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Agenda for Long Tail of Research Data Interest Group

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    Discussion
  • #138788

    If you are not attending the meeting in Washington, please post your dataset examples on the profile page of the wiki: https://rd-alliance.org/groups/long-tail-research-data-ig/wiki/dataset-p… [I think anyone who is a member of the group should be able to edit the wiki]

     

    RDA Long Tail of Research Data Interest Group Meeting
    September 17, 2013

    *Please note: Attendees are asked in advance to identify a dataset produced at an institutions, for which the researcher has archived the data locally or is looking for a place to archive the dataset. Please describe the dataset according to the following elements: domain (research area), format, size, doi (yes or no), any access restrictions (i.e. privacy OR readability). These examples will contribute to the development of a number of dataset profiles that will help us better understand the nature of research data that constitutes the so called “long tail”.

    Agenda

    1. Welcome: How did the interest group (IG) come about, what are the broad aims of the group.

    2. What is the long tail? Presentation by Wolfram Horstmann and general discussion
     
    3. Introductions and each person will describe their dataset (profiles will be developed based on these examples)
     
    4. Review and discuss draft objectives for the IG:

    • Define the scope of datasets that will be addressed in this project.
    • Develop a number of use cases, based on a range of disciplinary practices and other approaches.
    • Map the current repository landscape: to categorize the types of repositories that do exist along a number of axes such as domain, open/closed, data formats, etc.; to have a understand the capacity of existing repositories to collect small datasets
    • Identify gaps
    • Review data federation approaches that provide mechanisms for supporting discovery across the myriad of existing repositories (distinguish domain specific attributes from generalizable practices)
    • Identify and publish good practices.
    • Identify skills and competencies for those managing research data in university repositories.

    5. Next steps for the IG

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