{"id":5490,"date":"2019-11-04T13:26:32","date_gmt":"2019-11-04T12:26:32","guid":{"rendered":"https:\/\/www.go-fair.org\/?p=5490"},"modified":"2020-07-14T16:42:54","modified_gmt":"2020-07-14T14:42:54","slug":"workshop-report-data-discovery-across-disciplines-at-open-science-fair-2019","status":"publish","type":"post","link":"https:\/\/www.go-fair.org\/2019\/11\/04\/workshop-report-data-discovery-across-disciplines-at-open-science-fair-2019\/","title":{"rendered":"Workshop report: \u201cData Discovery Across Disciplines\u201d at Open Science Fair 2019"},"content":{"rendered":"\r\n

While we have made great strides when it comes to accessibility of scientific data, discoverability is seriously lacking. As a result, up to 85% of research data are not reused<\/a>. Discoverability is therefore one of the key challenges for FAIR data, especially across disciplines.<\/p>\r\n\r\n\r\n\r\n

The GO FAIR Implementation Network on Discovery<\/a> has taken up this challenge with a particular focus on user interfaces and other user-facing services. As part of our activities, we organized a workshop entitled \u201cData Discovery Across Disciplines\u201d\u00a0 at the Open Science Fair 2019<\/a>. The goals of the workshop were to introduce the topic to the audience, start a discussion and get their input for our stocktaking of the current landscape of data discovery.<\/p>\r\n\r\n\r\n\r\n

The workshop proved to be very popular with the conference audience, as we were happy to welcome around 80 participants. In the session, we introduced participants to current challenges and best practices around data discovery, as well as existing tools from the network. We also asked the audience for their use cases and for relevant open pieces of infrastructure that we had overlooked. Here, the diverse audience of Open Science Fair proved to be a strong asset, bringing in different views not only from researchers, but also from developers, funders, and companies.<\/p>\r\n\r\n\r\n\r\n

The discussion in the workshop demonstrated that FAIR data discovery is still an emerging area that requires our attention. It also showed that there is a strong need for better and more open user interfaces to carry out this task, validating the approach of the IN. The participants provided us with valuable input for our stocktaking, which we will structure and synthesize in the coming weeks. We will then use this input to define the standards and structure\u00a0 of an open ecosystem for data discovery and work towards its implementation.<\/p>\r\n\r\n\r\n\r\n

Resources:<\/p>\r\n\r\n\r\n\r\n