Data Management and Governance Practices at Transportation Agencies Monday, February 26, 2018 2:00-3:30 PM ET TRANSPORTATION RESEARCH BOARD
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Data Management and Governance Practices at Transportation Agencies
Monday, February 26, 2018 2:00-3:30 PM ET
TRANSPORTATION RESEARCH BOARD
The Transportation Research Board has met the standards and requirements of
the Registered Continuing Education Providers Program. Credit earned on
completion of this program will be reported to RCEP. A certificate of completion
will be issued to participants that have registered and attended the entire session.
As such, it does not include content that may be deemed or construed to be an
approval or endorsement by RCEP.
Purpose
Discuss NCHRP Synthesis 508. Learning Objectives At the end of this webinar, you will be able to:
• Describe key concepts in data management and governance
• List current data management and governance practices
NCHRP Synthesis Report 508: Data Management and Governance Practices NCHRP Project 20-05/ Topic 47-05
NCHRP is a State-Driven Program
– Suggest research of national interest
– Serve on oversight panels that guide the research.
• Administered by TRB in cooperation with the Federal Highway Administration.
• Sponsored by individual state DOTs who
Practical, ready-to-use results • Applied research aimed at
state DOT practitioners • Often become AASHTO
standards, specifications, guides, syntheses
• Can be applied in planning, design, construction, operations, maintenance, safety, environment
Synthesis Objective
• Develop a collection of transportation agency data management practices and experiences
• Demonstrate how agencies currently access, manage, use and share data
Today’s Speakers
• Nasir Gharaibeh, Texas A&M University • Johanna Zmud, Texas A&M Transportation
Institute • Jared Causseaux / Josh Whitaker, Florida
Department of Transportation • Moderator: Peggi Knight, Iowa Department of
Transportation
Data Management & Governance Practices at Transportation Agencies
NCHRP Synthesis 508
Research Team Nasir Gharaibeh, Johanna Zmud, Isaac Oti, David Schrank,
Texas A&M Transportation Institute Texas A&M University
February 26, 2018
Project Panel Members (Topic 47-05)
• CHAD T. BAKER, California Department of Transportation
• JAMES P. HALL, University of Illinois at Springfield
• DAVID HURST, VHB
• PEGGI KNIGHT, Iowa Department of Transportation
• ARLENE MATHISON, University of Minnesota Centre for Transportation Studies
• BENITO O. PEREZ, District of Columbia Department of Transportation
• JACK R. STICKEL, Alaska Department of Transportation and Public Facilities (retired)
• JOSHUA CLAY WHITAKER, Florida Department of Transportation
• KATHERINE A. PETROS, Federal Highway Administration (Liaison)
• TIANJIA TANG, Federal Highway Administration (Liaison)
• LISA LOYO, Transportation Research Board
• THOMAS PALMERLEE, Transportation Research Board
2
NCHRP Synthesis Studies Staff
• JON M. WILLIAMS, Program Director, IDEA and Synthesis Studies • TANYA M. ZWAHLEN, Consultant
3
Complexity and Amount of Transportation Data
4
CAD
Geospatial databases
Multi-media
Attribute databases
Other
• Multiple uses/business functions
• Multiple databases
• Multiple forms
• Increasing volume Rule of thump: Corporate
data double every 18 months
Inventory Construction Crash Other
Objective & Scope
• Objective: Discuss a collection of transportation agency data management practices and experiences.
• Topics: Data Governance
Data Warehousing and Cloud Computing
Data Integration and Sharing
Data Quality
5
Methods
• 2-Phase Survey DOTs Responses: 43 (Phase 1) & 34 (Phase 2)
MPOs & Municipalities Responses: 19 (Phase 1) & 11 (Phase 2)
• Interviews: Three DOTs (Alaska, Iowa, Nebraska)
One Local Agency (Chicago Metropolitan Agency for Planning)
• Literature Review 28 publications
Websites of majority of state DOTs and FHWA
6
Webinar Segments
7
• Practices in Data Governance
• Practices in Data Integration and Sharing
• Practices in Data Quality
• Findings
Practices in Data Governance
8
Data Governance
• Data Governance: Establishment, execution, and enforcement of authority over the management of data assets
• Examples: Florida DOT
Minnesota DOT
US DOT
9
Data Life-Cycle
Adapted from Ladley (2012)
Does your agency have a designated data governance board/council?
