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UKOLN is supported by: Realising the scholarly knowledge cycle: The experience of eBank UK Dr Liz Lyon, UKOLN, University of Bath, UK CNI Task Force Meeting.

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Presentation on theme: "UKOLN is supported by: Realising the scholarly knowledge cycle: The experience of eBank UK Dr Liz Lyon, UKOLN, University of Bath, UK CNI Task Force Meeting."— Presentation transcript:

1 UKOLN is supported by: Realising the scholarly knowledge cycle: The experience of eBank UK Dr Liz Lyon, UKOLN, University of Bath, UK CNI Task Force Meeting Spring 2004 Alexandria, Virginia, www.bath.ac.uk a centre of expertise in digital information management www.ukoln.ac.uk

2 CNI Spring 20042 Overview Setting the scene –e-Research trends –Towards a common infrastructure The scholarly knowledge cycle –Data, information and workflows –Provenance eBank UK Project –The experience so far –Issues arising Challenges for the future

3 Setting the scene

4 The next generation of research breakthroughs will rely upon new ways of handling the immense amounts of data that are being produced by modern research methods and equipment, such as telescopes, particle accelerators, genome sequencers and biological imagers….Similar developments are having an impact in the arts and humanities, and in the social sciences. A Vision for Research, Research Councils UK, December 2003.

5 CNI Spring 20045 Report of the National Science Foundation Blue-Ribbon Advisory Panel on Cyberinfrastructure 2003 http://www.cise.nsf.gov/sci/reports/toc.cfm

6 CNI Spring 20046 Report of the National Science Foundation Blue-Ribbon Advisory Panel on Cyberinfrastructure 2003 http://www.cise.nsf.gov/sci/reports/toc.cfm

7 CNI Spring 20047 UK e-Science Programme e-Science is about global collaboration in key areas of science and the next generation of infrastructure that will enable it. John Taylor, Director General, Research Councils, UK

8 CNI Spring 20048

9 CNI Spring 20049 Powering the Virtual Universe http://www.astrogrid.org (Edinburgh, Belfast, Cambridge, Leicester, London, Manchester, RAL) AstroGrid will provide advanced, Grid based, federation and data mining tools to facilitate better and faster scientific output. Picture credits: NASA / Chandra X-ray Observatory / Herman Marshall (MIT), NASA/HST/Eric Perlman (UMBC), Gemini Observatory/OSCIR, VLA/NSF/Eric Perlman (UMBC)/Fang Zhou, Biretta (STScI)/F Owen (NRA) :

10 CNI Spring 200410 e-Research: the trends? Increasingly data–intensive, quantitative Open access to data and information –OECD Declaration January 2004 Implementing new science Inter-disciplinary New disciplines e.g. Astro-informatics New skills requirements –IT + statistics + domain Collaborative –virtual / transient –communities / organisations Highly distributed resources

11 CNI Spring 200411 New resources…….used in new ways Primary / original data –Observational, experimental, numeric, genomic, 2/3D molecular structures, satellite images, electron micrographs, wave spectra, CAD, musical compositions, VR, performances, animations Data and information –Creation, discovery, gathering, aggregation, dis-aggregation, replication, federation, manipulation, transformation, linking, annotation, editing/versioning, validation, (self-)archiving, deposit, publication, curation Knowledge extraction and management –Analysis (textual, musical, statistical, mathematical, visual, chemical, gene……) –Mining (text, data, structures……) –Modelling (economic, mathematical, biological..) –Simulation (molecular, physical, environmental, games…) –Presentation (visualisation, rendering….)

