Dynamic data maintenance for quality data, quality research

► Results from a recently completed research project, sponsored by NYMTC, are reported. ► NYMTC's website, data products, current data maintenance process examined to identify specific issues and propose solutions. ► Examination within the framework of data life cycle, TQM protocol, and various dimensions of data quality. ► Best practices, NYMTC stakeholder survey, and latest technological tools considered. ► Recommendations specific to NYMTC's needs, but can be adopted and implemented by other agencies to address similar issues. Just like any other scientific research field, the value of data quality is undisputed in the field of transportation. From policy planning to performance evaluation, from model development to impact studies, good quality data is essential to generate ideas and clear-cut solutions to be implemented by transportation professionals and decision makers. In order to improve scientific data quality and function within a continuous quality assessment and management framework, research and development organizations and agencies constantly look for the latest methodologies and technological tools of data management. The New York Metropolitan Transportation Council (NYMTC), for example, has awarded a research project titled “Improvements on NYMTC Data Products” to the authors of this paper in an effort to modernize the existing data products (i.e., reports and brochures, both printed and online) and improve the communication between the agency and the public. The main goal of the research project was to perform a through review and examination of NYMTC data products to identify specific issues about the existing data products, website and the current data maintenance process at NYMTC, and then suggest appropriate solutions, both data and website, and process oriented. This paper reports the results from this research project by giving special emphasis to the issues and solutions related to the data maintenance process.