrated Complete Trip Deployment Plan (ICTDP),” Heart
of Iowa Regional Transit Agency ITS4US Deployment Project, January 2022 (expected), US
department of Transportation.
10. Santosh Mishra et al., “Phase 1 Human Use Approval (HUA) Summary (HUA), Heart of Iowa
Regional Transit Agency ITS4US Deployment Project, December 2021 (expected), US
department of Transportation.
2.3 Data Schedule
The information included in this DMP is preliminary and current as of October 2021. Final updates
for the Phase 1 to the DMP will be made prior to the conclusion of Phase 1, in December 2021. It
is expected that within Phase 1, this version of the document will be further updated based on the
2. Project Overvie
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 13
findings from the Institutional Review Board (IRB) approval process and through the preparation
of the following documents: Human Use Approval Summary (HUA), Performance Management
and Evaluation Support Plan (PMESP), Systems Requirements Development (SysRS), and
Integrated Completed Trip Deployment Plan (ICTDP).
Additional changes may be made in Phase 2 and 3 as details of the system and its components
are further developed as part of the system design, deployment and testing. Figure 4 provides a
tentative schedule for all 3 phases of the Health Connector that are used as a reference for
developing a schedule for the maintenance of the DMP.
Figure 4. Health Connector Deployment Schedule (Source: HIRTA team)
Table 2 provides a preliminary schedule for maintaining the DMP. The dates for Phase 2 and 3
are currently unclear so only preliminary estimates of timing are provided.
Table 2. HIRTA DMP Schedule
ID
Event Title
Description
Phase
Date
1
Draft DMP Is delivered
to USDOT
Initial Draft DMP with basic
information known at the time of
writing
Phase 1
Aug 2021
2
Final DMP
DMP is updated with USDOT
comments addressed. Any
outstanding details are included
except those that require the
completion of deliverables for future
tasks
Phase 1
Aug 2021
2. Project Overvi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
14
| Phase 1 Data Management Plan - HIRTA
ID
Event Title
Description
Phase
Date
3
IRB application
submitted
Data and performance management
approach along with details
regarding engaging human subjects
in the study submitted to IRB for
approval; May take up to 6 weeks
per ISU process
Phase 1
Oct 2021
4
System requirements
finalized
Requirements on performance and
data developed; walkthrough
conducted and requirements
finalized.
Phase 1
Oct 2021
5
PMESP Finalized
Performance measures, required
data and details regarding supporting
independent evaluation are finalized
Phase 1
Nov 2021
6
IRB approval and Draft
Human Use
AfSLApproval (HUA)
summary complete
IRB approval is received and HUA
summary is developed for USDOT
review.
Phase 1
Nov 2021
7
DMP Updated based on
PMESP, SysRS, IRB
input, HUA Summary
As details regarding the scope of
public and private data is approved
by the IRB and as it has become
evident through completion of other
documents, DMP will be updated
reflect the current understanding of
data management.
Phase 1
Nov 2021
8
Final Human Use
Approval (HUA)
summary complete
HUA summary document finalized
per USDOT comments.
Phase 1
Dec 2021
9
Final updates to DMP
for Phase 1
Any necessary updates are made to
the DMP based on outcomes of
Tasks 4-14.
Phase 1
Dec 2021
10
ICTDP Finalized
Data and performance management
approaches are finalized per
finalized Phase 1 DMP.
Phase 1
Jan 2022
11
Initial data samples
provided to USDOT
Initial Data samples are created
validated and submitted to USDOT
for review.
Phase 2
Sep 2022
12
Initial meeting with
USDOT data team to
review data
Meeting to review data with USDOT
and walkthrough the data schema
and DMP
Phase 2
Oct 2022
13
Baseline data collection
starts
Initial collection of data on current
conditions starts
Phase 2
Nov 2022
14
DMP updated
DMP updated with any changes from
testing and sample data schema.
Phase 2
Jan 2023
15
Baseline data provided
to USDOT
Complete Baseline data sets are
uploaded to USDOT and the IE
Phase 2
Jan 2023
16
Month of testing of
applications begins
Initial upload after datasets are
collected through testing
Phase 2
Feb 2023
17
Data transferred to
USDOT
Daily updates of after case data are
provided to USDOT and IE
Phase 2/3
Feb2023-
Aug 2024
18
Go-live
Go-live
Phase 3
Aug 2023
19
Data Review
Data Review conducted with USDOT
and IE to ensure datasets are
complete
Phase 3
Sep 2024
2. Project Overvie
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 15
ID
Event Title
Description
Phase
Date
20
Draft Final Analysis
Report submitted
Draft Final Analysis Report submitted
to USDOT
Phase 3
Jan 2025
21
Final Analysis Report
submitted
Draft Final Analysis Report submitted
to USDOT
Phase 3
Feb 2025
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 16
3 Data Overview
3.1 Data Needs Summary
The systems involved in the context of Health Connector, as shown in Figure 5, can be defined as
follows:
• Traveler-end Subsystem: this subsystem includes the tools and technologies
(phone/interactive voice response (IVR), mobile/smart devices, web-based tools) to be
used by travelers or patients seeking transportation services for their medical
appointments as part of pre-trip, en-route trip, on arrival and return trip activities.
Currently, HIRTA customers have access to the following Traveler applications from
Routematch by Uber:
o Amble App: used for requesting trip and finding out status of trips. No capabilities
for planning are there in the Amble App.
o RMPay: used for maintaining prepaid balance to pay for completed trips.
o IVR: used to send night-before reminders to Travelers per their subscription
preferences for upcoming trips. Real-time/same-day reminders are not available.
Health Connector plans to implement capabilities to provide a new off-the-shelf unified
application for planning, booking and payment. Also, this new application will provide
real-time status on trips on-demand and through push notification services.
• Transportation Management Subsystem (TMS): this subsystem includes the
technologies used to assist customer care and operations staff with Traveler registration,
eligibility management, reservations, scheduling, dispatching, billing and administration
activities. These products are commercially available from various providers of
paratransit/demand response vendors. Currently, HIRTA utilizes capabilities in the
Routematch Demand application from Routematch by Uber for completing transportation
management functions. While limited capabilities exist to address same day requests
(e.g., return trips), primarily Routematch Demand application is used to schedule trips at
least a day in advance.
Given Health Connector is focused on addressing same day and real-time requests,
commonly referred to as mobility on-demand (MOD), HIRTA will procure such capabilities
through an off-the-shelf MOD platform to augment existing TMS capabilities. The new
MOD platform will also be fully integrated with the new Traveler and Driver applications.
Further, this new platform will support utilizing third-party service providers for adding
capacity when needed in real-time. Finally, limited access to this platform will be made
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 17
available to Health Navigators and healthcare providers so they are able to book trips
directly without involvement of HIRTA staff.
At this time, HIRTA anticipates both Routematch Demand and the new MOD platform to
co-exist to meet Health Connector functions. This is required given advanced capabilities
within Routematch Demand application for managing the travel needs of underserved
populations (e.g., older adults and persons with disabilities) which are either not available
in off-the-shelf MOD platforms or are very limited. Therefore, for Health Connector,
Routematch Demand platform will be used for functions such as managing eligibility (e.g.,
advanced capabilities for eligibility/funding tracking and managing the mobility needs of
underserved) or prescheduled trips (e.g., 24-hour advance booking or subscription-
based) and the MOD platform will be used for providing same day booking, and for
enabling coordination with healthcare providers and health navigators. At least a daily
data exchange will be enabled between the MOD platform and Routematch Demand to
make all trips available in the MOD platform for dispatching on the day of the trip. Further
details of this data exchange and desired frequency are still being discussed and will be
finalized at the time of Phase 2 design.
While there are various commercially available MOD platforms that can provide the new
capabilities needed for Health Connector, HIRTA team is planning to deploy Uber Transit
platform given the integration needs with existing Routematch Demand application and
lack of proven data standards/standard interfaces to integrate with other commercially
available/off-the-shelf MOD platforms. However, requirements in this document are
vendor-agnostic and are defined such that any commercially available platform can meet
those.
This document refers to MOD platform as Uber Transit and system provider as
Uber Technologies where specific references are needed for a discussion (e.g.,
licensing, privacy policy, data stewardship). Uber Technologies is the provider of
both Routematch Demand and Uber Transit products.
• Vehicle Subsystem: this subsystem refers to the technologies deployed on vehicles to
support Driver-end functions for driver-dispatch communications, manifest management,
support just-in-time dispatching, turn-by-turn navigation and outdoor wayfinding (e.g., to
locate Travelers at the time of pick up), on-board customer information and fare
payments. All HIRTA-owned vehicles, Drivers will use tablets running Driver app. On
other vehicles, Drivers may use Driver app on their tablet or their phone.
• Wayfinding Subsystem: this subsystem refers to the technologies and infrastructure to
be used for providing, outdoor wayfinding, indoor positioning, orientation, and step-by-
step guidance on request to travelers. One or more commercially available wayfinding
system providers may be used but the current plan is to utilize at least the system
provided by HIRTA team partner, Navi Lens.
• Supporting systems: These refer to the phone system and existing functions provided
within Routematch software that are not part of Health Connector project. However, the
TMS will exchange data with these systems, as needed, or HIRTA staff may interact with
those for the following functions:
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
18
| Phase 1 Data Management Plan - HIRTA
• External Systems: These systems are external to Health Connector that have been
identified for close coordination among HIRTA and partners for providing efficient
transportation services for medical trips or for collecting data for performance
measurement needs.
o Access2Care: this subsystem refers to State of Iowa Medicaid Brooker’s system
used for booking and managing Medicaid trips. HIRTA is one of the providers
used by Access2Care. Medicaid trips will be booked by Access2Care when
requested by Travelers and will be ingested in the HIRTA system when assigned
to HIRTA. At that point, Traveler using Medicaid benefits will be able to use
Traveler tools provided by Health Connector.
HIRTA is planning to build a new interface with Access2Care to automate the
data exchange and improve coordination for Medicaid-funded trips. Details of this
interface are still under discussion and will be finalized by Phase 2 design.
o Health Navigator-end Subsystem: This subsystem includes the following
components:
An Information and referral (I&R) product that is used by Health
Navigators and the Health Administrator at the Dallas County Health
Department (DCHD) to track the status of referral activities and for
coordination with Dallas County residents health navigation/social care
services. Currently, DCHD uses Microsoft Access-based program that
recently replaced the previously used product from Healthleads. No
integration is planned with this product for Health Connector. However,
access to data may be needed for measuring Health Connector
performance.
Limited access to TMS components will be provided to Health Navigators
to arrange transportation services for the patients /Travelers they may be
working with and coordinate with HIRTA or healthcare staff on the status
of trip. This will also allow Health Navigators to access customer
feedback and trip performance data on transportation services provided
by Health Connector.
o EHR/Medical Record Subsystem: this subsystem refers to the systems used by
partner hospitals and clinics for booking medical appointments and maintaining
their appointments, including discharge and any subsequent referral activities.
Health Connector will develop a new interface with at least one of the healthcare
partner EHR.
Health Connector Back-end in Figure 4 and Figure 5 refers to new development as identified
above.
• Other: Additional relevant details for the system to de deployed are as follows
o Supporting systems: These are existing systems and are not part of Health
Connector project. However, the TMS will exchange data with these systems or
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 19
HIRTA staff may interact with these systems for certain operational functions, as
needed. Specifically, this refers to driver or vehicle information management,
vehicle maintenance management, customer service management, safety event
reporting. HIRTA currently uses capabilities within Routematch Demand
application for completing such functions but other off-the-shelf products are also
commercially available. List of these functions that will get utilized include:
Managing driver information.
Managing vehicle inventory.
Tracking vehicle maintenance and availability status.
Managing customer service complaints.
