Dynamic data maintenance for quality data, quality research
Dynamic data maintenance for quality data, quality research
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DOI：
10.1016/j.ijinfomgt.2011.11.003
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发表时间：
2012-06
期刊：
影响因子：
--
通讯作者：
Dilruba Ozmen-Ertekin;Kaan Özbay
中科院分区：
文献类型：
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作者：
Dilruba Ozmen-Ertekin;Kaan Özbay
就像任何其他科学研究领域一样，数据质量的价值在交通领域是无可争议的。从政策规划到绩效评估，从模型开发到影响研究，高质量的数据对于交通专业人员和决策者提出想法和明确的解决方案至关重要。为了在持续的质量评估和管理框架内提高科学数据的质量和功能，研究和开发组织和机构不断寻找数据管理的最新方法和技术工具。例如，纽约大都会交通理事会（NYMTC）已经将一个名为“对NYMTC数据产品的改进”的研究项目授予了本文的作者，以努力使现有的数据产品现代化（即，报告和小册子，包括印刷版和在线版），并改善该机构与公众之间的沟通。该研究项目的主要目标是对NYMTC数据产品进行全面审查和检查，以确定NYMTC现有数据产品、网站和当前数据维护过程中的具体问题，然后提出适当的解决方案，包括数据和网站，以及面向过程的解决方案。本文报告了该研究项目的结果，特别强调了与数据维护过程相关的问题和解决方案。
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.