10
19% (8 agencies)
44% (19 agencies)
37% (16 agencies)
YesNoIn development
Practice at DOTs
Does your agency have designated data coordinators?
11
60% (26 agencies)
14% (6 agencies)
26% (11 agencies)
Yes
No
In development
Practice at DOTs
What data in your agency have designated stewards?
12
0 10 20 30 40 50 60 70 80 90 100
OthersProject design and materials data
Pavement work history dataTravel modeling data
Real estate dataBridge work history data
Transportation improvement programs dataEnvironmental impact and compliance data
Project construction dataInventory and condition data for other assets
Financial dataContracts/procurement data
Traffic monitoring dataCrash Data
Bridge inventory & condition dataRoadway inventory
HPMSPavement inventory & condition data
% of DOT respondents
Practice at DOTs
To what extent do the following factors limit progress on instituting data governance in your
agency?
13
21
16
6
19*
10
14
14
11
1
2
12
3
0 20 40 60 80 100
Lack of staffing
Lack of resources
Hard to justify the costand effort
Other mission-relatedissues are more pressing
% of Respondents
MajorFactor
MinorFactor
Not anIssue
* indicates number of respondents
Practice at DOTs
• While only 1 out of 19 agencies indicated they have a designated data governance board/council, 5 indicated they have designated data coordinators.
14
Practice at Local Agencies
5 agencies
12 agencies
2 agencies
Yes
No
In development
Does your agency have designated data coordinators?
What data in your agency have designated stewards?
15
Practice at Local Agencies
0 2 4 6 8 10 12 14 16 18
Project construction dataHPMS
Project design and materials dataInventory and condition data for other assets
Bridge work history dataPavement work history data
OthersReal estate data
Environmental impact and compliance dataBridge inventory & condition data
Contracts/procurement dataPavement inventory & condition data
Traffic monitoring dataFinancial data
Crash DataRoadway inventory
Transportation improvement programs dataTravel modeling data
No. of local agency respondents
To what extent do the following factors limit progress on instituting data governance in your
agency?
16
8
5
4
7*
2
4
4
3
1
2
2
1
Lack of staffing
Lack of resources
Hard to justify the cost andeffort
Other mission-related issuesare more pressing
No. of respondents
MajorFactor
MinorFactor
Not anIssue
*indicates number of respondents
Practice at Local Agencies
Practices in Data Warehousing and Cloud Computing
17
What data in your agency are maintained in data warehouses or marts?
18
0 10 20 30 40 50 60 70 80 90 100
OthersReal estate data
Project design and materials dataTravel modeling data
Environmental impact and compliance dataPavement work history data
Inventory and condition data for other assetsContracts/procurement data
Bridge work history dataProject construction data
Transportation improvement programs dataPavement inventory & condition data
Financial dataHPMS
Crash DataTraffic monitoring data
Bridge inventory & condition dataRoadway inventory
% of DOT respondents
Practice at DOTs
What data in your agency are archived systematically to retain historical information?
19
0 10 20 30 40 50 60 70 80 90 100
OthersTravel modeling data
Real estate dataEnvironmental impact and compliance data
Inventory and condition data for other assetsBridge work history data
Transportation improvement programs dataPavement work history data
Contracts/procurement dataProject design and materials data
Financial dataBridge inventory & condition data
Crash DataProject construction data
Roadway inventoryHPMS
Traffic monitoring dataPavement inventory & condition data
% DOT respondents
Practice at DOTs
Approximately, what percentage of your agency’s transportation-related data is currently stored and
managed using commercial cloud computing services?