Managing safety events (e.g., incidents, accidents or others).
o Data Storage: Traveler applications will store data locally as allowed by their
devices and as authorized by Travelers. Vehicle and TMS subsystems will
communicate over cellular data communication for operational data exchange. All
data is exchanged in real-time (at a configurable frequency). Data is temporarily
stored on the vehicle to support offline operations in the event of communication
failures. On the central side, TMS data will be stored in a relational database in
the AWS cloud storage. Data is stored in a live database to support real-time
operations and then processed and archived for reporting in a historical database
Figure 5 provides a system context diagram for HIRTA Health Connector along with data flows:
Data flows are labeled according to the data ID used in Table 3 and Table 4 and later in the
document to provide the context for data exchange between systems and for data-related
discussions.
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 20
Figure 5. High-level System Context Diagram for Health Connector (Source: HIRTA team)
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 21
Table 3 provides an overview of data flow between system components identified earlier. HIRTA
will be the owner of all data generated by the system (exceptions listed in Section 4) and majority
of the data generated by the Health Connector system will be collected, stored, processed,
analyzed and archived within HIRTA TMS which will be maintained by Uber Technologies. Data
collected and generated by the wayfinding system will be stored within that system and will be
made available on-demand per HIRTA-defined terms and conditions.
For external systems from Access2Care and third-party service providers, data exchange will be
based on open APIs and relevant data will be stored within HIRTA TMS per approved terms and
conditions between HIRTA and external parties, as discussed in Section 4. Details of the API will
be included in the SyRS document (Task 6 deliverable).
While Table 3 identifies datasets in the context of existing and future systems at HIRTA, the
datasets are identified keeping the replicability of Health Connector system in mind. These
datasets and terms used are common in paratransit/demand response industry and are
applicable to most commercially available platforms/solutions. Most of the trip-related datasets
are available in current Routematch Demand product, as indicated in Table 1.
Table 3. Data Needs Summary
ID
Data
High-level Description
Systems Involved
1
Traveler profile
Traveler’s personal details as provided
as part of registration.
Traveler-end system,
HIRTA TMS
2
Traveler eligibility
Traveler’s eligibility for a funding source
or program; also verified with funding
entities (e.g., Medicaid).
HIRTA TMS, Eligibility
Management
System/Funding Source
3
Fleet information
Details on HIRTA’s vehicles; also,
details on third-party vehicles.
Supporting System (Driver
and vehicle management),
HIRTA TMS
4
Driver information
Details on HIRTA’s drivers; also, details
on third-party vehicles.
Supporting System (Driver
and vehicle management),
HIRTA TMS
5
Trip request
Traveler request for a trip from a web
or mobile device; some Travelers may
request over phone and use concierge/
customer care service.
Traveler-end system,
HIRTA TMS
6
Trip modification or
cancellation
Traveler’s request for modification to an
existing trip, including cancellation.
Traveler-end system,
HIRTA TMS
7
Trip status
Current information on upcoming trip.
Traveler-end system,
HIRTA TMS
8
Manifest
Time and location details on Travelers
to be picked up and dropped off by a
Driver during a shift.
Vehicle-end system,
HIRTA TMS
9
Vehicle location
Location and heading along with other
details for a vehicle in service.
Vehicle-end system,
HIRTA TMS
10
Trip performance
Trip-level log of actual time and
location for trips on the manifest along
with any no-shows and cancellation
events.
Vehicle-end system,
HIRTA TMS
11
Driver performance
Driver-level log of operational
performance on log on, on-time
performance, manifests completed.
Vehicle-end system,
HIRTA TMS
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
22
| Phase 1 Data Management Plan - HIRTA
ID
Data
High-level Description
Systems Involved
12
Travel time
Time needed to perform on-board
component of a trip.
Processed using Trip
Performance Data
13
Driver Messages
Log of messages sent by Drivers to
Dispatchers.
Vehicle-end system,
HIRTA TMS
14
Dispatcher Messages
Log of messages sent by Dispatchers
to Drivers.
Vehicle-end system,
HIRTA TMS
15
Fare Payment Log
Log of amount paid for a trip and
method of payment.
Vehicle-end system,
HIRTA TMS
16
Manifest (third party)
Time and location details on Travelers
to be picked up and dropped off by a
third-party Driver during a shift.
Vehicle-end system,
HIRTA TMS
17
Trip performance (third
party)
Trip-level log of actual time and
location for trips on the manifest along
with any no-shows and cancellation
events for trips delivered by a third-
party provider.
Vehicle-end system,
HIRTA TMS
18
Vehicle location (third
party)
Location and heading for a vehicle in
service along with other details for a
third-party provider.
Vehicle-end system,
HIRTA TMS
19
Driver Messages (third
party)
Log of messages sent by Drivers to
Dispatchers.
Vehicle-end system,
HIRTA TMS
20
Dispatcher Messages
(third party)
Log of messages sent by Dispatchers
to Drivers.
Vehicle-end system,
HIRTA TMS
21
Fare Payment Log
(third party)
Log of amount paid for a trip and
method of payment.
Vehicle-end system,
HIRTA TMS
22
Medicaid trip requests
Traveler request for Medicaid-funded
trips from a web or mobile device
through Access2Care; some Travelers
may request over phone and use
concierge service.
Traveler-end system
(Medicaid), Access2Care
system
23
Medicaid trip
performance
Trip-level log of actual time and
location for trips on the manifest along
with any no-shows and cancellation
events for trips delivered for Medicaid-
funded trips.
Access2Care system,
HIRTA TMS
24
Medical appointment
details
Consists of medical appointment date,
time and location (facility address and
doctor’s office) for a particular Traveler
HIRTA TMS, EHR system
25
Aggregated Summary
Aggregated data on driver, vehicle and
trip performance.
TMS Reporting
26
Traveler wayfinding
request
Requests initiated by Travelers to the
wayfinding system.
Traveler-end system,
Wayfinding system
27
Traveler wayfinding
guidance
Log of wayfinding information provided
to Travelers.
Traveler-end system,
Wayfinding system
28
Safety event
Log of incident and accidents by
vehicle/driver/trip.
Vehicle-end system,
HIRTA TMS, Supporting
System (Safety
Management)
29
Safety event report
Detailed reports by a safety event
(incident, accident) with response.
Supporting System (Safety
Management)
30
Trip history playback
Replay of trip events performed along
with location trail during a shift by a
driver.
HIRTA TMS
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 23
ID
Data
High-level Description
Systems Involved
31
System performance
Log of system performance, including
any failures.
HIRTA TMS
32
Information/referral
(I&R) request
Information and referral request.
DCHD I&R
33
Customer complaints
log
Log of customer complaints received
and actions taken.
Phone System,
Customer Service System
34
Customer survey data
and results
Customer data and survey conducted
by ISU of human use participants and
control group
Local database at ISU
35
Processed data for
controlled sharing
Data accessible to researchers,
Independent evaluation team and
USDOT
TMS Reporting
36
Public data for
USDOT-managed
System
Data to be made available to the
general public after further processing
and anonymization
USDOT-managed System
37
Cost and revenue data
Cost and revenue data by trip,
including actual cost, fare paid, funding
source share
HIRTA TMS and
Supporting System
(Accounting)
38
Wheelchair failure log
Summary of events referring to
situations when wheelchair lift could no
t
function at the time of pick-up or drop-
off.
HIRTA TMS/ Reporting
39
Medical appointment
status
Real-time status of progress on a
medical appointment resulting in an
impact on the pick-up time.
HIRTA TMS, EHR system
40
Discount coupon/credit
Discount coupons or credits applied by
trip
HIRTA TMS, Funding
Entity
41
Call center log
Call center statistics available from
HIRTA, DCHD and healthcare
providers, as available from phone
systems or manual logs.
Phone systems at HIRTA,
DCHD and healthcare
providers
42
Missed medical
appointments linked to
lack of transportation
access
Anonymized missed appointments
linked to transportation access
EHR or other systems
internal to healthcare
providers
43
Trip request (partners)
Trips manually requested by DCHD
and healthcare providers using HIRTA
TMS. To be tracked separately to
assess the benefit of such capability.
HIRTA TMS
3.2 Data Overview
Table 4 provides an overview of the data to be collected in the Health Connector system. It references
the data needs identified in Table 3 and provides additional information on the data to be collected,
type and scale of data involved and data collection methods.
Table 4 provides the following information for each dataset:
• Data: Refers to distinct category of data exchanged between two systems. Distinction is provided
by type of appointment (e.g., medical appointment or trip request), provider (e.g., in-house or
contracted), type of trip (e.g., Medicaid and non-Medicaid) since the level of aggregation or
anonymization needed will be different.
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
24
| Phase 1 Data Management Plan - HIRTA
• Dataset: Refers to the dataset that acts as the container for the data identified as follows:
o Admin: includes data that is required for administrative needs prior to a trip can be
provided (e.g., customer registration, eligibility management, fleet management/
maintenance). It also refers to any data that is part of routine process (e.g., safety
management, complaints).
o Driver: includes driver-level details on name, vehicle used, and their service performance
(revenue miles, revenue hour, on-time performance).
o Trip: includes trip-level data for Travelers and Drivers on location, time, fare payment.
Traveler, Driver and Trip identifiers are anonymized.
o Aggregated: refers to aggregated summary for a chosen time interval. Summary
available at Traveler, Driver /Vehicle, Provider and Trip level.
o Survey: refers to survey data and results. Details regarding this will be provided after the
IRB process is complete.
o Health: refers to medical appointment related data and any data collected by DCHD for
Health Navigation purposes.
o System Log: refers to data logged in the system to assess system performance and
reliability. Also, may include supportive information (e.g., communication log indicating
traffic delay).
o Wayfinding: refers to log of requests and pathways directions provided at device level.
• Description: Provides preliminary details on the fields available in a dataset. Further discussion
on this is available in Table 6 and Table 7 in the context of access control.
• Type and Scale: Provides the type of data included in the dataset. Also, provides a high-level
information on scale of data.
• Collection method: Provides information on how data is collected by the system.
• Format: Data that will be shared with the researchers and the USDOT will be in comma
separated value (CSV) format for non-spatial data and JavaScript Object Notation (JSON) for
spatial data. References to JSON is provided, as applicable in the table. Shape File (SHP) may
be used for spatial analysis and sharing of results from survey data. Please note that this format
does not indicate how systems components exchange data with each other.
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 25
Table 4. Data Overview
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
1
Customer
profile
Admin
Consists of personal details (e.g.,
name, addresses, contact information,
eligibility) and travel preferences (e.g.,
mobility aid, notification) for customers
stored in Traveler profile.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
3000 or less customers
Traveler input;
HIRTA or partner staff
input as concierge service
(HIRTA Customer care,
healthcare customer care,
Health Navigator)
CSV
2
Customer
eligibility for a
funding
source
Admin
Status of eligibility for each customer
for a funding source, as stored in
Traveler profile.
Type:
Text data,
Numerical data.
Scale:
3000 or less customers
Traveler input,
Provided by funding entity
CSV
3
Fleet
information
Admin
Consists of information on fleet (e.g.,
age, number of seats, accessibility).
Type:
Text data, numerical data.
Scale:
50 vehicles.
As maintained by HIRTA in
driver and vehicle
management (supporting)
system
CSV
4
Driver
information
Driver
Consists of information on driver
identifier and their status (e.g.,
experience, part time, full time,
contract, shift).
Type:
Text data, numerical data.
Scale:
50 drivers
As maintained by HIRTA in
driver and vehicle
management (supporting)
system.
CSV
5
Trip request
Trip
Consists of customer identifier, trip
identifier, date, time, and locations of
pick-ups and drop-offs.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
400 trips per day.
Traveler input;
HIRTA or partner staff
input as concierge service
.
CSV
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
26
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
6
Trip
modification
Trip
Consists of customer identifier, trip
identifier, date, time, and locations of
pick-up and drop-off.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
400 trips per day
Traveler input;
HIRTA staff input as
concierge service
.
CSV
7
Trip status
Trip
Consists of estimated time of arrival
and/or delay status, as applicable along
with pick-up location.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
400 trips per day
System-generated using
vehicle location and
driver/vehicle performance
data received in real-time
.
