Post on 28-Mar-2015
A centre of expertise in digital information management
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Digital libraries and digital scholarship: changing roles and responsibilities?
Dr Liz Lyon
Director, UKOLN
SCONUL Conference, Newcastle, June 2006.
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A centre of expertise in digital information management
www.ukoln.ac.uk
Overview1. Some images of scholarship
• Perceptions from the past• 23rd June: today• “Native digital scholar” beyond 2010?
2. Digital libraries and e-Research infrastructure• Data creation and capture • Data curation and preservation• Data citation, discovery and use• Adding value and Knowledge extraction
3. A Case Study4. Roles & responsibilities: new challenges?
A centre of expertise in digital information management
www.ukoln.ac.uk
The scholar in AD 731
Folio 3v Codex Beda Petersburgiensis
Scholarship today? OA landscape
A centre of expertise in digital information management
www.ukoln.ac.uk
http://www.flickr.com/photos/97797311@N00/61648107/
23 June 2006
Architecture of Participation?
A centre of expertise in digital information management
www.ukoln.ac.uke-Scientist desktop?
Slide: Carole Goble
Data-centric 2020 vision
Reference datasets as infrastructure?
Human discourse: supporting persistent
conversations?
MEMETIC Project
JISC VRE Programme
Compendium software + Access Grid
http://www.anotherlanguage.org/interplay/packetcreek/
Performing Arts & Access Grid
A centre of expertise in digital information management
www.ukoln.ac.uk
New forms of publication: integration of data and journals
A centre of expertise in digital information management
www.ukoln.ac.uk
Digital libraries & e-Research Infrastructure
(Very simple) e-Research Cycle
Formulate hypothesis / ideas, test, experiment, observe: data creation,
collection & capture
Adding value: Data linking, annotation,
visualisation, simulation
(New) knowledge extraction: data mining, modelling, analysis, synthesis
e-Infrastructure
Open access
Collaboration
Scholarly communications: data disclosure, publication, citation, discovery, re-use
Data management storage & validation: description, deposit,
self-archiving, preservation,
certification
Data processing
Data processingData processing
Data processing
Data processing
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Understanding the research process
• Core business process? Workflows?• Project StORe: Source-to-Output Repositories (Edinburgh)
– Primary data : research publications– Survey questionnaire
• RepoMMan: Repository Metadata and Management (Hull)– Survey questionnaire and interviews– Activity diagram and workflow
• How is primary research data captured in faculty and academic departments?
• Where and how is primary research data stored in your institution?
• What data is curated by data centres?
Learning & Teaching workflows
Research & e-Science workflows
Aggregator services: national, commercial
Repositories : institutional, e-prints, subject, data, learning objects
Institutional presentation services: portals, Learning Management Systems, u/g, p/g courses, modules
Harvestingmetadata
Data creation / capture / gathering: laboratory experiments, Grids, fieldwork, surveys, media
Resource discovery, linking, embedding
Deposit / self-archiving
Peer-reviewed publications: journals, conference proceedings
Publication
Validation
Data analysis, transformation, mining, modelling
Resource discovery, linking, embedding
Deposit / self-archiving
Learning object creation, re-use
Searching , harvesting, embedding
Quality assurance bodies
Validation
Presentation services: subject, media-specific, data, commercial portals
Resource discovery, linking, embedding
The scholarly knowledge cycle.
Liz Lyon, Ariadne, July 2003.
This work is licensed under a Creative Commons LicenseAttribution-ShareAlike 2.0
© Liz Lyon (UKOLN, University of Bath), 2005
“JISC Vision”: a global landscape of federated repositories
fusion layer ‘repository federator’
repository repository repository repository repository
portal portal portal portal portal
heterogeneous - metadataformats, content formats,identifiers, packagingstandards
homogeneous - metadataformats, content formats,identifiers, packagingstandards
From Andy Powell: http://www.ukoln.ac.uk/distributed-systems/jisc-ie/arch/presentations/jiie-jcs-2005/
• Multi-disciplinary, cross-sectoral
• National, institutional
• Different platforms
• Many format types: data, eprints, images, geospatial
• e-Framework and Information Environment context
• Define common + domain-specific + repository “services”
• Interoperability based on open standards, software tools
Digital repositories, OA & preservation• Long-term access: trust, responsibility, policy• Trusted DR Audit Checklist for Certification Draft Research Libraries
Group-NARA Taskforce 2005• Defined criteria under 4 categories
– Organisation– Functions, processes & procedures– Designated community & usability– Technologies & technical infrastructure
• UK Digital Curation Centre: advice, tools & services• RepInfo Registry• EU CASPAR Integrated Project
• Task Force on the Permanent Access to the Records of Science
http://www.dcc.ac.uk/
http://www.casparpreserves.info/pages/1/index.htm
http://tfpa.kb.nl/
Data, metadata and discovery• Validation, publication & discovery of data models
& schema• Metadata packaging standards
– METS, MPEG 21 DIDL– Complex object model?
• Semantic descriptions– Formal high-level and domain ontologies– Inter-disciplinary discovery
• ePrints DC Application Profile • UK Intute IR search service (eprints)• Informal social network approaches
“folksonomies”• What data models and metadata schema are
in place?• Have librarians been involved in their
development?