20
6% (2 agencies)
3% (1 agency)
71% (22 agencies)
10% (3 agencies)
10% (3 agencies)
21-50%
11-20%
1-10%
None
Unknown
Practice at DOTs
What data in your agency are maintained in data warehouses or marts?
21
Practice at Local Agencies
0 2 4 6 8 10 12 14 16 18
Project construction dataProject design and materials data
Pavement work history dataOthers
Real estate dataInventory and condition data for other assets
Bridge work history dataFinancial data
Contracts/procurement dataEnvironmental impact and compliance data
HPMSPavement inventory & condition data
Bridge inventory & condition dataCrash Data
Transportation improvement programs dataTravel modeling data
Traffic monitoring dataRoadway inventory
No. of local agency respondents
What data in your agency are archived systematically to retain historical information?
22
Practice at Local Agencies
0 2 4 6 8 10 12 14 16 18
Project construction data
Bridge work history dataPavement work history data
HPMSOthers
Project design and materials data
Bridge inventory & condition dataTraffic monitoring data
Real estate dataRoadway inventory
Contracts/procurement dataPavement inventory & condition data
Financial dataCrash Data
Travel modeling data
No. of local agency respondents
Approximately, what percentage of your agency’s transportation-related data is currently stored and
managed using commercial cloud computing services?
23
3 agencies
5 agencies
1 agency
1-10%
None
Unknown
Practice at Local Agencies
Practices in Data Integration and Sharing
24
Which of these data sets are integrated in your agency to serve various business needs?
25
0 10 20 30 40 50 60 70 80 90 100
B&CA&JA&I
A&BA&CA&GA&E
% of DOT respondents
Practice at DOTs
What location referencing methods are used in your agency?
26
0
20
40
60
80
100
Geographiccoordinates
Routemilepoint
Link− node Routereference
post
Routestreet
reference
MultilevelLRS
Other
% o
f age
ncie
s Practice at DOTs
How does your agency share data with outside users (public and private entities)?
27
0
20
40
60
80
100
Online (openaccess)
Upon request Not sharedoutside agency
Online (pre-authorized
access)
Other
% o
f age
ncie
s
Practice at DOTs
What strategies would improve (or have improved) data sharing and access within your
agency?
28
16
23
23
15*
10
6
4
15
3
2
1
2
3
0 20 40 60 80 100
Reduced use of hardware andsoftware that require specialized
data format
Improved database managementsystems
Increased use of web-based datastorage and access
Improved metadata
% of DOT respondents
MajorEffect
MinorFactor
No effect
Notapplicable
* indicates number of respondents
Practice at DOTs
Which of these data sets are integrated in your agency to serve various business needs?
29
Practice at Local Agencies
• Four out of 8 respondents indicated that their agencies integrate the following data sets:
Roadway inventory data and traffic monitoring data
Roadway inventory data and travel modeling data
Environmental impact and compliance data and project design and materials data
What location referencing methods are used in your agency?
30
0
1
2
3
4
5
6
7
8
Geographiccoordinates
Other Route milepoint Link−node
No.
of a
genc
ies
Practice at Local Agencies
How does your agency share data with outside users (public and private entities)?
31
Practice at Local Agencies
0
1
2
3
4
5
6
7
8
9
Online (openaccess)
Upon request Not sharedoutside agency
Other Online (pre-authorized
access)
No.
of a
genc
ies
What strategies would improve (or have improved) data sharing and access within your
agency?
32
4
4
4
[VALUE]*
2
4
3
4
2
1
1
1
1
1
1
Reduced use of hardware andsoftware that require…
Improved database managementsystems
Increased use of web-based datastorage and access
Improved metadata
No. of respondents
MajorEffect
MinorFactor
No effect
Notapplicable
Practice at Local Agencies
Practices in Data Quality
33
To what extent are data quality elements evaluated in your agency?
