Representing and Communicating Data Quality Information
Submitted by Ge Peng
Organized by the Information Quality Cluster of U.S. Earth Science Information Partners (ESIP IQC) and Australia/New Zealand Data Quality Interest Group (AU/NZ DQIG), in collaboration with the Barcelona Supercomputing Center Evaluation and Quality Control (BSC EQC) team and the Open Geospatial Consortium Data Quality Domain Working Group (OGC DQ DWG), this meeting seeks to:
- Identify and promote community interests, opportunities or capabilities to improve the representation and communication of data quality information,
- Describe activities and deployed capabilities that are improving the representation and communication of data quality information in diverse scientific environments,
- Engage the RDA community towards a Working Group for FAIR Data Quality Information.
(Session organizers: Ge Peng, Lesley Wyborn, Robert Downs, Hampapuram Ramapriyan, Ivana Ivanova, Carlo Lacagnina, and Mingfang Wu)
Collaborative session notes: https://docs.google.com/document/d/1JsWEP7rbCP-2WEVYPflOFRy3FdNGHfEwxOo38xjMEvY/edit
Welcome Remarks and Sign In - 5 mins
Presentations - 50 mins
Optimizing stewardship of genomic and related health data in the cloud (Vasiliki Rahimzadeh, Stanford Center for Biomedical Ethics, Stanford University, USA)
Data quality in astronomy - Building trust (Francoise Genova, Strasbourg astronomical data centre, France)
(Meta)Data Quality in the Social Sciences (Steven McEachern, Australian Data Archive, Australian National University, Australia)
Earth Science community guidelines to improve the representation and communication of dataset quality information (Robert Downs, Center for International Earth Science Information Network, Columbia University, USA)
- Development of geospatial data quality use cases:
- Ivana Ivánová, OGC Data Quality Domain Working Group, Curtin University, AUS;
- Christin Henzen, GeoKur project team, Geoinformatics/Technische Universität Dresden, Germany.
Community discussion on improving data quality information and path forward - 30 mins
- Panelists: All presenters and Lesley Wyborn, ESIP/RDA Earth, Space, and Environmental Sciences Interest Group, Australian National University, AUS)
Closing remarks - 5 mins
Many uses of data are dependent upon data quality. In addition to the need to ensure that data quality is acceptable to meet the needs of potential users, information about data quality must be represented and communicated to inform the use of the data. Effectively representing and communicating data quality information is important for conducting research within and across many disciplines and for improving data sharing.
Under the auspices of the Earth Science Information Partners (ESIP) and with collaboration among members of the ESIP Information Quality Cluster (IQC), the Barcelona Supercomputing Center (BSC) Evaluation and Quality Control (EQC) team, and the Australia/New Zealand Data Quality Interest Group (AU/NZ DQIG), a community effort has been undertaken by international Earth Science domain experts. The objective of this effort is to develop global community guidelines with practical recommendations to promote sharing and reusing of quality information at the dataset level, leveraging the experiences and expertise of a team of interdisciplinary domain experts and community best practice. Contacts have been established between the above-mentioned groups and the Open Geospatial Consortium (OGC) Data Quality Domain Working Group and information exchange meetings have been held. A peer-reviewed paper titled “Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets'' has been published in the Data Science Journal (DOI:http://doi.org/10.5334/dsj-2021-019). One of the purposes of this BoF meeting is to broaden the disciplinary base covered by these efforts beyond Earth science in promoting consistency when representing and communicating data quality information.
International FAIR-DQI community guidelines document: https://doi.org/10.31219/osf.io/xsu4p
Peer-reviewed call-to-action statement paper for sharing dataset quality information (DQI): http://doi.org/10.5334/dsj-2021-019
Workshop Summary Report: https://doi.org/10.31219/osf.io/75b92
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