CSV
8
Manifest
Admin
Consists of all trips to be performed by
a driver on a particular shift. Trip details
provide necessary information needed
for a driver to perform a trip (e.g., trip
identifier, customer info, pick-up and
drop-off locations and times, fare to be
paid, mobility-aid needed). This dataset
is listed for reference purpose only and
is meant for internal operations
management. This will not be made
accessible to external entities. Trip
request, Trip status and Trip
performance datasets provide
necessary information for external
parties.
For on-demand services, manifest may
not be needed as vehicles are
dispatched in real-time.
Type:
Type:
Text data, numerical
data, temporal data,
positional data.
Scale:
Up 20 trips a day per
driver manifest.
System-generated using
confirmed trips after
runcutting and driver
assignment process is
complete.
Real-
time updates are made
to the trips and
driver/vehicle manifests if
there are any changes
through automated data
transmission by HIRTA TMS
communicating to the
vehicle-end system using
cellular communications.
Changes to manifest are not
stored.
CSV
(unformatted)
/ PDF
(formatted)
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 27
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
9
Vehicle
location
Trip
Consists of vehicle location and
heading along with time, speed, and
vehicle or driver identifier.
Current plan is for providing only
historical record since use case for
real-time data is unclear.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
Up to 20,000 records per
day at 30 second refresh
rate.
Automated data
transmission at a
configurable interval over
cellular communications.
CSV,
JSON
10
Trip
performance
Trip
Consists of actual times and locations
for pick-up and drop-off. Also, includes
information on no-shows and
cancellations, as applicable. Reasons
for no-shows and cancellation will be
included if available.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
400 trips per day
Automated data
transmission over cellular
communications; driver
input on on-board terminals.
CSV
11
Driver
performance
Driver
Consists of driver performance at trip or
aggregated level (e.g., miles driven as
revenue or deadhead, on-time
performance).
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
For up to 50 drivers
System-generated based on
trip performance data.
CSV
12
Travel time
Aggregated
Consists of time taken by driver/vehicle
for a particular trip leg, available by
origin and destination.
Type:
Numerical data, positional
data
Scale:
400 trips a day
System-calculated using trip
performance data.
CSV,
JSON
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
28
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
13
Driver
Messages
System Log
Consists of data messages sent by
Drivers. Includes vehicle, driver
identifier. This data is included to
support analysis as in some cases
results may not be conclusive due to
confounding factors but relevant
messages explaining a situation may
be available (e.g., construction detour,
traffic delay, slippery conditions,
unexpected dwell time due to
wheelchair cycle issue).
Type:
Text data, positional data,
temporal data.
Scale:
5-10 messages per day
per driver
Driver input on on-board
terminals.
CSV
14
Dispatcher
Messages
System Log
Consists of data messages sent by
Dispatchers. Includes vehicle and
driver identifier. This data is included to
support analysis as in some cases
results may not be conclusive due to
confounding factors but relevant
messages explaining a situation may
be available (e.g., driver asked to swap
vehicle mid-shift by dispatcher, no-
show not approved, Traveler waiting at
another pickup spot).
Type:
Text data, positional data,
temporal data.
Scale
:
100 messages per day
Dispatcher input in HIRTA
TMS.
CSV
15
Fare Payment
Log
Trip
Consists of log of fare paid by Traveler
and method of payment. Includes trip
identifier and customer identifier.
Type: Text data,
numerical data
Scale: 400 trips per day
Automated data
transmission over cellular
communications; driver
input on on-board terminals
for actual amount paid
(some customers may
overpay and balance is
applied to their account
which can be used towards
future trips).
CSV
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 29
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
16
Manifest (third
party)
Admin
Consists of all trips to be performed by
a driver on a particular shift. Trip details
provide necessary information needed
for driver to perform the trip (e.g., trip
identifier, customer info, pick-up and
drop-off locations and times, fare to be
paid, mobility-aid needed). This dataset
is listed for reference purpose only and
is meant for internal operations
management. This will not be made
accessible to external entities. Trip
request, Trip status and Trip
performance datasets provide
necessary information for external
parties.
For on-demand services, manifest may
not be needed as vehicles are
dispatched in real-time.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale
:
50-75 trips per day
Automated data
transmission over cellular
communications; driver
input on on-board terminals.
CSV
(unformatted)
/PDF
(formatted)
17
Trip
performance
(third party)
Trip
Consists of actual times and locations
for pick-up and drop-off. Also, includes
information on no-shows and
cancellations as applicable. Reasons
for no-shows and cancellation will be
included, if available.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
50-75 trips per day
Automated data
communication over
cellular; driver input on on-
board terminals
CSV
18
Vehicle
location (third
party)
Trip
Consists of vehicle location and
heading along with time, speed and
vehicle identifier.
Driver identifier may
not be available.
Current plan is for providing only
historical record since use case for
real-time data is unclear.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
Up to 5,000 records per
day at 30 second refresh
rate.
Automated data
communication over cellular
CSV,
JSON
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
30
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
19
Driver
Messages
(third party)
System Log
Consists of data messages sent by
Drivers. Includes vehicle, driver
identifier. This data is included to
support analysis as in some cases
results may not be conclusive due to
confounding factors but relevant
messages explaining a situation may
be available (e.g., construction detour,
traffic delay, slippery conditions,
unexpected dwell time due to
wheelchair cycle issue).
Type:
Text data, positional data,
temporal data
Scale:
5-10 messages per day
per driver for a total of
20 drivers.
Driver input on on-board
terminals
CSV
20
Dispatcher
Messages
(third party)
System Log
Consists of data messages sent by
Dispatchers. Includes vehicle and
driver identifier. This data is included to
support analysis as in some cases
results may not be conclusive due to
confounding factors but relevant
messages explaining a situation may
be available (e.g., driver asked to swap
vehicle mid-shift by dispatcher, no-
show not approved, Traveler waiting at
another pickup spot).
Type:
Text data, positional data,
temporal data
Scale
:
50 messages per day
Dispatcher input in HIRTA
TMS
CSV
21
Fare Payment
Log (third
party)
Trip
Consists of log of fare paid by Traveler
and method of payment. Includes trip
identifier and customer identifier.
Type: Text data,
numerical data
Scale: 400 trips per day
Automated data
transmission over cellular
communications for actual
amount paid.
CSV
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 31
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
22
Medicaid trips
requests
Trip
Trips requested by Travelers for
Medicaid. Consists of customer
identifier, trip identifier, date, time, and
locations of pick-ups and drop-offs.
Type:
Text data, numerical data,
temporal data, positional
data
.
Scale:
50-80 trips a day
Traveler/concierge input into
Access2Care system. From
Access2Care, trips
assigned to HIRTA will be
ingested in HIRTA TMS.
Current process of ingestion
is manual and it is currently
done on a daily basis for the
trips scheduled for the next
day. For ad-hoc/same day
trips, Access2Care calls
HIRTA to confirm and trips
are entered at that point.
A more frequent ingestion
will be needed for same-day
requests (e.g., return trips),
which are critical to Health
Connector. Since ConOps
discussions, the HIRTA
team has determined that
an automated ingestion will
be a better approach which
will automatically ingest the
trip if a same day trip is
booked by the Access2Care
system.
CSV
23
Medicaid trip
performance
Trip
Consists of actual times and locations
for pick-up and drop-off. Also, includes
information on no-shows and
cancellations as applicable. Reasons
for no-shows and cancellation will be
included if available.
Type:
Text data, numerical data,
temporal data, positional
data
.
Scale:
50-80 trips a day
Automated data
transmission over cellular
communications; Driver
input on on-board terminals
CSV
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
32
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
24
Medical
appointment
details
Health
Consists of medical appointment date,
time and location (facility address and
doctor’s office) for a particular
customer. Whether or not
transportation was requested or a
telehealth appointment was requested
will be included. Linked to a customer
identifier and trip identifier if a
corresponding transportation is booked.
Data to be shared will include
anonymized data on any link between
medical appointment and transportation
provided for those appointments.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
100 trips a day
Data entry in EHR
or
medical appointment
system
CSV
25
Trip Summary
Aggregated
Consists of aggregated data on trip
performance by different providers
(e.g., revenue miles, fares collected,
on-time performance, travel time, no-
shows, cancellations, missed trips).
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
Up to 400 trips a day
System-generated
CSV,
JSON
26
Traveler
wayfinding
request
Wayfinding
Consists of origin and destination
location requested for step-by-step
guidance by Traveler outdoors or
indoors. Time of request and device ID
(anonymized) will also be included.
Type:
Positional data, temporal
data.
Scale:
Requests for up to 50
trips a day
Data entry by Travelers/
caregivers on devices.
CSV/
JSON
27
Traveler
wayfinding
guidance
Wayfinding
Consists of the actual pathways
provided to the customer; Also
includes data on whether or not a
provided guidance was used by a
customer once provided.
Time of
request and device ID (anonymized).
Type:
Positional data, temporal
data
Scale:
Requests for up to 50
trips a day
System-generated step-
by-step pathways direction
as provided by the
wayfinding system;
depends on availability of
mapping data
CSV/
JSON
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 33
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
28
Incident/
accident
Admin
Consists of any incident or accident
event reported by Driver; Trip, vehicle
and driver identifier included for internal
analysis but only aggregated data by
safety event type per day will be
available for external use.
Type:
Text data,
Numerical data,
Positional data, temporal
data
Scale:
10 events per months
Driver input using on-board
terminals for a particular
safety event. Initial incident
data per report entered into
HIRTA TMS by Dispatcher
.
Final report after
investigation filed in Safety
management System by
Safety Program Manager.
CSV
29
Incident report
Admin
Consists of details of report after
investigation by the Safety Program
Manager.
Driver, Trip, vehicle and
driver identifier included for internal
analysis but only aggregated data by
safety event type per day will be
available for external use.
Type:
Text data,
Numerical data,
Positional data, temporal
data
Scale:
10 events per month
Filed in the Safety
Management System by
Safety Program Manager
CSV
30
Trip History
Playback
Trip
Consists of a replay of events
performed by a Driver during their shift.
Used for internal investigation of
customer complains. Listed here for
information purpose only. Not to be
made available to the external entities.
Type:
Video
Scale:
400 trips a day
System-generated using trip
performance data by HIRTA
TMS
MPEG,
CSV
31
System
performance
System Log
Consists of data on system reliability. It
will be generated on a daily basis and
will be grouped by failure type and
system component.
Type:
Numerical.
Scale:
N/A
System-generated; Analysis
CSV
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
34
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
32
Information/
referral
request
Health
Consists of information/referral
requests received by DCHD from
Dallas County residents and outcome
of efforts made by Health Navigators.
This data will help track if I&R effort
resulted in booking of an appointment.
Text data, numerical data,
temporal data, positional
data.
Scale:
500 new customers per
year. 1500 active
customers. Customers
typically active for 6-8
weeks.
Data entry; customer
Surveys in the I&R system.
There is no plan to link I&R
system with HIRTA TMS.
Therefore, information will
be stored in the I&R system
only.
CSV
33
Customer
complaints log
Admin
Consists of customer complaint
received, complaint date, resolution,
and resolution date. Will be
aggregated by complaint type and
provider type at daily level for
tracking customer complaints
received.
Type:
Text, numerical,
temporal.
Scale:
10 complaints per month
Data entry in Customer
Service system
CSV
34
Customer
survey results
Survey
Consists of analysis of survey data
designed to measure the project
outcomes. It will be managed by ISU.
Results will be shared after using
appropriate anonymization and
aggregation. Additional details will be
added regarding survey data once the
approach is finalized through the IRB
process.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
List of human participants
TBD
Survey methods and details
are yet to be determined.
Will be finalized before IRB
application filing in
November 2021.
CSV (non-
spatial), SHP
format
(spatial),
charts
35
Processed
private data
for controlled
sharing
Aggregated
Refers to anonymize and aggregated
reports at daily level that will be
provided to researchers and
independent evaluators.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
400 trips a day
System-generated by
processing information
stored in the reporting
database
CSV,
JSON
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 35
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
36
Public data for
USDOT-
managed
System
Aggregated
Refers to anonymized aggregated
reports at daily level that will be
provided for USDOT-managed
System.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
400 trips a day
System-generated by
processing information
stored in the reporting
database
CSV,
JSON
37
Cost and
revenue
summary
Aggregated
Refers to the cost and revenue data,
aggregated on a monthly basis.