34
Evaluation Of Data Quality (By % of DOTs)
Quality element Accuracy Completeness Timeliness Relevancy Consistency Accessibility Access security
Evaluated in all or most areas 41 38 38 35 20 24 47
Evaluated in some areas 50 47 62 50 38 56 38
Evaluated in a few areas 9 15 0 15 41 21 15
Practice at DOTs
How does your agency share data with outside users (public and private entities)??
35
Practice at Local Agencies
To what extent are data quality elements evaluated in your agency? Accuracy Completeness Timeliness Relevancy Consistency Accessibility
Access security
Evaluated in all or most areas 6 4 3 4 4 4 3
Evaluated in some areas 3 3 6 4 2 3 4
Evaluated in a few areas 1 2 1 1 4 2 2
Not evaluated 1 1 1 1 1 2 2
Evaluation Of Data Quality (By number of local agencies)
Findings
36
Findings Related to Data Governance • A bottom-up approach for data management appears to be taking place.
• A more top-down data governance approach could: help recognize and leverage the value of data generated and/or stored in various
agency silos, and
spur increased data integration and sharing.
• The majority of responding DOTs and local agencies identified the following as major factors in limiting progress towards implementing data governance:
a) Lack of staffing
b) Other mission-related issues are more pressing
c) Lack of resources
• It is likely that data governance is more mature in DOTs compared to local agencies.
37
Findings Related to Data Warehousing and Cloud Computing
• Data sets that have data stewards tend to reside in data warehouses or marts. Conversely, data sets that do not have designated stewards tend to reside in disparate files and databases.
• Transportation agencies have a wealth of archived data. For DOTs, a clear majority of respondents (70% or more) routinely archive these data: pavement inventory & condition data, traffic monitoring data, HPMS data, project
construction data, crash data, and bridge inventory & condition data.
• The use of cloud computing services is expected to grow in the future, but most surveyed agencies are uncertain about the magnitude and nature of this growth in their agencies.
38
Findings Related to Data Integration and Sharing
• Transportation agencies use multiple location referencing methods (LRMs); indicating that the use of incompatible LRMs remains an impediment to increased data integration in these agencies.
• Geographic coordinates and route mile-point are the most commonly used LRMs.
• An area prime for reducing the duplication of data within DOTs is the creation of digital as-builts from 3D models used in design and construction.
• Majority of surveyed agencies indicated that the following strategies have major effect on improving data sharing and access:
a) Increased use of web-based data storage and access
b) Improved database management systems.
39
Findings Related to Data Quality
• Most respondents indicated that all seven data quality elements are evaluated in at least some data areas in their agencies.
• For DOTs, timeliness, accuracy, and access security are most commonly evaluated.
• Slightly more than half of the DOT respondents indicated that their agencies have mechanisms in place for incorporating feedback from data users into the data collection process. These feedback mechanisms include: Surveys, steering committees, web forms, and ad hoc communications (e.g.
meetings, emails).
40
Thank you for your attention
41
Florida DOT Implementation of Data Governance
Jared Causseaux GIS Program Manager
Florida Department of Transportation
1 Overview and Mission 2 Why ROADS? 3 History 4 Approach 5 What’s Next
The goal of the ROADS initiative is to improve data reliability, simplify data sharing across FDOT, and have readily available and accurate data to make
informed decisions.
Reliable, Organized, Accurate Data Sharing
Mission
• Information is organized around applications instead of around perspectives end users can relate to (e.g., business subject areas).
It’s hard to know what data is available
• Security controls are scattered across many different tools and processes (e.g., RACF, AARF, applications, SharePoint, etc.) throughout 170+ centralized and local systems.
Data is hard to access
• Many districts are moving toward the adoption of the GIS system as the entry point for information searches, but the approach has not been standardized across the districts.
Lack of standardized approach
• A majority of the district data efforts appear to focus on singular business issues without the added benefit of looking at the data from an overall business view to improve performance or reduce risk.
