Breakout 1 Socio-legal etc. - PowerPoint PPT Presentation

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Breakout 1 Socio-legal etc.

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... send to data centres. Promote use & interop thro metadata standards resource discovery standards ... Education recognise v wide range of understaing amongst ... – PowerPoint PPT presentation

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Title: Breakout 1 Socio-legal etc.


1
Breakout 1 Socio-legal etc.
  • Every discipline wil be different each
    datacentre will have diff answers to questions.
    Use questionnaire and send to data centres.
  • Promote use interop thro metadata standards
    resource discovery standards should be promtoed
    dev by learned societies/ (membership arms)
    subject communities by disciplines (not data
    curators). Bottom up rather than top down. (not
    JISC!)
  • Education recognise v wide range of understaing
    amongst disciplines re value of data curation
    centres/IRs/archives need go out and prmote why
    they exist and why should be used. Focus at p/g
    community.
  • Political issue every research council should
    havce a written data policy, written,
    disseminated and policed. Some have them but not
    policed, need more meatier than 7-8 words.
  • Legal issues value of JISC legal centre but
    like clairty of law where law existis re use of
    digital objects, IP etc need clarity of law and
    guidance on how best to interpret it. Model
    licences ffro use, interprtation,
    confidentiality, disclosure.
  • Academics data centre people need to b told
    differences between data banks/data centres etc
    and IRs. IRs have not had enough institutional
    buy-in. like to know/JISC to investigate why
    subject repositoires more successful than IRs.
    JISC policy should reflect what is happening on
    ground. controversial!
  • Comment clarity of law is not easy hope for
    clarity of assretians to uphold. Need
    straightforward answers to straightforward
    questions!
  • JISC should help sell IRs better

2
Breakout 2 Technical etc.
  • Need to define what is meant by semantics of
    structured data and publish guidelines at levels
    of metadata, classiffication/subject
    areas/factial names/agreed conventions layerd on
    top e.g identifiers. Ie 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 toher areas
  • Timeseries are dufferent how discover and use?
    More diffciult to defind discovery metadata for
    time series. Data might not be logically the
    same.
  • Data curation responsility at institutional
    level/data centre data curation requires
    specialisms and data cnetres could feed this
    expertise back to institutions need flow of
    expertisefrom DCs to institutions
  • Mixed economy re org reposnsibility is inevitable
    some federation will be there how to express
    quality role for provenance audit as a means to
    express quality also ranking and annotation
    liked levels 1-3 way of thinking about
    annotations
  • Curation of data is of more ineterst to
    scientists than interoperability re
    marketing/selling it.

3
Breakout 3 RR
  • Individual scientists to deposit data using
    domain standards of an acceptable quality
  • Reuser should acknowledge where dat came from and
    if approp to imporive the quality of the data.
  • Institution should have policies that mandata
    dposit in an appopiate place not neces 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 efine
    standards for domain working in and with the
    scientists
  • Funders should enforce their data deposit
    policies where possiblem recognise emerging need
    for new infrastructure and provide aprop funding
    for new infrsstructure and for their resulting
    actions
  • Feed back views on data to the data centre
    manager (not snivel in public meetings).
  • Click use licence says if you enmhance the data
    you must give it back for us ESDS rule. But how
    police that policy by data centre? Versioning an
    issue here
  • Good enough versus completely comprehensive
    descriptions (Graham C)
  • Who is reposnsible for ownership of the data to
    do changes? If mutiple versions not necessarily
    last one is best look at annotation model
  • Competeitve views re sabotage other groups work
    is possible.
  • Who checks provence of anyrthing new? Curators?
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