Notes from RDA Interest Group meeting, September 17, 2013

[I am reposting to a wiki page- with notes attached]

Hi all,

At long last, I am finally getting around to posting some notes from the Washington meeting on September 17, 2013. Thanks to Wolfram Horstman, Sarah Ramdeen, and Najla Rettberg for taking notes during the meeting.

We had a very wide ranging discussion at the 2.5 hour meeting, which is documented in the detailed notes that I have attached. The broad outcomes are documented below.

After consideration, I wonder if the best place to start is to undertake a survey of current practices for long-tail data management. Nothing too detailed or onerous for people to respond to, but it might give us a starting point to begin developing best practices and also making some recommendations for improving both interoperability and discovery of datasets. We already have 38 people signed up for this Interest Group, which would give us a good start in terms of responses. 

If you have any thoughts about the survey or other possible next steps, or if you have comments about the meeting notes, please feel to add them below or get in touch with me any time.


Meeting Outcomes:

  • Over 50 people participated in the session
  • Long tail cannot be easily defined and may be understood very differently depending on the context.
  • Right now, most institutions collecting long tail data are happy to accept anything researchers have prepared for deposit. We are not yet at the stage where selection policies are at play.

Some potential areas of work for the group:

  • Gather and share current practices and lessons learned
  • Work towards greater interoperability of long-tail data
  • Facilitate discovery (i.e. federated search systems and exposing metadata to other systems)
  • Advocate for the need for collection and preservation of long-tail data (perhaps overlap with other groups)
  • Understand the factors that contribute to researchers willingness to deposit
  • Identify cost and funding models for managing long-tail research data
  • Gather evidence to better understand the long tail