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

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Presentation on theme: "3TU.Datacentrum 3 Universities joined forces to support research with data-labs and archiving Jeroen Rombouts, TU Delft Library, March 28, 2011."— Presentation transcript:

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 1.Introduction 3TU.Datacentrum background 2.Organisational challenges Roles and responsibilities divided among institutes Focus on research support 3.Service challenges Add value for differing needs

3 Background Delft University of Technology 16,400 students 4,700 staff (204 professors) Eindhoven University of Technology 7,000 students 3,100 staff (169 professors) University of Twente 8,400 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 concern Structural 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 stewards Few people at every institute with basic knowledge of data management and 3TU.Datacentrum product catalogue Back office –Special expertise and archive at TU Delft TU Delft has national task and builds on two previous projects: E-Archiving – digital depot, Darelux – Data Archiving River Environment Luxemburg Other 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 preservation and (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 ‘Simple’ data sets Single file (BagIt) per data set (can be a ‘zipped’ collection). Standard (self)upload form and descriptive information, Special collections Relation network of data sets, instruments, time, locations and areas – formalised in RDF. Negotiate: deposit procedure, descriptive information (xml, picture, preview), data model, … Querying for large (array) data sets (OPeNDAP) We offer tailor-made if … –The data collection fits the objects + datastreams + relations setup –Your functional requests has (expected) general applicability –You do not require a different look & feel” Service/technical solutions

8 Special collections

9 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 Simple data sets

10 Example Example

11 Experience Advice by 3TU.Datacentrum is much appreciated Digital Object Identifiers (DOIs) as ‘carrots’ (TU Delft Library is a DataCite partner) Difficult to grasp relational 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.nldatacentrum.3tu.nl Data website: data.3tu.nldata.3tu.nl Example special collections: –OPeNDAP + picture ‘quicklook’: IDRA drizzle radar data: 1eec928cae6d 1eec928cae6d –XML view: Hospital event log: 0ab0-4fb8-803b-0d1120ffcf54http://dx.doi.org/ /uuid:d9769f3d- 0ab0-4fb8-803b-0d1120ffcf54 Simple data sets: –Laser measurements flame: 4a05-b28a-6091c15545c7http://dx.doi.org/ /uuid:cb9c1edd a05-b28a-6091c15545c7 DataCite: datacite.orgdatacite.org


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