Improving Safety Programs through Spatial Data Governance and Data Business Planning. GIS-T April 20, 2015
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1 Improving Safety Programs through Spatial Data Governance and Data Business Planning GIS-T April 20, 2015
2 Improving Safety Programs through Data Governance and Data Business Planning Peer Exchange 10 states Safety, IT, GIS, Program, Exec. Participants March 2015 Advance Questionnaire
3 Alaska Idaho Iowa Louisiana Maryland Michigan Montana Ohio Rhode Island Washington Participating States
4 Questionnaire Focus Areas Data Governance Data Management Data Integration Program Assessment Questions to Peers
5 Data Management The development, execution, and oversight of architectures, policies, practices, and procedures to manage the information lifecycle needs of an enterprise.as it pertains to data collection, storage, security, data inventory, analysis, quality control, reporting, and visualization
6 Data Governance The execution and enforcement of authority over the management of data assets and the performance of data functions.
7 DATA GOVERNANCE Section A
8 Data Governance: Data Sources Focus on Crash, Roadway, Traffic Closest source for collection but emphasis on usage Expanding data assets: signs, guardrail, stormwater, sidewalks, ramps, bicycle, ADA compatibility, signals, design drawings, contracts, fixed object in clear zones, maintenance, green assets.
9 Formal Data Governance Efforts Long Range Transportation Plan (LRTP) Strategic Highway Safety Plan (SHSP) Highway Safety Improvement Prog.(HSIP) Traffic Records Coord. Council (TRCC) Transportation Asset Management Plan Safety Management System Crash Data Asset Management Data
10 Data Governance: Innovative Practices Mapping data workflows Business rules for safety data Some formal data stewardship roles in job descriptions
11 Formal Data Governance Roles Data Governance Council (MI) Data Governance Comm. (IA,OH) Enterprise Information Governance Group (WA) Policy for Crash Data Some under Development
12 Governance Implementation (Mixed) Documentation of Safety Data Business Rules Service Level Agreements for Data Quality Codification of Responsibilities for Data Stewards
13 Institutional Issues Change in organizational roles/power, cultural Maintaining executive support Data Silos how to implement enterprise systems Centralized IT / Decentralized IT No data governance process standard/blueprint Staffing, knowledge workers Generational familiarity with IT and analytics Incorporating enhanced data collection techniques Expanding data collection categories
14 DATA MANAGEMENT Section B
15 Data Management: Data Review and Inventory Several assess critical data items Sources: MIRE, FDE, Safety Analyst, HSM, MAP-21 Coordinate effort safety and asset management Some have metadata and data standards in place
16 Archiving Historical Road Inventory Information Most annual file snapshots Iowa DOT - Timestamps and versions every record for both business data and LRS as edited ability to look at and run analysis a any point in time
17 Safety - Related Network Screening Business Intelligence Tools Safety Analyst Highway Safety Manual Home Grown Not yet Automated
18 General Observations Safety Data Management New datasets evaluated both structured and ad hoc Several states working on safety data models Most states deploy Data Dictionaries / Metadata / Data Business Rules at some level, but inconsistent
19 DATA GOVERNANCE: INTEGRATION Section C
20 Data Integration: Innovative Practices Most have common LRS for integrating data Local system more challenging (ARNOLD effort)
21 Safety Data Integration Most states Roadway, Traffic and Crash data at some level Most states - Integrated LRS/GIS Most states - All public roads with ties to ARNOLD Mixed on Local Roads Integration Mixed on Operations/Congestion data AK close to adding weather
22 Crash Records Integration with TAM, Performance Management, Project Scoping Web/GIS Portal Roadway, Traffic & Crash Crash Frequency/Severity with TAM Project Level
23 Data Visualization Techniques for Safety Program/Projects? GIS (Most) Intersection Crash Magic Photolog Heat Maps
24 Most Successful Integration Efforts Roadway, Traffic & Crash (AK, ID, IA, MI) Crash and Congestion (MD) Crash Frequency/Severity with TAM (ID, OH) Crash Data with Illumination/Lighting (WA) Safety Information Management System to SmartCop (MT)
25 Less Successful Integration Efforts? Crash and Health Records, personal/private information Fully Integrated TAM Project Scoping Currently Led by Individual Business Units instead of Enterprise Focus (WA) Past Successful Integration Efforts should be Upgraded with Modern Methods (MI)
26 PROGRAM ASSESSMENT Section D
27 Safety Program Assessments (Identify Data Gaps, Risks, Overlaps) Crash Data Improvement Program [CDIP] Roadway DIP [RDIP] Roadway Safety Data Program [RSDP] NHTSA Traffic Records Assessment Capability Maturity Assessments (Safety)
28 Procedures to Identify Data Collections Risks, Gaps and Overlaps? Action Plans resulting from Federal Assessments Highway Safety Offices TRCC Internally, As Needed None
29 Processes for Data Users to Assess Data Quality? Traffic Safety Engineers HPMS Review Office of Traffic Safety and State Police Informally with Users None
30 Prioritization of Safety Data Needs Perform a Risk Analysis Data Value Assessment Process Traffic Safety Engineers Office of Traffic Safety Fundamental Data Elements Address as Needed
31 ADDITIONAL QUESTIONS Section E
32 Agency Motivations for a Comprehensive Data Business Planning Process? Directive from Agency Head Data Governance Council/Committee Enterprise Architecture Project Improve TAM/Planning Processes Improve Spatial Delivery of Information Demonstration/Pilot Project Results Awareness of Problems & Opportunities Financial Support
33 What Safety-Related Business Process Areas would Benefit the Most? Spatial Analysis/GIS Integration of Safety and Asset/AM Data Creation of Data Warehouse Easy Access to Data Relationship with Law Enforcement
34 Questions to Peer States How to Establish Data Governance Council How to articulate business needs for data Successful automated data collection techniques How to obtain local agency buy-in for asset/crash data collection How to incorporate as-built and maint. data How to utilize crowdsourced data How to incorporate consistent location referencing for any data collected Establishing data hierarchies for automated roadway data collection. Future platforms. How to advance data analytics and integration
35 Peer Research Needs 1. Metrics for Successful Data Governance 2. Executive Perspective on Managing Transportation Data as an Asset 3. Essential Elements of Data Integration to Drive Business 4. Data Governance in Context of Centralized IT 5. Crash Data Life Cycle Practices 6. Effect of Location Accuracy on Safety Data Analysis
36 TRB E-Circular x
37 James P. Hall Associate Professor - Emeritus Management Information Systems University of Illinois at Springfield One University Plaza Springfield, IL Phone: jhall1@uis.edu
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