Breakout 1 Socio-legal etc. Every discipline will be different & each data centre will have different answers to questions. Use a questionnaire and send.

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Presentation transcript:

Breakout 1 Socio-legal etc. Every discipline will be different & each data centre will have different answers to questions. Use a questionnaire and send to data centres. Promote use & interoperability through metadata standards. Resource discovery standards should be promoted & developed by learned societies/ (membership arms) subject communities by disciplines (not data curators). Bottom up rather than top down. Education – recognise v wide range of understanding amongst disciplines re value of data curation centres/IRs/archives – need go out and promote why they exist and why they should be used. Focus at p/g community. Political issue: every research council should have a written data policy, written, disseminated and policed. Some have them but not policed, need to be meatier than 7-8 words. Legal issues – value of JISC legal centre but like clarity of law where law exists re use of digital objects, IP etc need clarity of law and guidance on how best to interpret it. Model licences for use, interpretation, confidentiality, disclosure. Academics & data centre people need to be told differences between data banks/data centres etc and IRs. IRs have not had enough institutional buy-in. JISC could investigate why subject repositories are more successful than IRs. JISC policy should reflect what is happening on ground. – this is controversial! Comment – clarity of law is not easy – hope for clarity of assertions to uphold. Need straightforward answers to straightforward questions! JISC should help sell IRs better

Breakout 2 Technical etc. Need to define what is meant by semantics of structured data and publish guidelines at levels of metadata, classification/subject areas/factual names/agreed conventions layered on top e.g identifiers. Application profiles – who should be keeper of those definitions eg registries – who funds and owns them ? Scientists concentrate on narrow areas but connections are to other wider areas Time series are different – how discover and use? More difficult to define discovery metadata for time series. Data might not be logically the same. Data curation responsibility at institutional level/data centre – data curation requires specialisms and data centres could feed this expertise back to institutions – need flow of expertise from Data Centres to institutions Mixed economy re organisational responsibility is inevitable: some federation will be there – how to express quality – role for provenance and audit as a means to express quality; also ranking and annotation – the group liked Mark Thorley / NERC annotation levels 1-3 way of categorising annotations. Curation of data is of more interest to scientists than interoperability as a means of marketing/selling it.

Breakout 3 Roles & Responsibilities Individual scientists to deposit data using domain standards of an acceptable quality Re-user should acknowledge where data came from and if it is appropriate to improve the quality of the data. Institution should have policies that mandate data deposit in an appropriate place not necessarily an IR. Publishers/journals/editors should mandate open deposit of data. Curators who collect, describe and connect data, idea of community proxy role – (NSF ref) try to understand ontology of the domain and define standards for domain working, in and with the scientists Funders should enforce their data deposit policies where possible. Funders should recognise the emerging need for new infrastructure and provide appropriate funding for this infrastructure and for the resulting actions. Users and funders should feed back views on the data stored to the data centre manager Click use licence – says if you enhance the data you must give it back for us ESDS rule. But how police that policy by data centre? Versioning an issue here. Value of good enough versus completely comprehensive descriptions (Graham C) Who is responsible for ownership of the data to make changes? If multiple versions not necessarily the last one is best – look at annotation model? Competitive views: risk of sabotage of other groups work is possible. Who checks provenance of anything new? Curators?