Peng Ge, Privette Jeffrey L, Tilmes Curt, Bristol Sky, Maycock Tom, Bates John J, Hausman Scott, Brown Otis, Kearns Edward J
North Carolina State University, Cooperative Institute for Climate and Satellites - North Carolina (CICS-NC), US.
NOAA's National Centers for Environmental Information (NCEI), 151 Patton Avenue, Asheville, NC 28801, US.
Data Sci J. 2018;17:15. doi: 10.5334/dsj-2018-015. Epub 2018 Jun 28.
Scientific data stewardship is an important part of long-term preservation and the use/reuse of digital research data. It is critical for ensuring trustworthiness of data, products, and services, which is important for decision-making. Recent U.S. federal government directives and scientific organization guidelines have levied specific requirements, increasing the need for a more formal approach to ensuring that stewardship activities support compliance verification and reporting. However, many science data centers lack an integrated, systematic, and holistic framework to support such efforts. The current business- and process-oriented stewardship frameworks are too costly and lengthy for most data centers to implement. They often do not explicitly address the federal stewardship requirements and/or the uniqueness of geospatial data. This work proposes a data-centric conceptual enterprise framework for managing stewardship activities, based on the philosophy behind the Plan-Do-Check-Act (PDCA) cycle, a proven industrial concept. This framework, which includes the application of maturity assessment models, allows for quantitative evaluation of how organizations manage their stewardship activities and supports informed decision-making for continual improvement towards full compliance with federal, agency, and user requirements.
科学数据管理是长期保存以及数字研究数据使用/再利用的重要组成部分。它对于确保数据、产品和服务的可信度至关重要，而这对决策来说很重要。美国联邦政府近期的指令和科学组织的指南提出了具体要求，这增加了采用更正式方法的必要性，以确保管理活动支持合规性验证和报告。然而，许多科学数据中心缺乏一个综合、系统且全面的框架来支持此类工作。当前以业务和流程为导向的管理框架对大多数数据中心来说实施成本太高且耗时太长。它们往往没有明确解决联邦管理要求和/或地理空间数据的独特性。这项工作基于已被验证的工业概念——计划-执行-检查-行动（PDCA）循环背后的理念，提出了一个以数据为中心的概念性企业框架来管理管理活动。这个框架包括成熟度评估模型的应用，能够对组织如何管理其管理活动进行定量评估，并支持做出明智决策，以便不断改进以完全符合联邦、机构和用户的要求。
