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Colleen Coggins NHTSA CIO, Office of the Chief Information Officer Michael D Frenchik

How the Shared Services Model is Strengthening NHTSA’s Mission Responsiveness While Achieving Cost-Savings Aug 2017. Colleen Coggins NHTSA CIO, Office of the Chief Information Officer Michael D Frenchik Chief, Safety Systems Management Division. Agenda. Intro

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Colleen Coggins NHTSA CIO, Office of the Chief Information Officer Michael D Frenchik

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  1. How the Shared Services Model is Strengthening NHTSA’s Mission Responsiveness While Achieving Cost-SavingsAug 2017 Colleen Coggins NHTSA CIO, Office of the Chief Information Officer Michael D Frenchik Chief, Safety Systems Management Division

  2. Agenda • Intro • Overview – What are Shared Services? • Data Usage Examples – Shared Services • EDT • vPIC • Application Shared Services • FARS MDE • NHTSA’s Enterprise Data Warehouse - Overview • Value Add to NHTSA and the States • Where do we go from here? • The future and beyond ………

  3. Shared Services and Introduction – What is it? • Shared services are the provision of a service by one part of an organization or group where that resource had previously been found in more than one part of the organization or group. • Thus the funding and resourcing of the service is shared and the providing department effectively becomes an internal service provider. • More than just infrastructure: Data and Applications are shared services too!!

  4. How does this Shared Services benefit my State? Open use of Data Sharing and Services with the States as a group is a NHTSA key mission objective to meet the safety goals for the country (i.e., Data.gov, etc.). Without open sharing of data and applications, silos are created which affects our ability to meet the safety goal of getting to “zero deaths”.

  5. Open Data Sharing Initiatives NHTSA’s Electronic Data Transfer (EDT) NHTSA’s Product Information Catalog and Vehicle Listing (vPIC) NHTSA Fatality Analysis Reporting System (FARS) NHTSA’s Enterprise Data Warehouse (EDW) / Corporate Information Factory (CIF)

  6. Electronic Data Transfer (EDT) • What is it? • Transfer of crash data in an electronicdataformatbetween a State and NHTSA • Includes police crash reports and supporting analysis data (where available)

  7. EDT Value / Benefits • Timeliness • Pre-coding • Accuracy • Reduced manual entry • Integration • Increased use in other programs • Uniformity • Consistent form and coding

  8. More Data Available for Analysis

  9. EDT Current Operations • Seven State crash datasets are currently being transmitted • CA Highway Patrol cases are currently being pre-coded for fatals only due to limitations • Working with additional States (WA, TX, ID, WI, and more)

  10. How is EDT Helping States? FARS Pre-coding: Brings data to coding interface faster to improve timeliness FARS Completeness Maps Virginia 2015 - July Virginia 2016 - April * Based on EDT pilot study of Virginia (late 2015) to Virginia Starting 1/1/2016

  11. Virginia – Experience with EDT Joint effort between VA and NHTSA • Process Timeline: October 2014 - May 2015 • 2 meetings - establish technical solution and process • 320 hours - devoted to EDT project over a 7 month period • Utilized existing resources (TREDS/IT and FARS staff)

  12. Virginia – Experience with EDT • Process • Data mapping • Confidence/matching levels assigned to each attribute • Web service for automated transfer (XML) • Tested the new EDT process • Go Live…!!!!!!!

  13. Virginia FARS/EDT Value/Benefits • Integration • External Data Transferred • Alcohol/Drug Test Data • EMS Time (Notification/Arrival Scene/At Hospital) • Vital Statistics (Death Certificate Info) • Crash Location Data

  14. Virginia FARS/EDT Value/Benefits • Timeliness • 118 (72%) - FARS fields pre-coded • 400 hours/year - saved on data entry • Accuracy • Eliminate errors due to manual entry • Confidence levels used to assist on QC

  15. Shared Data and Application Programming Interfaces (APIs) - vPIC http://vpic.nhtsa.dot.gov/ • Includes three Public application areas: • vPIC Decoder • Manufacturer Information Database (MID) • Application Programming Interfaces (APIs) – 16 Public Interfaces

  16. vPIC: A Few Examples of Uses • VIN Decoding Data • Ability to Decode Crash VINs and get additional information • System and Application Developers • Single and Batch Decoding Capability • Currently multiple states are looking to integrate vPIC in their systems • Manufacturer Regulatory Compliance: Registration and/or Importation • Example: Washington CBP port uses vPIC for validation of vehicle products incoming.

