International Efforts to Develop Community Guidelines for FAIR Quality Information of Earth and Environmental Science Datasets
Dr Lesley Wyborn1, Dr MIngfang Wu2, Dr Ivana Ivanova2, Ms Irina Bastrakova4, Dr Ge Peng5, Mr David Moroni6, Dr Hampapuram Ramapriyan7, Dr Robert R.. Downs8, Dr Yaxing Wei9
1Australian National University, Canberra, Australia, 2Australian Research Data Commons, Melbourne, Australia, 3Curtin University, Bentley, Australia, 4Geoscience Australia, Symonston, Australia, 5The University of Alabama, Huntsville, The United States of America, 6NASA Jet Propulsion Laboratory, Los Angeles, The United States of America, 7Science Systems and Applications, Greenbelt, The United States of America, 8Columbia University, Palisades, The United States of America, 9Oak Ridge National Laboratory, Oak Ridge, The United States of America
Digital datasets, the Internet and web services have made access to data resources so easy. At the click of the mouse it is possible to locate data from anywhere around the world for either online processing or local downloads. Datasets are increasingly being reused, integrated into larger collections, and even repurposed for use cases beyond what the original creator intended.
But questions are being asked about the ‘quality’ of the dataset being accessed: how does the user know how reliable a dataset is? It is common to hear the cries “we can’t use that dataset because it is of poor quality”, or “don’t trust data from XXXX (where XXXX can represent sector, organisation, group, person) – their data is full of errors and of low quality”.
For effective data reuse, aggregation and repurposing, community agreement and guidelines about what actually defines the quality of a dataset and its metadata are critical: it is essential that this information be Findable, Accessible, Interoperable and Reusable (FAIR) and available with each dataset.
Since September 2020, international interdisciplinary domain experts have been working voluntarily towards defining community guidelines for making data quality information FAIR, based around both the four quality dimensions (science, product, stewardship, services) and the data quality information required for supporting data life cycles. The objective is to develop the ‘International Community Guidelines for Sharing and Reusing Quality Information of Individual Earth Science Datasets’. This presentation will give an overview of the draft guidelines and invite additional community participation in the effort.
Lesley Wyborn is an Honorary Professor at ANU, now working part time with NCI and ARDC. She formerly had 42 years’ in Geoscience Australia in scientific research/data management. She is Chair of the National Data in Science Committee and is on the AGU Data Management Advisory and ESIP Executive Boards.