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Understanding and Using New Data Sources to Address Urban and Metropolitan Freight Challenges

National Cooperative Freight Research Program (NCFRP) Project 49

  • Urban and Metropolitan Challenges
    • Congestion
    • Last-Mile Access
    • Final 50-feet Access
    • Land Use
    • Truck Parking
    • Case Studies
  • Emerging Data Sources
    • GNSS/GPS
    • Radar
    • Wireless Address Matching
    • Administrative Records
    • Cellular/GSM
    • Induction Loops
    • LIDAR
    • Computer Vision
  • Analytical Approaches
    • Speed
    • Location
    • Re-identification
    • Classification
  • Stewardship Principles
    • Transparency and Openness
    • Purpose Specification
    • Data Minimization
    • Data Quality and Accuracy
    • Accountability
    • Security
    • Data Management
  • Resources
    • Source Use Concept Map
    • Case Studies
    • Previous NCFRP Projects
    • Glossary
    • Sources Cited
Home » Data Stewardship and Principles » Data Quality and Accuracy

Data Quality and Accuracy

Agencies should work to ensure the data they collect and use are accurate and of high quality. Explicit quality checks should be performed. In addition, agencies should allow individuals the opportunity to correct any information about themselves that may be incorrect if data are used in an ongoing manner, such as for tolling or commercial vehicle screening. This principle is closely linked with the principles requiring accountability and openness.

With some of the emerging data, data accuracy can be a concern. Certain lighting or “urban canyon” conditions can reduce the accuracy of the data reads. Previous studies (such as NCHRP Report 666 and NCHRP Report 814) suggest that the use of structured methods and instruments for gathering feedback from data users and data managers across agencies can help improve the quality of data maintained by transportation agencies. Depending on the size of the agency, methods that can be used include surveys, focus group meetings, data program workshops, and research studies (Cambridge Systematics, Inc. et al. 2010). NCHRP Report 814 (Spy Pond Partners, LLC and Iteris, Inc. 2015a) provides a detailed self-assessment guide and tools for continuing data improvement.

Principle Checklist:

  1. Does your agency collect information on individuals or commercial firms: sensitive, PII, or otherwise?
  2. Does your agency routinely collect and use data pertaining to the same individuals or commercial firms?
  3. If the data your agency has collected is incorrect or inaccurate, is there potential to harm individuals or commercial firms?
  4. Does your agency have procedures for handling access requests from individuals or commercial firms? Do these include procedures for responding to requests in a reasonable period of time?

Answering these questions can help your agency understand if the principle of data accuracy applies to your data collection and use activity, and identify possible actions or tools to aid implementation. If answers to these any of these questions are “yes”, then the principle of data accuracy could apply to your agency.

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  • Transparency and Openness
  • Purpose Specification
  • Data Minimization
  • Data Quality and Accuracy
  • Accountability
  • Security
  • Data Management

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