Metadata and Granularity: a deeper examination for the FAIR Data Maturity Model
Collaborative session notes: https://docs.google.com/document/d/1bCLVb06vCBSsYt_CgHMN34Vu-uQ69KA26sSD3ZQ62EY/edit?usp=sharingWelcome, objectives of the meeting [5 minutes]
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Overview of the FDMM and the current focus on Metadata and Granularity [5 minutes]
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Metadata Elements and Granularity [5 minutes]
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Brief review of the work intended for Data Granularity WG [5 minutes]
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General discussion (part 1) - The maturity model and how it applies to evaluating metadata.
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General discussion (part 2) - The maturity model and how it applies to the level of granularity of the data being evaluated.
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Action items and next steps
The proposed session will bring together people interested in the RDA FAIR Data Maturity Model and other FAIR assessment approaches, to discuss the future development and evolution of the RDA FAIR Data Maturity Model and its relation to other FAIR initiatives. In specific, we are focused on both metadata (Metadata IG) needed to understand a dataset and the granularity (Data Granularity WG) in which datasets should be referenced as it applies to a FAIR assessment or a dataset.
This joint session is intended to develop relationships with the Metadata IG and Data Granularity WG (pending endorsement) working on the specific concerns that will inform the next version of the FAIR Data Maturity Model.
FAIR Data Maturity Model WG
The FAIR Data Maturity Model Working Group worked in 2019 and the first half of 2020 to develop an RDA Recommendation on assessment of FAIRness in research data. The RDA Recommendation FAIR Data Maturity Model: specification and guidelines was published on 8 June 2020 (https://doi.org/10.15497/RDA00050). Since then, the Working Group has entered maintenance mode and is currently developing a work plan for the next years.
Metadata IG
The Metadata Interest Group has spun off 2 working groups, the Metadata Standards Directory WG and the Metadata Standards Catalog. Both of those groups have been completed and are in maintenance mode. New content continues to be added to the Metadata Standards Directory and a new version of the Metadata Catalog was released in 2020. The Metadata Interest Group continues the work of unpacking the proposed Metadata Elements.
Data Granularity WG
The Data Granularity Working Group is currently in the process of submitting a case statement to be admitted as a formal working group. Once the status is achieved, the next step is to collect use cases and survey the community. The overall goal is to provide a guidance document containing information on use cases, best practices and community feedback.
FAIR Data Maturity Group Working Group
The RDA FAIR Data Maturity Group was established at the end of 2018 with the objective to bring together stakeholders from different scientific and research disciplines, the industry and public sector, who are active and/or interested in the FAIR data principles and in particular in assessment criteria and methodologies for evaluating their real-life uptake and implementation level. The Working Group completed 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. The group has over 250 members representing a wide range of disciplines and regions around the world.
Metadata Interest Group
The Metadata Interest Group (MIG) is supported by individuals and organizations involved in the development, implementation, and use of metadata for scientific data. MIG’s chief objective is to identify and endorse metadata solutions for addressing data management challenges. Metadata is crucial for the discovery, access, preservation, exchange, manipulation, and use/re-use of research data. Metadata discussions frequently focus on community-specific issues such as discipline-specific standards; however, there are dimensions of metadata that are of general interest, cross disciplines, and are amenable to broad community input. MIG endorses metadata solutions that balance domain-specific and interdisciplinary needs.
MIG has proposed metadata ‘packages’ for the commonly required purposes; a ‘package’ consists of elements (attributes or data structures) the values of which relate to the unique identity of the dataset or record (instance). To assure machine processing a formal syntax and declared semantics are required, and the packages must exhibit referential and functional integrity as well as human readability.
Data Granularity Working Group
The RDA Data Granularity Working Group is currently forming out of a Task Force within the Data Discovery Paradigms Interest Group (DDPIG). Early activities include Birds-of-a-feather sessions at the RDA 15th and 16th Virtual Plenary with very positive feedback. A case statement is currently being prepared to apply for formal RDA Working Group status.
We address issues of data granularity in data discovery, access, interoperability, analysis, citation, and more. More efficient and effective reuse of data requires that users can find and access data at various levels of granularity. The WG will explore key questions and collect and share valuable information for how to best support data granularity, providing guidance to help data professionals to determine the best level of granularity for user discovery, access, interoperability and citability. The activities and final recommendations of the Data Granularity WG will build upon and complement existing and ongoing work of several RDA Working and Interest Groups that touch upon the subject of data granularity. The final deliverable for the WG is a set of collected use cases and a guidance document of data granularity approaches for prioritized use cases, including terminology, methods to evaluate approaches, and a summary of community feedback.
The group currently has 11 founding members with many more having declared interest.
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