Type:
Text data, numerical data,
financial data
Scale:
400 trips a day
System-generated by
processing information
stored in the reporting
database
CSV
38
Wheelchair
failure log
Aggregated
Refers to wheelchair failure log
aggregated on a daily basis by
vehicle.
Type:
Text data, numerical data,
temporal data, positional
data
Scale:
400 trips a day
System-generated by
processing information
stored in the reporting
database
CSV
39
Medical
appointment
status
Health
This is for internal use only and is
needed to track any changes in
medical appointments that also
require changes in transportation
appointments.
Type:
Text data, numerical data,
temporal data, positional
data
Scale:
100 trips a day
Data entry in EHR
or
medical appointment
system
CSV
40
Discount
coupon/credit
Trip
Consists of a log of discount code
applied to trips and amount of credit.
Available at trip level and will be
linked to Fare Payment Log.
Type:
Text data, numerical data,
temporal data, positional
data
Scale:
100 trips a day
Entered by Traveler or
concierge/ customer
service staff
CSV
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
36
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Description
Type/Scale
Collected Method
Format
41
Call center log
Admin
Call center statistics available from
HIRTA, DCHD and healthcare
providers, as available from phone
systems or manual logs
Type:
Text, numeric, temporal
Scale:
500 calls per day
Generated from phone
system
CSV
42
Missed
medical
appointments
linked to lack
of
transportation
access
Trip
Anonymized missed appointments
linked to transportation access
Type:
Text data, numerical data,
temporal data, positional
data
Manual record
CSV
43
Trip request
(partners)
Trip
Trips manually requested by DCHD
and healthcare providers using
HIRTA TMS. To be tracked
separately to assess the benefit of
such capability.
Type:
Text data, numerical data,
temporal data, positional
data.
Scale:
TBD
Manual entry
CSV
3. Data Overview
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 38
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 39
4 Data Stewardship
This section provides details concerning data stewardship. Data stewardship involves proper data
management throughout the data lifecycle, including, but not limited to, maintaining data quality
and safeguarding data.
4.1 Data Owner and Stewardship
Table 5 provides information on data title, data owner, data steward and federal sponsor as
follows:
• Data Title: Provides the title of the data and/or datasets that are assigned to the designated data
owner and/or data steward. Data and/or datasets with different data owners and/or data stewards
are listed separately. Datasets that have the same information for Owner, Steward and Sponsor
are all listed in the same row of the table for clarity.
• Data Owner: The data owner is the person or organization with the authority, ability, and
responsibility to access, create, modify, store, use, share, and protect the data. Data owners have
the right to delegate these privileges and responsibilities to other parties. For Phase 1, Data
Owner is identified as the team/team member creating the dataset.
• Data Steward: The data steward, at the direction of the data owner, is the person or organization
that is delegated the privileges and responsibilities to manage, control, and maintain the quality of
a data asset throughout the data lifecycle. The data steward may also apply appropriate
protections, restrictions, and other safeguards depending on the nature of the data, subject to the
direction of the data owner.
• Federal Sponsor: Refers to the federal entity that is the sponsor for this deployment. The federal
sponsor will assume the role of Data Owner once the dataset(s) are provided to them per BAA
and notice of funding opportunity (NOFO) requirements later in the project.
Data Title correspond to datasets listed in Table 3 and Table 4. Currently, HIRTA is listed as the
owner of all data, except in the cases where data is generated in external systems. ITS JPO is the
federal sponsor for all data sets created under the project. In future updates during Phases 2 and
3, as data is provided to the USDOT and made publicly available, USDOT may become the
owner of the dataset.
Where Federal Sponsor is not applicable (e.g., dataset is generated in systems outside the scope
of this project) it is marked N/A.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
40
| Phase 1 Data Management Plan - HIRTA
Table 5. Data Owner and Steward Information
Group
ID
Data Title
Data Owner
Data Steward
Federal
Sponsor
A
1) Customer profile,
2) Customer eligibility for a funding source,
3) Fleet information,
4) Driver information
28) Incident/ accident
29) Incident report,
33) Customer complaints log,
37) Cost and revenue summary
HIRTA
HIRTA
N/A
B
5) Trip request,
6) Trip modification,
7) Trip status,
8) Manifest,
9) Vehicle location,
10) Trip performance,
11) Driver performance,
12) Travel time,
13) Driver Messages,
14) Dispatcher Messages,
15) Fare Payment Log,
30) Trip History Playback,
31) System performance,
35) Processed private data for controlled
sharing,
40) Discount coupon/credit,
38) Wheelchair failure log,
35) Trip Summary
HIRTA
Uber
Technologies
ITS JPO
C
16) Manifest (third party),
17) Trip performance (third party),
18) Vehicle location (third party),
19) Driver Messages (third party),
21) Dispatcher Messages (third party),
22) Fare Payment Log (third party)
HIRTA
Provider TBD
ITS JPO
D
22) Medicaid trips requests,
23) Medicaid trip performance
Access2Care
HIRTA
N/A
E
24) Medical appointment details,
39) Medical appointment status
Healthcare
Partner
Healthcare
Partner
N/A
F
26) Traveler wayfinding request,
27) Traveler wayfinding guidance
HIRTA
Navi Lens and
other wayfinding
system provider
(TBD)
ITS JPO
G
32) Information/ referral request
DCHD
DCHD
N/A
H
34) Customer survey results
HIRTA
ISU
ITS JPO
I
36) Public data for USDOT-managed
System
USDOT
HIRTA
ITS JPO
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 41
4.2 Access Level
Access level is defined for accessing data as follows:
• Open - Data that can be used by the public with no or limited licensing restrictions. This
data is available to the public without needing to request permissions and will be provided
to the USDOT-managed Public System. These datasets will be provided after
anonymizing and aggregating raw private datasets to protect PII.
• Private- Data that cannot be shared with external users. Access to this data is limited
and only granted with IRB and Project Team approvals. Private data will be available
under the following subcategories of access levels:
o Personal Identifiable Information (PII)- Data that has PII included in the data
set. The access to this data will be restrictive to protect the PII based on IRB-
approved processes. Data in this category will have an operational purpose that
justifies its storage. For Health Connector, it will include Traveler details (name,
ID, location), Driver details (name, ID, vehicle details), Trip details (Trip ID that
can be linked to any personal identity), medical appointment details in the raw
dataset and any other dataset marked as PII as part of the IRB process.
o Proprietary– Licensed data from third parties or data that can reveal details on
proprietary methods and applications protected as part of intellectual property.
This data will be used for operational purposes. Any access to the data is
determined by usage agreements between the parties. Examples include
pathways structure for wayfinding, access to raw real-time data on service
management from Uber Technologies.
o Research- Data that is available for research, but users of the data must meet IRB
requirements before gaining access to the data. These datasets may have PII.
Examples of this data include survey data, trip-level data, driver-level data, Traveler-
level data.
4.2.1 Public/Open Datasets
TMS reporting platform as shown in Figure 6 will be used for making access to open data
available at aggregated level as part of data sharing requirement for USDOT-managed System. A
publicly available open data portal already provides travel time and speed data by TAZ and CT for
various US cities. A customized version for Health Connector will make additional data available
as identified in Table 6.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
42
| Phase 1 Data Management Plan - HIRTA
Figure 6. TMS reporting for Data Access (Source: Uber Technologies)
Table 6 provides a list of data that can be safely made available per the current understanding of
HIRTA team as of October 2021. As the team continues to work through the finalization of
PMESP, SyRS and HUA summary document along with the IRB process, further updates may
become available and will be incorporated. HIRTA team plans to provide another version of
updated DMP in November 2021 when PMESP, SysRS and Draft HUA summary document are
complete. This is included in the DMP schedule in Table 2.
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 43
Table 6. Health Connector Open Data Scope
ID
Data
Dataset
Access Portal
Safeguarding Methods and Processes
3
Fleet information
Admin
USDOT-
managed
System
Active HIRTA fleet data will be made publicly available “as is” given it does
not contain any PII or sensitive information.
Active fleet data for contractors or TNCs will be made available excluding
any PII (e.g., license plate). Key purpose of making this dataset available
will be to analyze capacity, reliability and availability by vehicle.
9
Vehicle location
Trip
USDOT-
managed
System
Historical log of raw vehicle location, time, heading and speed will be made
available along with anonymized vehicle or driver ID (not both) for HIRTA
vehicles.
18
Vehicle location (third
party)
Trip
USDOT-
managed
System
Historical log of raw vehicle location, time, heading and speed will be made
available along with anonymized vehicle ID for third-party vehicles.
25
Trip Summary
Aggregated
USDOT-
managed
System
Aggregated trip summary data at TAZ and CT level. At the least,
aggregated operational summary (trips completed, vehicles in use, average
travel time, average revenue miles, average deadhead miles, fare collected)
by hour, funding program, provider and underserved group will be provided.
Scope and level of aggregation for this data is still being finalized and will
not be available until IRB process is complete.
28
Incident/accident
Admin
Secure FTP
Details involving HIRTA assets will be made available to report on safety
events on a monthly basis. No PII will be included.
29
Incident report
Admin
Secure FTP
Details involving HIRTA assets will be made available to report on safety
events along with any safety response taken on a monthly basis. No PII will
be included.
36
Public data for
USDOT-managed
System
Aggregated
USDOT-
managed
System
Data described in this table will primarily be available. However, this list will
be updated as the HIRTA team determines additional data that can be
made publicly available through appropriate anonymization and aggregation
exercise.
38
Wheelchair failure log
Aggregated
USDOT-
managed
System
Daily report on data aggregated at vehicle level will be available on
wheelchair failure logs indicating number of failure events by vehicle.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
44
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Access Portal
Safeguarding Methods and Processes
12
Travel time
Aggregated
USDOT-
managed
System
Access to real-time data cannot be provided as continuous stream of real-
time data can be used to reverse engineer proprietary algorithms.
Travel time data by analyzing anonymized historical trip data will be
available at CT and TAZ level.
Travel time in the context of the project refers to only vehicle component of
the Complete Trip. The w
ayfinding leg of the trip that involves walking or use
of mobility aid is going to be calculated separately. Wayfinding data doesn’t
have PII since that is stored by device ID and nodes used in the pathway
and pathway steps. However, this is listed currently as private dataset and
will be made publicly available based on IRB approval.
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 45
4.2.2 Private Datasets
Controlled access to private data will be made available in CSV and JSON format (as shown in
Table 4) to researchers and USDOT Independent Evaluators through a web-based data access
portal, TMS Reporting. A snapshot of TMS Reporting is provided in Figure 7.
Figure 7. Snapshot of TMS reporting used to Access Driver, Trip Level and Program Level
Data (Source: Uber Technologies)
Table 7 provides a list of private data that can be securely made available per the current
understanding of HIRTA team as of October 2021. As the team continues to work through the
finalization of PMESP, SyRS and HUA summary document along with the IRB process, further
updates may become available and will be incorporated. HIRTA team plans to provide another version
of updated DMP in November 2021 when PMESP, SysRS and Draft HUA summary document are
complete. In particular, feasibility of providing identified dataset will be assessed during SysRS
development process. This is included in the DMP schedule in Table 2.
This section will be updated again in December 2021 after the IRB process is complete.
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 46
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 47
Table 7. Scope and Availably of Private Datasets
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
1
Customer profile
Admin
TMS reporting
• Research: This data
consists of PII information
on Travelers/customers
and cannot be made
available without
anonymization and
controlled access.
Uber dataset anonymizes personal information (name,
address) and assigns a universally unique identifier (UUID),
Traveler UUID, to the dataset. The UUID is mapped internally
to Traveler’s Uber ID and is inaccessible to unauthorized
users. This approach wil
l be used to make controlled access to
Traveler profile available at CT or TAZ level. Primary purpose
will be to provide data for researching transportation needs of
underserved population.