Persistent identifiers for data citation• How will they be used? We need use cases: depositor,
author, service provider, researcher, publisher?• Schemes: DOI, Handle, ARK, PURL• Publication & citation of scientific primary data project
National Library for Science & Technology (TIB), University of Hanover, Germany. STD-DOI Project DOI registry for datasets http://www.std-doi.de
• What persistent identifiers have been assigned to your data?• Is there a data citation policy?• Was the Library involved?
Adding value: repository services• Tools: for deposit, normalisation, manipulation, transformation…..
• Linking, annotation, visualisation
• Aggregators: generic, (sub-) disciplinary
Knowledge extraction:• Mining (data, text, structures)
• Modelling (economic, climate, mathematical, biological…)
• Analysis (statistical, lexical, gene….)
Is your data OA?
How is your data being used and re-used?
Avian flu outbreaks mashup - Nature January 2006
Data from FAO, WHO…
+Google Earth
Nature 23 March 2006 OTMI: Open Text Mining Interface
NaCTeMhttp://www.nactem.ac.uk/
Emerging tools: TerMine, GENIA, Cafetiere
A centre of expertise in digital information management
www.ukoln.ac.uk
A Case Study in Crystallography
A centre of expertise in digital information management
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Data capture
Deposit scenario (…part of….)1. Produce strategy for synthesis (=idea)
2. Submit plan to SmartTea system (incl. identifiers)
3. Retrieve and follow instructions (sub-workflow?)
4. Experimental synthesis metadata automatically recorded on instruments (Smart Lab)
5. Create record for synthesised sample (+ proposed chemical identifier) in R4L laboratory data management system
6. Run spectral analyses on sample capturing further analysis metadata (incl. time-stamp, analysis software version, researcher details etc.)
7. Save spectrum in native and common formats
8. Invoke R4L data capture service and deposit files + metadata in laboratory repository…
RAW DATA DERIVED DATA RESULTS DATA
A centre of expertise in digital information management
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eBank UK Project• Promote open access crystallography data • Aggregator service harvests OAI metadata from institutional data
repository (e-Crystals archive)• Service linking from data to derived research publication• Embedding eBank service in learning workflows: pedagogy• Future federation plans for crystallography data repositories
UKOLN (lead), University of Southampton, University of Manchester
http://www.ukoln.ac.uk/projects/ebank-uk/
A centre of expertise in digital information management
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A data repository entry ecrystals.chem.soton.ac.uk
Access to the underlying data: complex objects
eBank Metadata Publication
• Using simple Dublin Core • Crystal structure• Title (Systematic IUPAC Name)• Authors• Affiliation• Creation Date
• Additional chemical information through Qualified Dublin Core• Empirical formula• International Chemical Identifier InChI • Compound Class & Keywords
• Specifies which ‘datasets’ are present in an entry• Application Profile• DOIs from TIB http://dx.doi.org/10 .1594/ecrystals.chem.soton.ac.uk/145
• Data citation policy http://ecrystals.chem.soton.ac.uk/rights.html
http://www.ukoln.ac.uk/projects/ebank-uk/schemas/
Discovering data:
Coles, S.J., Day, N.E., Murray-Rust, P., Rzepa, H.S., Zhang, Y., Org. Biomol. Chem., 2005, (10),1832-1834. DOI: 10.1039/b502828k
• Domain identifier: International Chemical Identifier (INChI) code• Google molecule using INChISlide from Simon Coles
Adding value: eBank linking data to
publications
Linking research to learning - embedding eBank aggregator service in a science portal for student learners
Integration into the curriculum and e-Learning workflows
• MChem course • Assess role in
Undergraduate Chemical Informatics courses
• Pedagogic evaluation• April – June 2006• Report to follow.
e-Research workflows
Aggregator services
Institutional data repositories
Data curation & preservation: databases & databanks
Validation
Harvest
Data creation & capture in “Smart lab”
Deposit
Publishers: peer-review journals, conference proceedings
Publication
Validation
Data analysis, transformation, mining, modelling
Search, harvest
Presentation services: portals
Data discovery, linking, citation
Linking, citation
Laboratory repository
Deposit
(Chemistry Central)
e-Crystals Federation model
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A centre of expertise in digital information management
www.ukoln.ac.uk
Roles & responsibilities: new challenges?
Workforce development and capacity building
• NSF Draft Report 2005 “Data scientist” - hybrid skills
• Facilitate collaboration– “Multidisciplinary teams: computer
scientists, domain scientists, digital library experts, statisticians/modellers e.g. eBank project
– Lessons learnt: e-Science Human Factors Audit Report (to be published 2006) Roy Kawalsky, Loughborough
• CURL/SCONUL e-Research Taskforce
Has your (digital) library engaged with the e-Research agenda?
Supporting the “native digital scholar”• Develop leadership & vision for eResearch engagement
and infrastructure development• Provide (e-)Services for data
– We “do” eLearning so why not eResearch?– Include in institutional digital asset management plans
• Review organisational structures– Extend & re-profile the Faculty/Subject/Reference Librarian role– Collaborate closely with Computing Services and Depts
• Promote professional development of staff– Raise awareness, acquire new skills– Build multidisciplinary teams, explore emergent roles
Respond to the challenge...The Future is NOW
A centre of expertise in digital information management
www.ukoln.ac.uk
Thank you.
UKOLN receives core funding from the Joint Information Systems Committee (JISC) and the Museums, Libraries & Archives Council (MLA)
and is based at the University of Bath, UK.