  17. CrashManager Program:A Shared Services & Knowledge Program • Shared Open Source Software (OSS): • Creation of reusable technology with applied data standards, which by definition will meet all expected data standards for creation of integrated datasets at the national level specific to crash data; and • By definition will define the data space requirements of the DOT sponsored surface transportation domain subject area of Vehicle Safety. • State Roadmap to Compliance (SRC): • Development of formal guidance for state-based solution development at a technical level to facilitate true application of data standards at the state and local levels; and • Commercial Compatible Solution Program (CCSP): • Development of a formal review and compatibility testing program to influence application of good software development primarily centered on the use of DOT accepted data standardization principles to meet all levels of data integration and analysis.

  18. NHTSA Shared Data Services Value-Add • Federation of Disparate Data Sources • Data Governance • Standardization • Data Enrichment / Expansion • Improved data quality • Standardize naming conventions and data types • Integration of external data sources (to program) • Added Context • Unified glossary • SME participation in definitions & business rules • Leverage Data Integration Tools • Repeatable process • Build Once/Reuse Often

  19. What is NHTSA’s Corporate Information Factory (CIF) Program? Data-Centric Hub powered by Enterprise Service Bus (ESB) and EDW Analytical and Workflow Applications: Cognos, Watson, ACM, SPSS, DataCap

  20. CIF Enterprise Service Bus / Data Warehouse NHTSA Program Area Data Domains • Allows for cross-program data use / consolidation; and • Data is pulled into the centralized warehouse as needed.

  21. Why Centralized EDW Hosted Within Virtualized Shared-Services Environment • Standardized data services infrastructure enables the seven ‘ilities • 1.Usability • 2.Maintainability • 3.Scalability • 4.Reliability • 5.Extensibility • 6.Security • 7.Portability • Federate data from disparate systems into concise subject areas • Retain historical “cleansed” data

  22. NHTSA Shared Data Services: Staged Approach

  23. Benefit to States/Traffic Records Community

  24. Electronic Data Transfer (EDT) Maryland is piloting secure snapshot feeds back to a state-managed database from NHTSA in 2017*

  25. Where do we go?

  26. Questions? Colleen Coggins NHTSA CIO, Office of the Chief Information Office Collleen.Coggins@dot.gov Phone: (202)366-1199 Michael D. Frenchik Chief, Safety Systems Management Division Michael.Frenchik@dot.gov Phone: (202)366-0641

  27. BACK UP SLIDES

  28. CrashManager Program:A Shared Services & Knowledge Program • Shared Open Source Software (OSS): • Creation of reusable technology with applied data standards, which by definition will meet all expected data standards for creation of integrated datasets at the national level specific to crash data; and • By definition will define the data space requirements of the DOT sponsored surface transportation domain subject area of Vehicle Safety. • State Roadmap to Compliance (SRC): • Development of formal guidance for state-based solution development at a technical level to facilitate true application of data standards at the state and local levels; and • Commercial Compatible Solution Program (CCSP): • Development of a formal review and compatibility testing program to influence application of good software development primarily centered on the use of DOT accepted data standardization principles to meet all levels of data integration and analysis.

  29. OCIO Enterprise Data Management Approach • Primary Objective: Coalesce NHTSA’s disparate information landscape into an authoritative and standardized information framework • Improved capability for data sharing; • Enhanced security; • Eliminated silos improves: • Monitoring • Scalability • Interoperability • Leads to reduced labor for establishing and maintaining servers • Lays the groundwork for the development of the: NHTSA Enterprise Data Warehouse

  30. What is a Data Mart? Whereas data warehouses have an enterprise-wide depth a data mart is a subcomponent with a specific purpose and function. • Generally: • A data mart is a subset of a data warehouse; • May be within the same architecture or linked through network; • Typically subject-based and can be: • Specific to a subject area, business line or team; • Small slices of the larger organizational collection; • May pertain to a single department or program (e.g., crash data) • Integrated into the Enterprise Data Warehouse through common connections (e.g., case IDs, vehicle IDs, etc.)

  31. Enterprise Service Bus (ESB) • An enterprise service bus (ESB) is a mechanism used for: • Designing and implementing communication; • Facilitates interaction in a standardized manner; • Establishes a mutual link between software and/or applications • Leverages a service-oriented architecture (SOA) to make data components available for re-use across a data warehouse. An ESB can be leveraged to establish aEnterprise Data Warehouse using multiple decentralized Data Marts without physical consolidation of data.

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