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FHWA MIRE Management Information System (MIS)

FHWA MIRE Management Information System (MIS) . Nancy Lefler, VHB August 30, 2012. Overview . Background Purpose Overview of Activities Data Collection Structure of MIS Performance Measures Results/Products Questions. Project Team . Prime Vanasse Hangen Brustlin, Inc. (VHB)

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FHWA MIRE Management Information System (MIS)

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  1. FHWA MIRE Management Information System (MIS) Nancy Lefler, VHB August 30, 2012

  2. Overview • Background • Purpose • Overview of Activities • Data Collection • Structure of MIS • Performance Measures • Results/Products • Questions

  3. Project Team • Prime • Vanasse Hangen Brustlin, Inc. (VHB) • Supported by • Applied Research Associates (ARA), Data-Nexus, Inc., UNC-Highway Safety Research Center, Dr. Forrest Council • FHWA • Robert Pollack and Dr. Carol Tan

  4. Background

  5. Background – MIRE • MIRE – Model Inventory of Roadway Elements • Listing of roadway and traffic elements critical to safety management • Data dictionary – definition, attributes, etc. www.mireinfo.org

  6. Next Step – MIRE MIS • Evolution of MIRE from listing to Management Information System (MIRE MIS)

  7. Purpose • Determine feasibility of MIRE data management system: • Mechanisms for data collection • Process for data handling and storage • Linkage among files • Performance metrics • Provide lessons learned/guidance for safety data improvement

  8. Overview of Project Activities • Collection of data elements • Development and testing of MIS structure • Development/expansion of performance measures

  9. Collection

  10. Collection of MIRE Data Elements • Research: current practices and gap analysis • Lead Agency Program: pilot MIRE data collection • “Collective Data” concept • MIRE Data Collection Guidebook

  11. Lead Agency Program • Pilot MIRE data collection • New Hampshire DOT and Washington State DOT • Developed an intersection inventory

  12. Data Collection Process • Determine what elements to collect • Develop detailed Work Plan • Develop data collection tool • Model to extract and pre-populate • User interface • Populate inventory • Conduct QA/QC

  13. Data Collection

  14. Data Collection: Results/Products • Intersection inventory for NHDOT and WSDOT • Final Report: Document development of tool and lessons learned

  15. Collective Data Concept • Assembling data or collecting information using a large group of people (think Wikipedia) • Agencies putting concept into practice • Explore how this concept can apply to collecting roadway information • Result: Collective Data White Paper

  16. MIRE Data Collection Guidebook • Guidance on collecting the MIRE elements. • Focus on elements that do not have established collection methodologies. • Includes for each element: • Description • Accuracy parameters • Considerations • Existing resources • Methodologies • Concerns

  17. Structure

  18. MIS Structure • Develop overall structure • Develop of prototype • Test prototype • Refine structure

  19. Structure of the MIRE MIS • Decision support system to improve highway safety • Developed using relational database model • Integrate data from disparate sources for higher level analysis

  20. Lessons Learned • Data quality matters! • Using MIRE as guidance - States build system around their own data structure • GIS is an essential part of the MIRE MIS - consistent referencing system for data points

  21. Performance Measures

  22. Performance Measures • Tools for measuring data quality and establishing goals for data improvement • Six primary metrics: • Timeliness • Accuracy • Completeness • Uniformity • Integration • Accessibility

  23. Roadway Inventory Metrics • NHTSA developed initial performance measures for the six core traffic safety data systems • Built/expanded on those metrics • Detailed review of metrics proposed for roadway data • Metric related business practices – how to use metrics to improve data • Result: Performance Measures Report

  24. Results/Products

  25. Summary of Project Activities/Products • Collection of MIRE data elements: • Collection Mechanisms and Gap Analysis Report • MIRE Pilot Data Collection Report • Intersection inventory datasets for NHDOT & WSDOT • Collective Data White Paper • MIRE Data Collection Guidebook • Development and testing of MIS structure: • Prototype for pilot agency • Report on structure and lessons learned • Performance Measures: • Performance Measures Report

  26. Summary • MIRE MIS – how to collect, integrate, manage, and measure data for improved safety decisions • State and local agencies can realize benefits • Products available on website: www.mireinfo.org

  27. Thank you! VHB Contact • Nancy Lefler, nlefler@vhb.com FHWA Contacts • Robert Pollack, Robert.Pollack@dot.gov • Dr. Carol Tan, Carol.Tan@dot.gov

  28. Questions

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