Planned data to be included: Traveler UUID, undeserved
population category, mobility need, eligibility for funding
sources (multiple sources may be applicable), recurring or ad-
hoc trip customer,
2
Customer eligibility
for a funding source
Admin
TMS reporting
• PII: Identified as a critical
information and will not be
made available.
Approach taken for Data ID #1 provides the eligibility
information.
4
Driver information
Driver
TMS reporting
• Research: some PII data
may be included so
available only for
research.
Uber dataset currently includes Driver PII (ID and name) when
making information available through TMS Reporting. This will
be explored further with IRB before deciding if information on
Drivers can be made available as is.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
48
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
5
Trip request
Trip
TMS reporting
• Research: Trip-level
details include location
and time information
which can be an issue if
somehow Rider identity is
determined (e.g., looking
up address in public
records). Trip-level data
will be made available
only for research with an
agreement that Traveler
identity will be fully
protected.
Uber dataset anonymizes Trip information (trip id, name,
address) and assigns a unique identifier (Trip ID) to the
dataset. The public Trip ID is mapped internally to Uber’s
internal Trip ID in the system and is inaccessible to
unauthorized users. This approach will be used to make
controlled access to trip data available.
Planned data to be included: Trip ID (anonymized), requesting
device id (anonymized), device type, pick-up location, drop-off
location, pick-up time, drop-off time, mobility aid requested,
funding source requested, whether or not request completed,
gap in requested time and scheduled time
6
Trip modification
Trip
TMS reporting
• Research: Trip-level
details include location
and time information
which can be an issue if
somehow Rider identity is
determined (e.g., looking
up address in public
records). Trip-level data
will be made available
only for research with an
agreement that Traveler
identity will be fully
protected.
Same approach as Data ID #5 will be used.
Planned data to be included: Trip ID (anonymized), device id
(anonymized), device type, original/modified pick-up location,
original/modified drop-off location, original/modified pick-up
time, original/modified drop-off time, whether or not request
completed, gap in requested time and scheduled time
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 49
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
7
Trip status
Trip
TMS reporting
• Research: Trip-level
details include location
and time information
which can be an issue if
somehow Rider identity is
determined (e.g., looking
up address in public
records). Trip-level data
will be made available
only for research with an
agreement that Traveler
identity will be fully
protected.
• Proprietary: access to
real-time data cannot be
provided as continuous
stream of real-time data
can be used to reverse
engineer proprietary
algorithms.
Same approach as Data ID #5 will be used.
Planned data to be included: To check the reliability of ETA, a
log of Trip ID, ETA and actual time of arrival will be made
available for a requested time period.
Any log of delay communicated to Traveler, if available, will be
provided as supporting dataset
8
Manifest
Admin
TMS reporting
Private dataset used for only
internal operational purposes.
Contains PII data.
Not made available externally since other data is sufficient.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
50
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
10
Trip performance
Trip
TMS reporting
• Research: Trip-level
details include location
and time information
which can be an issue if
somehow Rider identity is
determined (e.g., looking
up address in public
records). Trip-level data
will be made available
only for research with an
agreement that Traveler
identity will be fully
protected
• Proprietary: access to
real-time data cannot be
provided as continuous
stream of real-time data
can be used to reverse
engineer proprietary
algorithms.
Same approach as Data ID #5 will be used.
Planned data to be included: Trip ID (anonymized), driver ID,
vehicle ID, scheduled/actual pick-
up location, scheduled/actual
drop-off location, scheduled/actual pick-up time,
scheduled/actual drop-off time, whether or not a no-show, no-
show reason, whether or not cancelled, cancellation reason.
11
Driver performance
Driver
TMS reporting
• Research: raw driver-level
data includes PII (name).
Aggregated driver
performance can be
provided
Approach identified as part of Data ID #4 will be used for
aggregation.
Planned data to be included: Driver ID, revenue miles,
revenue hours, trips completed, revenue collected, rating
13
Driver Messages
System Log
TMS reporting
• Research: sensitive
operational information
may be available that
should not be made
public. However, can be
made available for
researchers to investigate
and resolve any
confounding factors.
Log of messages will be provided as is.
Planned data to be included: Driver ID, Vehicle ID, time,
location, message text
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 51
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
14
Dispatcher
Messages
System Log
TMS reporting
• Research: sensitive
operational information
may be available that
should not be made
public. However, can be
made available for
researchers to investigate
and resolve any
confounding factors.
Log of messages will be provided as is.
Planned data to be included: Driver ID, Vehicle ID, Dispatcher
ID, time, location, message text
15
Fare Payment Log
Trip
TMS reporting
• Research: while actual
payment data is not there
,
fare payment data is
connected with trip
performance data and
contains PII.
Trip anonymization approach as discussed for Data ID #5 will
be used to provide log of fare payment.
Planned data to be included: Trip ID,
actual cost, fare required,
fare paid, discount coupon/code, payment method.
16
Manifest (third
party)
Admin
TMS reporting
Private dataset used for only
internal operational purposes.
Contains PII data.
Not made available externally since other data is sufficient.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
52
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
17
Trip performance
(third party)
Trip
TMS reporting
• Research: Trip-level
details include location
and time information
which can be an issue if
somehow Rider identity is
determined (e.g., looking
up address in public
records). Trip-level data
will be made available
only for research with an
agreement that Traveler
identity will be fully
protected
• Proprietary: access to
real-time data cannot be
provided as continuous
stream of real-time data
can be used to reverse
engineer proprietary
algorithms.
Same approach as Data ID #5 will be used.
Planned data to be included: Trip ID (anonymized), vehicle ID,
driver ID, scheduled/actual pick-up location, scheduled/actual
drop-off location, scheduled/actual pick-up time,
scheduled/actual drop-off time, whether or not a no-show, no-
show reason, whether or not cancelled, cancellation reason.
19
Driver Messages
(third party)
System Log
TMS reporting
Research: sensitive
operational information may
be available that should not
be made public. However,
can be made available for
researchers to investigate and
resolve any confounding
factors.
Log of messages will be provided as is.
Planned data to be included: Driver ID, Vehicle ID, time,
location, message text
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 53
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
20
Dispatcher
Messages (third
party)
System Log
TMS reporting
Research: sensitive
operational information may
be available that should not
be made public. However,
can be made available for
researchers to investigate and
resolve any confounding
factors.
Log of messages will be provided as is.
Planned data to be included: Driver ID, Vehicle ID, Dispatcher
ID, time, location, message text
21
Fare Payment Log
(third party)
Trip
TMS reporting
Research: while actual
payment data is not there,
fare payment data is
connected with trip
performance data and
contains PII.
Trip anonymization approach as discussed for Data ID #5 will
be used to provide log of fare payment.
Planned data to be included: Trip ID,
actual cost, fare required,
fare paid, fare promotion, payment method.
22
Medicaid trips
requests
Trip
TMS reporting
• Research: Trip-level
details include location
and time information
which can be an issue if
somehow Rider identity is
determined (e.g., looking
up address in public
records). Medicaid trips
may have other HIPAA-
protected details as well.
Trip-level data will be
made available only for
research with an
agreement that Traveler
identity will be fully
protected
Uber dataset anonymizes Trip information (trip id, name,
address) and assigns a unique identifier (Trip ID) to the
dataset. The public Trip ID is mapped internally to Uber’s
internal Trip ID in the system and is inaccessible to
unauthorized users. This approach will be used to make
controlled access to trip data available.
Planned data to be included: Trip ID (anonymized), pick-up
location, drop-off location, pick-up time, drop-off time, whether
or not request completed, gap in requested time and
scheduled time
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
54
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
23
Medicaid trip
performance
Trip
TMS reporting
• Research: Trip-level
details include location
and time information
which can be an issue if
somehow Rider identity is
determined (e.g., looking
up address in public
records). Trip-level data
will be made available
only for research with an
agreement that Traveler
identity will be fully
protected
• Proprietary: access to
real-time data cannot be
provided as continuous
stream of real-time data
can be used to reverse
engineer proprietary
algorithms.
Same approach as Data ID #5 will be used.
Planned data to be included: Trip ID (anonymized),
scheduled/actual pick-up location, scheduled/actual drop-off
location, scheduled/actual pick-up time, scheduled/actual
drop-off time, whether or not a no-show, no-show reason,
whether or not cancelled, cancellation reason.
24
Medical
appointment details
Health
TMS reporting
• PII: HIPAA-protected
details
Whether or not a transportation access was provided for a
medical appointment is the only data made available; also
identified if the medical appointment was a no-show.
Planned data to be included: Trip ID (anonymized), No-show
status, No-show reason.
26
Traveler wayfinding
request
Wayfinding
Navi Lens
• Proprietary: the format in
which request is received
is proprietary given there
is no standard available.
• Research: Controlled
access to researchers will
be made available.
Information will be made available only by anonymized device
ID.
Planned data to be included: Device ID, wayfinding origin,
wayfinding destination
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 55
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
27
Traveler wayfinding
guidance
Wayfinding
Navi Lens
• Proprietary: the format in
which direction is
provided is proprietary
given there is no standard
available.
• Research: Controlled
access to researchers will
be made available.
Information will be made available only by anonymized device
ID.
Planned data to be included: Device ID, wayfinding origin,
wayfinding destination, whether or not direction provided,
reason for not providing, pathways details for direction
provided, customer feedback (if available)
30
Trip History
Playback
Trip
TMS reporting
Private dataset used for only
internal operational purposes.
Contains PII data.
Not made available externally since other data is sufficient.
31
System
performance
System Log
TMS reporting
• Proprietary: details may
include server logs that
may reveal unintended
information
Only aggregated information of failure logs by component on a
daily basis, will be available.
Planned data to be included: failure type, occurrences,
severity, resolution time, repeat problem
32
Information/referral
request
Health
DCHD System
PII: HIPAA-protected details
Standard report on referral success will be made available by
anonymized Traveler ID (as determined per approach for Data
ID # 1)
33
Customer
complaints log
Admin
SFTP
• PII: may include some PII
information so wide
release will be denied.
• Research: will be made
accessible for research,
particularly to supplement
findings from other
analyses.
Will be aggregated by complaint type and provider type at
daily level for tracking customer complaints received.
Planned data to be included: customer complaint received,
provider, date received, complaint date, resolution, and
resolution date.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
56
| Phase 1 Data Management Plan - HIRTA
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
34
Customer survey
results
Survey
SFTP
• PII: some PII information
may be present
• Research: will be made
accessible for research,
particularly to supplement
findings from other
analyses. Survey results
will be critical for several
performance measures
A detailed approach for survey data to be collected, terms and
conditions for human subject participation, survey design,
analysis plan still needs to be determined and will be finalized
as part of IRB/HUA process and PMESP finalization.
35
Processed private
data for controlled
sharing
Aggregated
TMS reporting
Private dataset as discussed
earlier in this table:
A controlled access to data, discussed earlier in this Table will
be made available using appropriate level of anonymization,
protection and aggregation
37
Cost and revenue
summary
Aggregated
TMS reporting
• Research: cost and
revenue data are
sensitive until finalized
Data will be made available for research only. There are
several factors involved in managing cost and revenue data
and sometimes it is not done until a reporting period is
complete. So, data based on formal request will be provided
after proper validation.
Planned data to be included: Reporting period (monthly,
quarterly, annual), number of trips completed, total revenue
miles, total revenue hours, total cost, total revenue, total fare
paid, trips completed, number of Travelers served
39
Medical
appointment status
Health
TBD
PII: HIPAA-protected details
Only limited information available indicating whether or not
transportation access was provided for a medical appointment
and if the medical appointment was a no-show.
Planned data to be included: Trip ID (anonymized), No-show
status, No-show reason.