No enterprise-level view of data
• Teams consistently stated they would like a "one stop shop" to access all information they need in one place, with a "Google Type" Search. Over 40 "Search Criteria" elements have been identified.
Teams want a “one stop shop”
Why Roads
Better: Ensure information is secure, accurate, reliable, and at the appropriate level to empower you to do your job better.
Easier: Provide the ability to access relevant business data more quickly and efficiently by knowing where to find it.
Faster: Reduce the amount of time to locate the data you need and more time to analyze the data.
Sharable: Effectively share information across our organization to enable better and faster decisions.
Integrated: Enable a greater capability to link data together from different Districts, Functional Areas, and Systems.
Streamlined: Remove the barriers currently in place that prevent the efficient sharing of information.
Why Roads
1 In the fall of 2014, FDOT began to develop an Enterprise-wide Information Technology Strategy.
2 Office of Information Technology sponsored a critical assessment of the Department’s information technology capabilities, personnel, and infrastructure.
3 A recommendation was made to develop a comprehensive Enterprise Information Management structure, once the current information management practices at the Department had been assessed.
4 To accomplish this task, Phase I of the Reliable, Organized, and Accurate Data Sharing (ROADS) Initiative began in March of 2015.
5 The ROADS Initiative expects to drive many benefits by streamlining information across the organization to enable better, faster decisions by removing the current barriers that prevent the efficient sharing of information.
History
Approach
People: Managing a formal Data Governance Structure to make key decisions related to Data / Information. Process: Training FDOT on the Data Governance Component Model and Implementing Standard Processes & Routines to provide a formal approach to Data Governance. Technology: Providing common standardized BI / DW Tools, Technologies and Frameworks that will be used across FDOT to make data/information more accessible.
Data
QualityData
Integration
DataStrategy andArchitecture
MasterData
Management
MetadataManagement
Analytics
Securityand
Privacy
DashboardsScorecardsReporting
• Chaired by CIM Officer • Champions Data Quality Improvement • Represents Organizational Stakeholders • Prioritizes Data Issues • Sets Data Governance Rules and Procedures
• Chaired by Data Governance Administrator • Leads the Data Governance Working Group • Acts as Liaison between ROADS Executive Team &
the Data Stewards and Data Custodians • Ensures Data Governance Compliance
Business Function Expert • Collaborates Across Dept. on Data
Governance Activities • Defines and Maintains Business Metadata • Coordinates Adequate Documentation • Develops Data Quality Process and
Standards • Drives Remediation of Data Quality Defects • Manages Data Confidentiality & Security
Classification
Technical Function Expert • Supports and Implements
Data Governance Activities • Assists With Documentation • Maintains Knowledge of Data
Structure • Identifies and Resolves Data
Quality Defects • Implements Data
Confidentiality & Security Requirements
Approach
Other key roles for ROADS • Executive Sponsor (Chief of Transportation Technology) • Project Sponsor (CIM Officer) • Business Functional Coordinator (CIM Officer) • Technical Functional Coordinator (IT Bureau Chief) • ROADS Business Liaison • BI/DW Project Manager
Bi/DW Structure
Business Capability Iterations Safety #1
• Enhance existing Metadata • Enhance current Data Quality process • Improve Data Integration within Safety Office • Improve Data Integration with other Departmental Offices • Develop Safety Dashboards • Create Enterprise Reports • Create Self Service Reports
Bi/DW Next Steps
Jared Causseaux Civil Integrated Management GIS Program Manager 605 Suwannee Street, MS 5-L Tallahassee, FL 32399-0450 [email protected] fdot.gov/gis (850) 414-4336
Questions
Today’s Participants
• Peggi Knight, Iowa Department of Transportation, [email protected]
• Nasir Gharaibeh, Texas A&M University, [email protected]
• Johanna Zmud, Texas A&M Transportation Institute, [email protected]
• Clay Whitaker, Florida Department of Transportation, [email protected]
• Jared Casseaux, Florida Department of Transportation, [email protected]
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