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3TU.Datacentrum

3TU.Datacentrum. 3 Universities joined forces to support research with data-labs and archiving Jeroen Rombouts, TU Delft Library, March 28, 2011. Outline. Introduction 3TU.Datacentrum background

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3TU.Datacentrum

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  1. 3TU.Datacentrum 3 Universities joined forces to support research with data-labs and archiving Jeroen Rombouts, TU Delft Library, March 28, 2011

  2. Outline • Introduction3TU.Datacentrum background • Organisational challengesRoles and responsibilities divided among institutesFocus on research support • Service challengesAdd value for differing needs

  3. Background • Delft University of Technology16,400 students 4,700 staff (204 professors) • Eindhoven University of Technology7,000 students 3,100 staff (169 professors) • University of Twente8,400 students 3,000 staff (180 professors) • 3TU.Datacentrum initiated 2008 by University libraries as 3yr project by 3TU.Federation • Current year for transition to going concernStructural funding, staff, QA, promotion focus on data consumers • Challenge: ‘Competitors’ trusting each other!

  4. Organisational solutions • New ‘flag’: 3TU • Front offices • Local 3TU.Datacentrum staff as liaison and ‘primary’ data stewardsFew people at every institute with basic knowledge of data management and 3TU.Datacentrum product catalogue • Back office • Special expertise and archive at TU DelftTU Delft has national task and builds on two previous projects: E-Archiving – digital depot, Darelux – Data Archiving River Environment LuxemburgOther projects at other universities • Data-labs • Consult, support, build platforms for on-going research (projects)Trying Data Verse Network and supporting 2 community platforms

  5. Experience • Front office • Being (physically) close helps building trust • Huge ‘disciplinary’ (individual) differences in openness and data management level • Need more than a few (trained) people • Back office • Wide array of skills required (legal, it, management, digital curation, research tools, training, …) • Trade-off between long term preservationand (re-)use • Balancing generic and discipline specific • Data labs • Value for acquisition and standardisation

  6. Researcher Needs • Security • Long term, source preservation, backup, … • Data exchange • Visibility, access, enable sharing, efficient distribution, … • Storage space • Finished project data, … • Claim • Pre-publication data sharing, verification, … • Quality • Standards, … • (Access) Efficiency • Data modelling, retrieval, …

  7. Service/technical solutions • ‘Simple’ data setsSingle file (BagIt) per data set (can be a ‘zipped’ collection).Standard (self)upload form and descriptive information, • Special collectionsRelation network of data sets, instruments, time, locationsandareas – formalised in RDF.Negotiate: deposit procedure, descriptive information (xml, picture, preview), data model, … • Queryingfor large (array) data sets (OPeNDAP) • We offer tailor-madeif … • The data collection fits the objects + datastreams + relations setup • Yourfunctionalrequests has (expected) generalapplicability • You do notrequire a different look & feel”

  8. Special collections

  9. Simple data sets • Standard (bibliographical) meta data • Single datastream “BAG” (BagIT)zipfile containing data en technical meta data Most cases only data required.Meta data for long term preservation:- checksums- mapping of file extensions to mime-types

  10. Example

  11. Experience • Advice by 3TU.Datacentrum is much appreciated • Digital Object Identifiers (DOIs) as ‘carrots’ (TU Delft Library is a DataCite partner) • Difficulttograsprelational data model

  12. Conclusions Evaluation • Opportunities for university libraries • People training (data librarians & data scientists) required • Data acquisition/ingest, training, raising awareness, cultural change are all slow processes • High IT ‘awareness’ researchers makes life easy & difficult Plans • Expand front offices • Discipline archive collaboration • Expand staff and skills • Data consumers • Funding

  13. Questions & Discussion

  14. Links • Main website: datacentrum.3tu.nl • Data website: data.3tu.nl • Example special collections: • OPeNDAP + picture ‘quicklook’: IDRA drizzle radar data: http://dx.doi.org/10.4121/uuid:5f3bcaa2-a456-4a66-a67b-1eec928cae6d • XML view: Hospital event log: http://dx.doi.org/10.4121/uuid:d9769f3d-0ab0-4fb8-803b-0d1120ffcf54 • Simple data sets: • Laser measurements flame: http://dx.doi.org/10.4121/uuid:cb9c1edd-1120-4a05-b28a-6091c15545c7 • DataCite: datacite.org

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