40
Discount
coupon/credit
Trip
TMS reporting
Same as Data ID #15 and
#21
Same as Data ID #15 and #21
41
Call center log
Admin
SFTP
Same as Data ID #33
Same as Data ID #33
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 57
ID
Data
Dataset
Access
Portal
Reason(s) the Data is Private
Safeguarding Methods and Processes
42
Missed medical
appointments linked
to lack of
transportation
access
Trip
SFTP
Same as Data ID #39
Same as Data ID #39
43
Trip request
(partners)
Trip
TMS reporting
Same as Data ID #5
Same as Data ID #5
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan – HIRTA | 58
4.2.3 Access Request
Access to the Health Connector system and data is governed by user type, and access licenses
and agreements, except for open data as defined Section 4.2.1 . The system, in general, is not
publicly accessible. Access is based on the functional roles and responsibilities of each user
requiring access to the system. Access to the system is permitted to the level of need for each
user to perform his or her role. For example, this would include customer service representatives
booking trips on behalf of riders and facilities, discharge planners management outflow of patients
from area health care facilities, supervisors and managers tasked with oversight of the program
and independent third-party evaluators requiring access to data for performance and program
level reporting.
HIRTA can make data available to researchers based on terms and conditions yet to be
determined. This section will be completed after IRB process is complete and human use
approval (HUA) summary is available.
4.2.4 Related Tools, Software and/or Code
Health Connector includes several commercially available subsystems, as explained in Section
3.1.
Controlled access to private data will be made available in CSV (non-spatial) and JSON (spatial)
format to researchers and USDOT Independent Evaluators through a web-based data access
portal for download, TMS Reporting as identified in Table 4 and Table 5. Addition data with
analytics capability will also be accessible to researchers through secure login to TMS Reporting
platform providing the user to review and report on the system through the use of visual
dashboards and graphs.
Public data for the USDOT-managed System will be made available after anonymization and
aggregation, also in CSV and JSON formats.
4.2.5 Relevant Privacy and/or Security Agreements
The proposed project will make available the aggregate data and metadata for research
purposes. Any PII, Confidential business information (CBI) and electronic personal health
information (ePHI) as defined under the HIPAA will be collected, maintained and protected in
secure data management system in accordance with all applicable state and federal laws. Written
agreements entered into between HIRTA and Uber Technologies; the mobile application’s terms
of use entered into by the customer; and Uber Technologies privacy policy shall govern the
collection and use of the data generated through use of the Software. Per these agreements,
HIRTA and Uber Technologies will each protect all data access to ensure maximum security.
This section will be updated further once the IRB process is complete in December 2021. Also,
additional agreements needed between HIRTA and Access2Care for Medicaid data; and HIRTA,
EHR software and healthcare care provider for medical appointment data are expected be
completed before the ICTDP is complete. While Uber Technologies will deploy the interfaces,
HIRTA will be the lead for Phase 2/3 and will be entering in agreements needed with third parties
on behalf of the HIRTA team. However, it is likely that details may not be finalized within Phase 1
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 59
completion timeframe. The HIRTA team is tracking interfaces as risk items in the Risk Register.
Once developed, the HIRTA team will submit agreements for approvals from the IRB.
4.3 Re-Use, Redistribution, and Derivative Products
Polices
HIRTA maintains ownership of the electronic data of their customers, and its users, that is
submitted by or imported by HIRTA into the Software in connection with HIRTA use of the
Software.
The system will be licensed to HIRTA. HIRTA will comply with all licensing regulations set forth in
the agreement. This project incorporates several off the shelf licensing components as well as
planned custom configurations and potentially new feature builds as an outcome of the project
pilot. The licenses will include licensing agreements from Uber Technologies, as well as other
third-party vendors such as Navi Lens.
Open data through USDOT-managed system will be made available under Creative Commons,
Attribution Non-Commercial License. Please note that the complete details of license are
currently not available. This section will be updated once the details are available.
Table 8 provides further details.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
60
| Phase 1 Data Management Plan - HIRTA
Table 8. Licensing for Private Data
Dataset Title
License Used
Reason(s) for Non-Open License
Trip Level Data
Uber Technologies Licensing
Agreement
Contractual between HIRTA & Uber
Technologies. Access can be
provided through license
agreement with HIRTA. Access will
be granted based on defined roles
and program responsibilities.
Driver Level Data
Uber Technologies Licensing
Agreement
Contractual between HIRTA & Uber
Technologies. Access can be
provided through license
agreement with HIRTA. Access will
be granted based on defined roles
and program responsibilities.
4. Data Stewardship
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 61
Dataset Title
License Used
Reason(s) for Non-Open License
Aggregate Program Data
Uber Technologies Licensing
Agreement
Contractual between HIRTA & Uber
Technologies. Access can be
provided through license
agreement with HIRTA. Access will
be granted based on defined roles
and program responsibilities.
HIRTA Admin Data
Uber Technologies Licensing
Agreement
Contractual between HIRTA & Uber
Technologies. Access can be
provided through license
agreement with HIRTA. Access will
be granted based on defined roles
and program responsibilities. .
System Log
Uber Technologies Licensing
Agreement
Contractual between HIRTA & Uber
Technologies. Access can be
provided through license
agreement with HIRTA. Access will
be granted based on defined roles
and program responsibilities. .
Health Data
Uber Technologies Licensing
Agreement
Includes sensitive data with PII
Contractual between HIRTA & Uber
Technologies. Access can be
provided through license
agreement with HIRTA. Access will
be granted based on defined roles
and program responsibilities
Wayfinding Data
Navi Lens Licensing Agreement
Pathways information is proprietary
given there is currently no standard
in use outside GTFS-pathways as
available for the fixed route transit
service.
4.4 Data Storage and Retention
Storing and retaining the data is a key part of the data steward’s responsibilities to manage,
control, and maintain the quality of a data asset throughout the data lifecycle. All data generated
by Health Connector will be stored in the Amazon Web Service (AWS) cloud storage. The data
will be made available for 7 years.
4. Data Stewardshi
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
62
| Phase 1 Data Management Plan - HIRTA
HIRTA in collaboration with project stakeholders will determine the data storage and retention
policies. These policies will include but not limited to the following:
• User Data Retention and Deletion Policy - defines how long user data should be
retained before it is deleted or anonymized and how long user data may be accessible by
team members.
• Exceptions to User Data Retention and Deletions Policy: May include specific
circumstances such as maintaining data for security, safety, fraud and abuse. Other
considerations would include legal proceedings or insurance claims.
• Privacy Policies - include how data/ information is collected, used, and shared; and
choices and options regarding this data/ information.
• Access Management Policy - policy specifically managing access to Uber data and
information sources
• Change Management Policy - Defining the change and release management
requirements to be followed when implementing system changes to information and data
resources.
• Data Classification, Handling and Sharing Policy - Defining classification and handling
requirements for processing and storing data using system information resource and
sharing data with external entities.
4.4.1 Storage Systems
While system will be hosted on AWS servers within the United States, actual storage details for
the system are currently not known. Also, some of the details will not be made publicly available
for security reasons. Detailed storage needs will be determined through the requirements
development process in Phase 1 and the section will need to be revisited further in Phase 2
during System Design and testing as better details on storage needs, archival plan and other
details become available (e.g., frequency and granularity of actual data needs after the review of
initial dataset).
A summary of storage systems, per current understanding is provided in Table 9.
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Table 9. Summary of Storage Systems
Data Storage
System Type
Dataset Title(s)
Initial Storage
Date
Frequency of
Update
Archiving and
Preservation
Period
Uber Technologies -
AWS Hosted Storage
Traveler trip requests
may be logged
locally. This is still
being investigated
and will be updated
as details are
available during
system requirements.
Trip Level Data
Feb 2023 Daily
Through Feb
2025
Uber Technologies -
AWS Hosted Storage.
Some data may be
temporarily stored on
Driver tablets/phones
to work in offline
mode (e.g., due to
data disconnection)
before getting
synchronized
Driver Level
Data
Feb 2023 Daily
Through Feb
2025
Uber Technologies -
AWS Hosted Storage
Aggregate
Program Data
Feb 2023 Daily,
Monthly,
Annual
Through Feb
2025
Uber Technologies -
AWS Hosted Storage
HIRTA Admin
Data
Feb 2023 Daily
Through Feb
2025
Uber Technologies -
AWS Hosted Storage
System Log
Feb 2023 Daily
Through Feb
2025
Uber Technologies -
AWS Hosted Storage
Health Data
Feb 2023 Daily
Through Feb
2025
Navi Lens System
Wayfinding Data
Feb 2023 Daily
Through Feb
2025
4. Data Stewardshi
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Data Storage
System Type
Dataset Title(s)
Initial Storage
Date
Frequency of
Update
Archiving and
Preservation
Period
HIRTA Local Data
Center
Open HIRTA
Admin Data
Feb 2023
Daily
Through Feb
2025
ISU Local Data Center
Open-survey
data and results
TBD
TBD
TBD
U.S. DOT-managed –
Public System
USDOT-
managed
System
Aug 2023
Daily
Five years
4.4.2 Data Storage System Description
HIRTA will be transitioning from the current cloud-based hosting service to AWS-based hosting
service within the United States. This section will be completed when the process is complete.
The system will use a relational database format in the collection, storage, and output of the data
and metadata. The data collection, operational, and reporting processes are practical and within
industry practices. The use of technology enables the protection of the data collection
methodology and seeks to use standards where available.
4.4.3 Cybersecurity Policies
Core Security Engineering team at Uber Technologies will deliver secure system and services for
the infrastructure and products. The team will manage all aspects of security architecture,
engineering and operations focused operational risks driver product delivery in compliance with
international standards and regulations. Further existing policies (not public), will govern
cybersecurity incident management policy, defining the policies for managing cybersecurity
incidents and threats that impact confidentiality, integrity or data availability.
Terms of use of NaviLens application will be as described in the conditions of use
(https://www.navilens.com/terms
). Also, privacy terms will be governed by Navi Lens privacy
policy (https://www.navilens.com/privacy).
HIRTA does not have cyber security or privacy policies developed. Interfaces with Access2Care
and EHR provider (Epic/Unity Point) are still under discussion so those cannot be included at this
time. The document will be updated when these details are available. HIRTA team plans to
finalize these details before Phase 2 design.
4.4.4 Data Security Policies and Procedures
Preliminary assessment related to data and system confidentiality, availability, integrity and
authenticity are provided below:
• Confidentiality: HIRTA will be the owner of all datasets for the data collected within
HIRTA TMS. Only authorized users, per their role, are provided access to specific
modules of the system and the data generated by those systems, as identified in the
system configurations. For Health Connector, data flow diagram by user group in ConOps
will be used to identify access levels for system end users.
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Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 65
When medical appointment data is made available by the healthcare provider, an
information release form will have to be signed by the parties accessing such information.
Consent form is approved by both healthcare provider and Patient/Traveler.
Data within Access2Care and Navi Lens systems will be made available to HIRTA per
agreement signed by HIRTA with them but currently both of those organizations are
marked as the owners of data generated in their systems. Further details on data
ownership are clarified in Table 5.
• Availability: The system will have high-availability requirement and HIRTA’s service level
agreement (SLA) with Uber Technologies and Navi Lens will govern the availability of
their products. The SLA language is still to be determined but will focus on the following
key aspects of the system availability:
o Definition of types of expected issues and their severity.
o Identification of vendor response time and level of support to be provided
depending on the severity of issue and the level of support needed, in the event
an issue is reported.
o Identification of key performance indicators (KPIs) with respect to system
performance.
o Guidance on planned system/data maintenance schedule.
o Vendor support cost as applicable by the severity of an issue.
o Clear description on what may constitute as a maintenance update, system
upgrade or new enhancement, and what is covered per the vendor-agency
contract.
o Identification of vendor credits as applicable in the event of a system outage
/unavailability.
o Terms and conditions attached to the data breach or other security issues.
o Definition of roles and responsibilities (vendor, agency, third parties) with respect
to system maintenance and incident response.
• Integrity: System functions will be made available to HIRTA staff and its partners
according to their roles and responsibilities. Except for those privileges, no user is
authorized to make any changes. Also, system audit trail shows if and what changes
were made by a user.
• Authenticity and non-repudiation: Data sent and received between devices are logged
with contextual information (e.g., vehicle to TMS messages have vehicle ID, location and
time stamp attached). Also, when trip requests are sent by customers, those will include
the customer information as only registered customers are allowed to book trips with
HIRTA.
