Towards Metadata Requirements for Data Quality Assessment Joint Meeting
- Collaborative Notes Link: https://drive.google.com/open?id=18mk42-T3IOwgnvEq77KlefH1_5XHjDOqJMhRLq...
The agenda will include three presentations of 15 mins each, followed by an open discussion.
- An overview of data quality assessment in disciplinary and cross-disciplinary contexts (Social Science IG chairs)
- Outcomes of the RDA data quality and fitness for purpose working group (Marina Soares e Silva, WDS/RDA Data Fitness for Use WG co-chair)
- Metadata requirements for data quality assessment (Luiz Bonino, GO FAIR)
- Discussion on interest in establishing a working group on shared practices and tools for data quality assessment
The FAIR principles, by design, do not include any reference to quality due to its contextual nature (what is of high quality for one purpose may be of low quality for another). However, the principles indicate the need for providing rich metadata such as provenance and for meeting standards. The purpose of the open discussion is to contextualise the FAIR principles with respect to data quality and debate what metadata information is required for quality assessment. For example, is it possible to establish an RDA recommendation for a metadata schema that enables data quality assessments?
The aim of this joint meeting is to discuss shared interest in the development of metadata quality checking “tools” or “checklists”, etc. for improving and progressively automating metadata checking of research data deposited with data repositories. There will be four objectives to the meeting:
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Understanding the current state of data quality assessment practices and tools in interested disciplines and communities
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Examining cross-disciplinary approaches to assessing data quality, and the potential for automated quality assessment
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Reviewing recent RDA efforts in relation to data quality assessment and fitness for purpose
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Determining interest in a joint working group to establish shared practices and tools for data quality assessment
This is the first proposed joint meeting of these interest groups, with the intent of discussion of a potential working group.
Social Science Research Data IG - https://www.rd-alliance.org/groups/social-science-research-data-ig. The Social Sciences Research Data (SSRD) Interest Group operates under the auspices of the Research Data Alliance (RDA), to foster diverse professional exchange on issues particular to data originating from the social sciences and related disciplines.
WDS/RDA Assessment of Data Fitness for Use WG - https://www.rd-alliance.org/groups/assessment-data-fitness-use The RDA FAIR Data Maturity Model Working Group develops as an RDA Recommendation a common set of core assessment criteria for FAIRness and a generic and expandable self-assessment model for measuring the maturity level of a dataset.
Fair Data Maturity Model WG - The RDA Working Group "FAIR data maturity model" was established in January 2019 and aims primarily to develop a common set of core assessment criteria for FAIRness as an RDA Recommendation. In the course of 2019, the WG established a set of indicators and maturity levels for those indicators through participation and contributions from the WG members.
GO FAIR IG - https://www.rd-alliance.org/groups/go-fair-ig GO FAIR stands for Global Open FAIR and aims at bringing interested stakeholders together to define a practical and concrete approach for implementing the FAIR principles. GO FAIR is organized in terms of Implementation Networks (INs) that are groups of stakeholders that decide to collaborate to define, design and/or implement elements that can contribute to a global platform for data, services and computing capacity interoperability. The GO FAIR Interest Group (GFIG) aims at serving as a bridge between the various GO FAIR INs and RDA’s Interest and Work Groups. The GOFAIR Interest Group has not yet been endorsed as an RDA IG, but will present as part of the joint session, with a view to contributing to the joint group program if and when they are endorsed as an IG.
QAMyData - quality assessment tool from the UK Data Archive - https://www.ukdataservice.ac.uk/about-us/our-rd/qamydata.aspx
Fitness for Use working group outputs - https://www.rd-alliance.org/group/wdsrda-assessment-data-fitness-use-wg/outcomes/wdsrda-assessment-data-fitness-use-wg-outputs
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