TY - JOUR
T1 - Dynamic data maintenance for quality data, quality research
AU - Ozmen-Ertekin, Dilruba
AU - Ozbay, Kaan
N1 - Funding Information:
The research project summarized in this paper was funded by a joint grant from NYMTC and the Region 2 University Transportation Research Center .
Funding Information:
Dilruba Ozmen-Ertekin is an Assistant Professor of Engineering at Hofstra University. She authored and co-authored more than 50 journal/conference papers and research reports. Most recently, she was the Co-Principal Investigator of a project funded by NYMTC. She is also an affiliated faculty at the Region 2 University Transportation Reseach Center located at the City College of NY. She is an Assocaite member of the American Society of Civil Enigeers and member of Sigma Xi Scientific Research society. She is a committee member of the HCLAS Standards and Review Committee, and senator-at-large in Hofstra University's Special Committee on Recruitment, Elections and Nominations. She is also a frequent reviewer for various journals in her area of expertise. She also provides graduate study, internship and job opportunities to engineering students at Hofstra through her connections with various schools including Rutgers, City College, consulting firms and government agencies including NYMTC, NYSDOT, UTRC2. She is a licensed Professional Engineer.
Funding Information:
Kaan M.A. Ozbay is a full professor of Civil and Environmental Engineering at Rutgers University. He is the recipient of the prestigious National Science Foundation (NSF) CAREER award. He is the co-author of a book titled “Feedback Based Ramp Metering for Intelligent Transportation Systems” published by Kluwer Academics in 2004. In addition to this book, he is also the co-author of two books titled “Feedback Control Theory for Dynamic Traffic Assignment”, Springer-Verlag and “Incident Management for Intelligent Transportation Systems” published by Artech House publishers in 1999. He published more than 250 refereed papers in scholarly journals and conference proceedings. Professor Ozbay serves as the “Associate Editor” of Networks and Spatial Economic journal and is a member of the editorial board of the ITS journal. Since 1994, he has been the Principal Investigator and Co-Principal Investigator of 64 projects funded at a level of more than $8,500,000 by National Science Foundation, NJDOT, NYMTC, NY State DOT, New Jersey Highway Authority, USDOT, FHWA, VDOT, CUNY University Transportation Research Center (UTRC), Rutgers Center for Advanced Infrastructure and Transportation (CAIT), USDOT ITS Research Center of Excellence. He is the founding director of the Rutgers Intelligent Transportation Systems (RITS) laboratory that leads ITS research and education activities at Rutgers University.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2012/6
Y1 - 2012/6
N2 - 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.
AB - 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.
KW - Data life cycle
KW - Data quality
KW - Dynamic data maintenance
KW - Total quality management
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U2 - 10.1016/j.ijinfomgt.2011.11.003
DO - 10.1016/j.ijinfomgt.2011.11.003
M3 - Article
AN - SCOPUS:84860290444
SN - 0268-4012
VL - 32
SP - 282
EP - 293
JO - International Journal of Information Management
JF - International Journal of Information Management
IS - 3
ER -