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4.4.5 Back-up and Recovery Policies and Procedures
Vendors will use a highly reliable system and data environments will be designed to protect any
data loss due to routine and ad-hoc maintenance processes that may require data back-up and
recovery.
For Uber Technologies, globally, policies are in place and systems are monitored in a real-time on
a 24-hour basis with several undisclosed Network Operations Centers. The governing policy
defines the standard for backup and recovery management of primary data generated by
production systems and services. It outlines the requirements for taking backups, ensuring their
security and integrity, monitoring and testing the backup and restoration process.
Back-up and recovery policies incorporate specific policies regarding eligibility for data stores,
new datastores and existing datastores. Unless otherwise authorized backups include primary
data, instances of all storage system and storing source of truth data. Incrementation and
differential backups are also performed.
Access to backup data must be protected by access control list. Access must also be limited to
the team responsible for production support of the storage system and data.
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Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
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Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
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5 Data Standards
5.1 Data Standards
A list of standards, as applicable to vehicle, central environment, and data access and sharing are
discussed in the following subsections.
5.1.1 Vehicle Data Standards
Currently, only planned vehicle equipment is a tablet or a mobile device for Drivers that will
exchange data over cellular data network.
HIRTA team also plans to explore the potential to provide advanced infotainment service on
vehicles to provide information to travelers (e.g., orientation information upon arrival at the
hospital). This was identified as low priority need at ConOps stage. However, it is included as an
optional requirement based on subsequent stakeholder discussions and implementation
approach (e.g., hardware and content management) will be revisited during design stage as part
of Phase 2.
None of the planned features require a vehicle area network (VAN) except obtaining real-time
status on wheelchair availability. Fault codes can be received over Society of Automobile
Engineers (SAE) J1939 network if a wheelchair lift interlock module is available on a vehicle.
Based on system requirements discussion, need for real-time monitoring of such failure is not
considered essential.
5.1.2 Data Communication Standards
Vehicle to central communication will be accomplished using Internet Protocol (IP)-based
transport protocols, Transmission Control protocol (TCP) or User datagram Protocol (UDP).
Data transport will occur over 4G or 5G network with a carrier-level encryption using a private
Access Point Name (APN).
5.1.3 Data Access Protocols
At least the following protocols will be used:
• HTTPS: Hypertext Transfer Protocol Secure (HTTPS) will be used for accessing data
over the web or mobile browsers. Secure Socket Layer (SSL)-based security as provided
at OS-level will be used by mobile apps.
• SFTP: Secure file transfer protocol (SFTP) will be used to make access available to open
data from HIRTA’s local data center.
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5.1.4 Data Sharing Standards
Data will be shared using the following standard formats:
• CSV: non-spatial data will be shared using text-based files using CSV format. Files will
include a header and data. Details on the header fields will be available in the metadata.
• JSON: TMS Reporting portal currently makes spatial data available over JSON and the
same practice will be used for sharing spatial data.
• SHP: Shape file format may be used for sharing spatial analysis conducted using survey
data.
5.1.5 Open Data Standards for Transactional Data
Open data, currently in practice in the transit industry, is applicable to fixed-route services only to
openly share data related to Traveler information. For Health Connector, which will be a demand
response service, only applicable standard is GTFS-flex. GTFS-flex, however, is limited to trip
planning for demand response services and is mostly useful when multiple agencies are involved
given the effort required in putting together the feed. Given the limited utility to the project, use of
GTFS-flex is not planned.
Overall, open data-based exchange is not applicable to this project since there is currently no
transactional data standard for functions such as booking, service management, payment in use
for demand response services in the industry. Existing and planned open data standards for
transactional information, General on-Demand Feed Specification (GOFS) or Transactional Data
Standard (TDS), are still not ready for mainstream deployment based on our assessment. HIRTA
team will continue to monitor that development for Phase 2 but currently taking the open API
approach for interfacing with external systems (Access2Care, EHR system or third-party service
providers).
Exchange with wayfinding system will be done using a standard format based on GTFS-
pathways, which has been adopted for outdoor and indoor wayfinding by transit industry.
However, officially there is no standard for indoor environment beyond transit industry.
5.1.6 Open API
Interfaces with Access2Care and Epic EHR are planned using Uber’s open Representational
State Transfer (REST) APIs. Detailed API document is available on Uber developer page
(https://developer.uber.com/
, accessed Aug 2021).
Epic’s open API will be needed to access medical appointment data. Details of the API are
available at https://open.epic.com/
(accessed Aug 2021). Epic APIs are also compliant with Fast
Health Interoperability Record (FHIR) and use eXtensible markup language (XML) or JSON for
data exchange.
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Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
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5.2 Versioning
Datasets released at a particular interval (e.g., daily, monthly) will follow a naming convention (to
be defined by Dec 2021) so it is easily identifiable by users. Also, datasets will be accompanied
by metadata so users are able to determine information on what is included. If there are any
changes in the data structure between versions, it will be identified in the metadata. Also, the
DMP will be updated accordingly. Further details on metadata update process is described in
Section 5.3.3.
Change and Release management policies govern the release of updated versions for the
system.
5.3 Metadata
Routematch and other Uber products from Uber Technologies as discussed earlier will be part of
the HIRTA TMS that will generate and maintain the datasets identified in this document. Data will
also be generated in the third-party system (EHR, Access2Care) and will be accessed by HIRTA
TMS through secure interfaces. Navi Lens system will contain its own data but will be shared by
the Health Connector data access portal.
The following sections provide further details on the Metadata that will be included with the
shared data.
5.3.1 Metadata Types
In the context of Health Connector project, metadata is defined as follows.
• Business Metadata: Data that is used to provide business value and context for the
data. The following subcategories are used to define this metadata:
o Discovery: Metadata that is used to allow other users to find and work with the
data. This metadata includes information on why the data was collected, what
type of data is it including, general description of the dataset types, location the
data was collected, when it was collected, what techniques/technologies where
used, and who created that data.
DMP has identified data and datasets that will be generated, collected, stored
and archived by the Health Connector system in Table 3 and Table 4. Owner and
steward of the data and datasets are also identified in the DMP.
Details of survey data are currently not available and will not complete until the
PMESP is finalized and the IRB process is complete.
o Licensing: Metadata that provides the licensing for the data and allows users to
know the rights they have to use, any restrictions on copying, publishing,
distributing, transmitting, citing or adapting the data.
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Section 4.2 defines the access levels for public and private data per HIRTA
team’s current understanding. This will be further reviewed as system
requirements get finalized along with PMESP. Also, IRB will have to approve if
the data can be provided as planned.
Terms and conditions of data use will be covered by the agreements between
HIRTA and providers of systems as follows:
Written agreements entered into between HIRTA and Uber Technologies;
the mobile application’s terms of use entered into by the customer; and
Uber Technologies privacy policy shall govern the collection and use of
the data generated through use of the Software.
Access to wayfinding system data will be governed by licensing terms
set by Navi Lens.
Access to Medicaid data will be governed by terms of the agreement as
entered into by HIRTA and Uber Technologies with Access2Care.
Access to healthcare data will be covered by 1) consent release signed
by healthcare provider, Traveler/patient, HIRTA and Uber Technologies;
2) terms and conditions as set by EHR provider (Epic) and Uber
Technologies, and subsequently HIRTA and Uber Technologies. Note
that the health data scope is limited to what is defined in this DMP.
Also, for access to data and use through TMS Reporting will be governed by Uber
Technologies privacy policy (
https://www.uber.com/legal/en/document/?country=united-
states&lang=en&name=privacy-notice ).
• Technical Metadata: Data that is used to provide technical details on the data, as
defined under the following categories
o Data Schema: Metadata that documents the exact fields in the data including,
field name, description, data type, and notes. Currently, this information is
available at dataset level for Uber Technologies, however, exact fields and other
details are being determined during interface requirement development as part of
systems requirements development process. A sample of Trip-level dataset (not
finalized) as available through TMS Reporting is provided in Table 10. Please
note that the schema may evolve through Phase 2 design and development,
however, a finalized schema for datasets, including columns and descriptions will
be included once the systems requirement document is complete by November
2021.
Table 10. Trip-Level Data Description
Data
Column Label
Trip
Status (e.g., completed, driver cancel)
Trip ID
Comments
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Data
Column Label
Rider & Driver
Info
Rider ID (UUID) (for managed riders)
Rider First Name (for managed riders)
Rider Last Name (for managed riders)
Rider Email (for managed riders)
Seats Requested
Driver Name
Driver Last Lame
Vehicle License
Vehicle VIN
Vehicle ID
Vehicle Capacity
Voucher name (if applicable)
Location
Route
City
Pickup Address
Pickup Lat
Pickup Long
Dropoff Address
Dropoff Latitude
Dropoff Longitude
Distance (miles)
Time
Pickup Date
Pickup Time
Drop Off Date
Drop Off Time
Request Timezone Offset from UTC
Duration (minutes)
Transaction
Date
Transaction Type (e.g., rider fare)
Expense Code
Expense Memo
Payment Method
Invoices
Transaction Amount
Fare
Subtotal
Taxes
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Data
Column Label
Fees
Tip
Total fare
Rider fare portion
Organization fare portion
Type
Service (e.g., program name)
Program
Policy name (e.g., fare policy name)
Rider Group Name (for managed riders)
o Data Processing: Metadata that documents any data processing that was done
to the data from the data inception (when the data was produced) to when it was
delivered to the USDOT. This will be applicable to Aggregated dataset which will
be anonymized and aggregated, available through TMS Reporting and USDOT-
managed System. Also, metadata as it relates to the processing of survey data
(data cleanup exercise, anonymization, aggregation) will be included.
o Data Impact Log: Refers to metadata that provides information on any changes
to data during the collection period. Any time the data changes in a unique way
that is not expected in the experimental design either by internal or external
forces it will be documented. An example of changes expected are listed below:
Testing of system components and features.
Addition, modification, or deletion of a new feature in one or more system
components.
Replacement of a system component, either due to replacement of a
system provider or due to availability of new/upgraded component from a
provider.
Modification in server infrastructure used for storage and providing data
access.
Modification in schema or structure for data tied to system components,
data format for the data made available and metadata.
Modifications in policies, system components and tools related to data
storage, management, access and sharing.
Any changes required due to externalities will also be documented. Potential
factors that may impact the data collection on the project include:
Extended impact of a severe weather event impacting data collection
due to communication outage or other issues (e.g., flooding).
Regulatory changes, government policy changes or unanticipated data
needs from funding entities that require additional /reduced data
collection.
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Intelligent Transportation System Joint Program Office
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Major change in trip volume as service expands.
• Static Metadata: Metadata that is mostly static that describes key parts of the project.
Data on fixed pick-up and drop-off locations (e.g., designated spot outside a hospital or a
senior center to pick up Travelers) along with any relevant details (e.g., any signage or
digital infrastructure at the stop) as those get defined will be included. Also, this category
of metadata will include the application inventory (list of applications involved, version
installed, vendor, SLAs, owner, next planned update/upgrade, last update/upgrade any
other relevant information) and fleet inventory (ID, age, capacity, propulsion, digital
infrastructure). Further, this category will include data on the sensor/visual marker
installed outside and inside facilities to support outdoor and indoor wayfinding.
5.3.2 Metadata Structure
This section provides the structure used to communicate metadata information. Metadata will be
provided in CSV format along with the datasets being provided.
Metadata will be stored with the data to allow the users of the data, including future deployers,
researchers and the public all key information in a single location. Files will be provided in a way
that maintain the structure of the data, so users of the data can easily determine what is project
metadata and what is specific dataset metadata.
Each metadata package will include:
Summary information for datasets included in the package along with any other reference
information as needed (e.g., DMP, privacy policy, public information on additional details
on data collection, as available).
CSV file with static metadata.
For each dataset, technical metadata in CSV format with schema, processing and license
metadata.
5.3.3 Metadata Update Process
Metadata will be kept up to date so the current version is always shared with the data when there
is a change. The following steps will be followed:
1. When it is learned that any of the changes in the dataset (e.g., examples listed in Section
5.3.1) trigger a change in metadata, CCB will meet to identify changes necessary in the
metadata structure. In most cases, this meeting will occur months in advance of a change
to the dataset.
