Every year, state, regional, and local agencies across the nation measure transportation systems performance and make numerous planning and operations decisions. These complex decision-making processes need large amounts of data. To be useful, data from a variety of sources—that may have been collected for different purposes—has to be transformed into information. Data integration offers a significant opportunity to make improve decision-making through the use of a data management process that efficiently and effectively produces new information derived from isolated heterogeneous data sets.
The lack of proper data integration tools can result in widely different analytical outcomes and negatively affect the quality of decision-making. For example, traffic flow speed is often analyzed to identify bottlenecks and problematic areas with low levels of service. However, if actual speeds are looked at without considering posted speeds, queue lengths, and volumes, actual speed data can potentially lead to inappropriate conclusions about the need for improvements.
The fields of transportation forecasting, planning and operations have been slow to adopt and benefit from the advantages of data integration solutions in the face of a rapidly changing urban data environment, an enormous increase in new transportation data sources and data collection technologies, and the establishment of new commercial data sources. Data integration issues have therefore become more important in order to ensure that a complete and coherent picture of past and emerging performance. Data integration solutions should facilitate easy access to disparate transportation data sets for data mining, comparisons, visualization and other functions that rely on data.
The objectives of this research is to (1) examine the current state of transportation data integration, with an emphasis on performance measurement data and data that are relevant for planning and maintenance decisions; and (2) provide guidance for data management program development at state, regional and local levels. The research results should summarize current practices in the transportation data integration, including at a minimum forecasting, planning, operations, asset management, transportation economics, transportation modeling and other related fields.
List of Anticipated Work Tasks:
The following activities were performed:
1. Collected and analyzed information on the data integration practices at state DOTs and MPOs.
2. Identified transportation data integration strengths, weaknesses, opportunities and threats on national, state and local levels in the context of performance measurement, and supporting planning and operations decision-making.,
3. Identified additional steps that state DOTs and MPO may take to develop practical
4. Identified additional research needed to support successful data integration by state DOTs and MPOs.
This study has been released in two components: 1) The Final Report and 2) a PPT Presentation to decision makers.