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Ten recommendations for data repositories/catalogues to improve data discoverability

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    Discussion
  • #133927

    Introduction of the group (10 minutes)

    Introduction: Ten simple rules for data repositories/catalogues to improve data discoverability (15 minutes)

    Updates from participants on work related to the ten rules (20 minutes)

    Discussion and feedback on the ten rules (30 minutes) 

    Wrap up and steps forward (15 minutes)

    Additional links to informative material
    The group has delivered the following three supporting outputs: 

    Eleven quick tips for finding research data

    Data discovery paradigms: user requirements and recommendations for data repositories

    A survey of current practices in data search services

    Slides from previous plenary sessions: 

    March 2023 – RDA Virtual Plenary 20:

    Recommendations for data repositories to improve data discoverability

    June 2022 – RDA Virtual Plenary 19:

    Searching for connections: Data search, web search and literature search (Group session, slides)

    November 2021 – RDA Virtual Plenary 18:

    Mapping the road ahead for the data discovery paradigms IG (Group session, slides)

    January 2021 – RDA Virtual Plenary 17:

    Investigating data discovery across domains (Group session, slides)

    November 2020 – RDA Virtual Plenary 16:

    What information about data do users desire for discovery? (Group session, slides)

    April 2020 – RDA Virtual Plenary 15:

    Inferring data searchers’ intent and their interaction with data discovery systems (group session)

    Data Granularity BoF; user perspectives, data citation and data versioning (BoF session)

    Oct. 2019 (P14) – Data Discovery Paradigms IG: Reports from Task Forces and Way Ahead (slides)

    April 2019 (P13): Data Discovery Paradigms IG: Reports from Task Forces and Way Ahead (slides)

    Oct. 2018 – RDA Plenary 12; IG meets, Task Forces report back

    March 2018 — RDA Plenary 11; IG meets, Task Forces report back

    Slides from earlier plenaries are available from the group page.

    Avoid conflict with the following group (1)
    FAIR for Machine Learning (FAIR4ML) IG

    Brief introduction describing the activities and scope of the group
    The objective of this IG is to provide a forum where representatives from across the spectrum of stakeholders and roles pertaining to data discovery can work together to identify, study and make recommendations concerning issues related to improving data discovery. The goal is to produce concrete deliverables that will be recognised and valued by the research and data communities.
    This group was officially endorsed at RDA P9. The group has worked on the following task forces, namely:

    User studies in data discovery (ongoing)

    Data/Metadata granularity (ongoing, a BoF has been submitted)

    Using schema.org for research dataset discovery (This task force has spun off to the Research Metadata Schemas Working Group, which was endorsed in Sept. 2019).

    Task forces from the group:

    Relevancy ranking (completed)

    Use cases, prototyping tools and test collections (completed)

    Best practice for making data findable (completed)

    Metadata enrichment (closed)

    Data granularity (became a WG, in progress)

    Publish structured metadata (became the Research Data Schemas WG, completed)

    User study of data discovery context and search behaviour (in progress)

    Estimate of the required room capacity
    30-50

    I Understand a Chair Must be Present at the Event to Hold the Breakout Session
    Yes

    Meeting objectives
     
    Click here for the collaborative session notes
     
    To update the group progress

    To get feedback on: Ten recommendations for data repositories/catalogues to improve data discoverability

    Please indicate at least (3) three breakout slots that would suit your meeting.
    Breakout 1, Breakout 2, Breakout 4

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