2. If follow-up discussions and expert advice is needed, the CCB will meet with the subject
matter expert from the dataset provider (e.g., Uber Technology, Navi Lens, ISU) to assess
any impact on the metadata structure due to change in dataset (e.g., if column dropped
or renamed in a new software release). The impact may be on business metadata,
technical metadata or static metadata, or a combination of the 3 metadata types.
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3. If changes to the metadata is necessary, the vendor will be requested to provide a
modified metadata file in a similar format as described in Section 5.3.1.
4. The CCB will assess any changes to the DMP as discussed in Section 2.1 and approve
the updates to the DMP.
5. HIRTA PML will obtain the revised metadata file and include that within the appropriate
folder structure for file sharing.
6. HIRTA team will verify once the new dataset based on revised metadata structure is
generated (e.g., when changes are in technical and static metadata).
7. Metadata structure will be updated to reflect the changes and appropriate files will be
updated.
8. Updated metadata structure along with the new dataset is uploaded to the USDOT-
managed System. For researchers accessing data through Uber data portals, a link to
download the revised metadata structure will be provided at the time of accessing the
data request.
.
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Intelligent Transportation System Joint Program Office
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Appendix A. Acronyms and Glossary
Access2Care
A transportation broker for State of Iowa Medicaid program that performs booking and scheduling
and works with service providers such as HIRTA for successful delivery of Medicaid-eligible trips.
ADA – Americans with Disabilities Act
Refers to the civil rights legislation passed and signed into law in 1990 to prevent discrimination
against people with disabilities.
API- Application Programming Interface
Software middleware that allows two devices or applications to exchange data with each other.
APN: Access Point Name
A communication gateway for enabling cellular data communications over a carrier network.
Public or private APN configurations are used depending on data security needs.
AWS: Amazon Web Service
A commercial cloud-based hosting service provided by Amazon.
BAA- Broad Agency Announcement
A procurement instrument used by USDOT.
Billing
Refers to the process of invoicing third-party funding sources (e.g., Medicaid) after a successful
delivery of a trip. Billing is typically done on a monthly basis.
CHNA - Community Health Needs Assessment
Refers to the Community Health Needs Assessment Report developed by Dallas County in 2019.
CCB- Change Control Board
A body of subject matter experts tasked to manage change control process for work products,
schedule or other relevant matters related to a project or program.
CDL- Concept Development Lead
Key project team member tasked with leading Phase 1 concept development activities.
Appendix A. Acronyms and Glossary
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CO: Contract Officer
The CO will serve as the USDOT point of contact for any concerns related to the contracts.
COR - Contract Office Representative
The Contract Office Representative will serve as the USDOT representative for this project and is
responsible for coordination and review of the proposer’s work.
Cost Allocation
Refers to the process of associating a funding source that should be billed for a trip in a shared
ride scenario when riders covered by separate funding sources share the vehicle for their trips
and trip purposes at the same time.
CSV- Comma Separated Value
A common text-based file format that is supported by many platforms and programs.
CT- Census Tract
A geographic region defined for the purpose of collecting census data.
CTAA – Community Transportation Association of America
One of the project Partners who will lead stakeholder engagement on this project.
DCHD – Dallas County Health Department
One of the project Partners who will lead integration with health care services.
DR-Demand Response
Refers to a service that is not run on a fixed route or a schedule (e.g., dial-a-ride, vanpool etc).
This requires making trip booking by contacting the service provider (e.g., HIRTA). However, DR
is different than an ADA Paratransit service which is provided as a complement to a fixed route
and is governed by specific requirements provided in 49 CFR- Part F. HIRTA operates only DR
Service in Dallas County and all discussion in this document is related to DR Service.
Dispatching
Refers to an operations management function which involves assigning vehicle, tracking fleet
location, managing schedule adherence, managing trip manifests and other operational functions.
DMP – Data Management Plan
The Data Management Plan is Task 3 of Phase 1 and will describe the approach for data
collection, processing, storage and utilization.
DOT – Department of Transportation
Appendix A. Acronyms and Glossary
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Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 79
The government department responsible for transportation. In this report, this generally refers to
either the State of Iowa’s DOT or the United States DOT referred to as Iowa DOT and USDOT,
respectively.
EDI – Electronic Data Interchange
In this context, refers to the electronic data interchange (EDI) format messages developed by
HIPAA following American National Standards Institute (ANSI) X12 standard for electronic data
exchange and are used to communicate with third-party health care provider systems (e.g.,
Medicaid).
EHR – Electronic Healthcare Record
Refers to the healthcare information management system used by hospitals for patients’
healthcare-related appointments, transactions, and records management.
FHIR- Fast Healthcare Interoperability Record
A standard developed to describe and exchange health records in electronic format.
FHWA- Federal Highway Administration
A USDOT agency in-charge of highway transportation.
FTA- Federal Transit Administration
A USDOT agency in-charge of public transportation.
GTFS – General Transit Feeds Specification
GTFS is a standard to provide static public transportation schedule information. The standard has
been expanded to include real-time passenger information (GTFS-real-time), flexible services
(GTFS-flex) and accessible routing within stations (GTFS-pathways).
HIPAA – Health Insurance Portability and Accountability Act of 1996
Provides guidelines for data protection of sensitive patient health information.
HIRTA - Heart of Iowa Regional Transit Agency
Rural, regional public transit agency in central Iowa. HIRTA will serve as Proposer/Applicant for
the Complete Trip - ITS4US project.
HL7 – Health Level Seven International
A not-for-profit, standards developing organization focused on electronic health information.
HN-Health Navigator
Refers to services provided by Dallas County Health Department to Dallas County residents in
identifying resources as necessary for improving social determinants of health.
Appendix A. Acronyms and Glossary
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HUA- Human Use Approval Summary
A deliverable in Phase 1 for Task 8 that outlines the process to be used for human subject
participation in the program for research and evaluation purposes.
HTTPS: Hyper Text Markup Language Secure
A protocol for accessing data/information over internet using Transport Layer Security (TLS)/
Secure Socket Layer (SSL).
ICTDP – Integrated Complete Trip Deployment Plan
The Integrated Complete Trip Deployment Plan is a deliverable of Task 13 under Phase 1.
I&R: Information and Referral
Refers to public and private entities that help their customers in identifying resources for health
and human services and other needs.
IPFP - Institution, Partnership, and Financial Plan
The Institution, Partnership and Financial Plan is a deliverable of Task 10 under Phase 1.
IRB- Institutional Review Board
An institutional body that reviews and approves research methods to ensure ethical standards are
followed, particularly when involving human subjects.
ISU– Iowa State University
Iowa State University is a public research university with multiple campuses in the State of Iowa
and will be engaged as the research and evaluation partner in Phases 2 and 3.
IVR: Interactive Voice Response
A technology that allows humans relying on phone systems to interact with computer programs
using natural voice or alphanumeric input using phone keys. This is an alternative used to provide
services to populations that may not have access to web-based devices.
IP- Internet Protocol
A network layer protocol for enabling data exchange over Internet.
JSON: Java Script Object Notation
Open standard and human readable data format for storing and transmitting electronic data.
KPI – Key Performance Indicators
Represents primary metrics used to assess the success of a project or operations.
Appendix A. Acronyms and Glossary
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 81
LEP – Limited English Proficiency
Refers to individuals who have a limited ability to read, speak, write, or understand English.
LTE: Long Term Evaluation
A telecommunication standard for wireless communications using mobile devices, also referred
as 4
th
generation wireless.
MOD: Mobility-on-demand
A USDOT program that intends to support the develop of an ecosystem that provides safe,
reliable and sustainable solution for all. MOD includes both trips made by Travelers or Trip
replacements (e.g., courier network services (CNS) such as food delivery).
MPM: Mobility Performance Metrics
MPM is a program being led by the FTA to develop performance measures that focus on new
mobility modes (e.g., micromobility, TNC).
NDSP- Non-Dedicated Service Provider
NDSP refers to operators providing service under contract (e.g., taxis) to an agency (e.g.,
HIRTA).
NEMT – Non-emergency Medical Transportation
The provision of transportation to patients for medical appointments, lab visits, and other routine
care. Generally, used in the context of Medicaid service only.
NOFO- Notice of Funding Opportunity
Formal announcement of availability of funding by US federal agencies for one of the financial
assistance programs.
PII – Personally Identifiable Information
Refers to any data that can distinguish an individual, either alone or when linked with other
available data.
PML-Program Management Lead
HIRTA project team member in-charge of managing all project and program management
activities.
Provider
Provider in this context mainly refers to an entity performing service delivery for requested trips,
sometimes also referred as service provider. the HIRTA team have also used healthcare partners
as providers in some cases but referred as ‘healthcare providers.’
Appendix A. Acronyms and Glossary
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
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REL- Research and Evaluation Lead
HIRTA team member responsible for managing the research and evaluation as part of Phase 3
and guiding the concept development and deployment activities as part of Phase 1 and 2.
Reservation
Refers to the act of booking a trip based on a request from a customer. Reservation is available
to only to registered customers.
REST- Representational State Transfer
A popular protocol to enable data exchange over the Internet using web APIs. HTTP/HTTPS is
used for communication protocol and data in HTML, JSON, XML or other formats may be used
for exchange.
SAE- Society of Automobile Engineers
Professional standards development organization, primarily focused on aerospace, automotive,
and commercial vehicles (e.g., trucking).
Scheduling
Refers to the process of identifying driver and vehicle resources and their runs/shifts for a given
workday. Scheduling is typically performed for all requests received until 24 hours in advance.
Booking within 24-hour notice and on-demand is offered but not encouraged due to limited
system capacity and resources.
SDL- Systems Development Lead
HIRTA team member responsible for all systems engineering aspects of the project.
SEL- Stakeholder Engagement Lead
HIRTA team member responsible for stakeholder engagement focused activities.
SFTP- Secure File Transfer Protocol
Protocol used to securely transfer file between networked devices.
SEMP – System Engineering Management Plan
A System Engineering Management Plan describes how systems engineering process of
planning, design, and deployment is applied to a project.
SHP- Shape File Format
Common spatial data format developed and regulated by Esri.
Appendix A. Acronyms and Glossary
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
Phase 1 Data Management Plan - HIRTA | 83
SMP – Safety Management Plan
A Safety Management Plan describes the steps to be taken to ensure the safety of the project
stakeholders and beneficiaries.
Smart Device
Refers to smartphone, smartwatch and similar personal devices that may be internet enabled and
are equipped with sensors.
TAG – Transportation Advisory Group
The TAG is a diverse group of community stakeholders and business representatives interested
in the advancement and improvement of public transportation in the HIRTA service area.
TAZ- Traffic Analysis Zone
A geographical unit used to conduct traffic /transportation analysis, constructed using census
block information.
TCP- Transmission Controls Protocol
A transport layer protocol that is focused on assured delivery of data packets over an IP network.
TDS: Transactional Data Standard
Open data standard for exchanging transactional data (booking, payment, service coordination)
between different systems or system components. Available in TCRP Report 210 - Development
of Transactional Data Specifications for Demand-Responsive Transportation
(http://www.trb.org/Main/Blurbs/180593.aspx
)
TMS- Transportation Management System
All systems and tools to be used by HIRTA for managing day-to-day delivery of transportation
services. This will be provided by various products offered by Uber Technologies.
TNC – Transportation Network Company
Encompasses a group of companies that provide on-demand Ridehailing services.
UUID-Universal Unique Identifier
Encrypted label used for assigning a unique ID to a field in a computer system, network or
program.
UDP- User Datagram Protocol
A transport layer protocol that uses connectionless datagrams for applications that need time-
sensitive data transmission but do not require assured delivery
Appendix A. Acronyms and Glossary
U.S. Department of Transportation
Office of the Assistant Secretary for Research and Technology
Intelligent Transportation System Joint Program Office
84
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Wayfinding
Refers to the tools and technologies that assist in orientation, locating objects, and step-by-step
navigation to destinations in outdoor and indoor environments using visual markers, sensors or
physical signage.
