Recent research and analyses have identified several issues about the quality of traffic data available from intelligent transportation systems for transportation operations, planning, or other functions. FHWA contracted with Battelle, the Texas Transportation Institute, and Cambridge Systematics to develop an action plan to help stakeholders address traffic data quality issues. The project team developed a series of three white papers that addressed traffic data quality issues, and regional stakeholder workshops were held in Columbus, Ohio, and Salt Lake City, Utah, to critique the white papers and gather input for the traffic data quality action plan. Recommendations are provided for defining and measuring traffic data quality. Data quality is defined as the "fitness of data for all purposes that require it. Measuring data quality requires an understanding of all intended purposes for that data." Six key data quality measures are recommended: accuracy, completeness, validity, timeliness, coverage, and accessibility. Although examples and definitions of these data quality measures are given, future work will more clearly define the calculation and use of these data quality measures in different application areas of transportation.