版权所有:内蒙古大学图书馆 技术提供:维普资讯• 智图
内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:Earth System Science Center/NASA MSFC IMPACT The University of Alabama in Huntsville HuntsvilleAL United States Columbia University Palisades NY United States Spain Ramapriyan Science Systems and Applications Inc. Lanham MD United States NASA Goddard Space Flight Center GreenbeltMD United States Curtin University Australia Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States Environmental Sciences Division Oak Ridge National Laboratory Oak RidgeTN United States /Magellium Spain National Computational Infrastructure Australian National University ACT Australia Silver SpringMD United States Darmstadt Germany Geoscience Australia ACT Australia Hannover Germany Aston University United Kingdom Cooperative Institute for Research in Environmental Sciences NSIDC BoulderCO United States Australian Research Data Commons Melbourne Australia University of Maryland at Baltimore County BaltimoreMD United States AshevilleNC United States StormCenter Communications | GeoCollaborate HalethorpeMD United States Metadata Game Changers BoulderCO United States Rhea GROUP La Piramide Via di Grotte Portella 6/8 Frascati00044 Italy European Space Agency Frascati Italy American Geophysical Union WashingtonDC United States Mercator Ocean International France North Carolina Institute for Climate Studies North Carolina State University AshevilleNC United States Ronin Institute United States Spain Lamont-Doherty Earth Observatory of Columbia University Palisades NY United States NASA Marshall Space Flight Center HuntsvilleAL United States
出 版 物:《Data Science Journal》 (Data Sci. J.)
年 卷 期:2021年第20卷第1期
核心收录:
基 金:The virtual pre-ESIP workshop held on July 13 2020 was sponsored by ESIP and co-organized by the ESIP IQC and the BSC EQC team in collaboration with the ARDC AU/NZ DQIG. An additional community engagement event was carried out by the AU/NZ DQIG prior to the pre-ESIP workshop. ESIP is primarily supported by the National Aeronautics and Space Administration (NASA) the National Oceanic and Atmospheric Administration (NOAA) and the United States Geological Survey (USGS). The technological and infrastructural support during the preparation and conduct of the workshop was invaluable. In particular we thank Megan Carter ESIP Community Director for supporting us throughout the workshop and providing helpful advice during the planning stage of the virtual workshop and ESIP Community Fellow Alexis Garretson for supporting the ESIP SM20 report-out session. We thank all participants for attending the pre-ESIP workshop and the ESIP SM20 session and contributing to productive discussions during the live sessions and the two weeks of the ESIP SM20 period. Portions of this work have been extracted from Peng et al. (2020a) which reported on the workshop and the ESIP SM20 report-out session. The Australian participants acknowledge the support of the ARDC. The constructive suggestions from two anonymous reviewers of Data Science Journal have helped improve the quality of the paper
摘 要:Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision-and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science. © 2021 The Author(s).