12 CNI Spring 200412 Towards a common infrastructure UK e-Science Programme & JISC Development e-Science Phase 2 2003 – 2006 –A National e-Science Centre linked to a network of Regional Grid Centres –An Open Middleware Infrastructure Institute (OMII) based on common standards (Web Services) JISC Information Environment –Technical architecture based on open standards (Web Services, OAI-PMH, Z39.50, RSS…..) http://www.ukoln.ac.uk/distributed-systems/jisc-ie/arch/ –A Digital Curation Centre (DCC) http://www.dcc.ac.uk/ –Virtual Research Environments? A changing landscape of scholarly communications

13 The scholarly knowledge cycle

14 CNI Spring 200414 Research & e-Science workflows Aggregator services: national, commercial Repositories : institutional, e-prints, subject, data, learning objects Data curation: databases & databanks Validation Harvesting metadata Data creation / capture / gathering: laboratory experiments, Grids, fieldwork, surveys, media Deposit / self- archiving Peer-reviewed publications: journals, conference proceedings Publication Validation Data analysis, transformation, mining, modelling Searching, harvesting, embedding Presentation services: subject, media-specific, data, commercial portals Resource discovery, linking, embedding Linking

15 CNI Spring 200415 Research & e-Science workflows Aggregator services: national, commercial Repositories : institutional, e-prints, subject, data, learning objects Data curation: databases & databanks Validation Harvesting metadata Data creation / capture / gathering: laboratory experiments, Grids, fieldwork, surveys, media Deposit / self- archiving Peer-reviewed publications: journals, conference proceedings Publication Validation Data analysis, transformation, mining, modelling Searching, harvesting, embedding Presentation services: subject, media-specific, data, commercial portals Resource discovery, linking, embedding Linking

16 CNI Spring 200416

17 CNI Spring 200417

18 CNI Spring 200418

19 CNI Spring 200419

20 CNI Spring 200420

21 CNI Spring 200421

22 CNI Spring 200422 Research & e-Science workflows Aggregator services: national, commercial Repositories : institutional, e-prints, subject, data, learning objects Data curation: databases & databanks Validation Harvesting metadata Data creation / capture / gathering: laboratory experiments, Grids, fieldwork, surveys, media Deposit / self- archiving Peer-reviewed publications: journals, conference proceedings Publication Validation Data analysis, transformation, mining, modelling Searching, harvesting, embedding Presentation services: subject, media-specific, data, commercial portals Resource discovery, linking, embedding Linking

23 CNI Spring 200423 Learning & Teaching 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 Harvesting metadata Resource discovery, linking, embedding Peer-reviewed publications: journals, conference proceedings Validation 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

24 CNI Spring 200424 Learning & Teaching workflows Research & e-Science workflows Aggregator services: national, commercial Repositories : institutional, e-prints, subject, data, learning objects Data curation: databases & databanks Institutional presentation services: portals, Learning Management Systems, u/g, p/g courses, modules Validation Harvesting metadata 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 Linking

25 CNI Spring 200425 Learning & Teaching workflows Research & e-Science workflows Aggregator services: eBank UK Repositories : institutional, e-prints, subject, data, learning objects Data curation: databases & databanks Institutional presentation services: portals, Learning Management Systems, u/g, p/g courses, modules Validation Harvesting metadata 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 Linking

26 The eBank UK Project

27 CNI Spring 200427 eBank UK project JISC-funded for 1 year from September 2003 UKOLN (lead), University of Southampton, University of Manchester Building the links between research data, scholarly communication and learning e-Science testbed Combechem –Grid-enabled combinatorial chemistry –Crystallography, laser and surface chemistry –Development of an e-Lab using pervasive computing technology –National Crystallography Service Resource Discovery Network PSIgate physical sciences portal http://www.ukoln.ac.uk/projects/ebank-uk/

28 CNI Spring 200428 The project team UKOLN Michael Day Monica Duke Rachel Heery Liz Lyon + Andy Powell Southampton Les Carr Simon Coles Jeremy Frey Chris Gutteridge Mike Hursthouse Manchester John Blunden-Ellis

29 CNI Spring 200429 Key Deliverables 1.Requirements specification 2.Pilot service 3.Two supporting studies: –Provenance: review of current research –Feasibility report on dataset description and schema 4.Consultative evaluation workshop and report 5.Recommendations for future work

30 CNI Spring 200430 Diagram by Andy Powell, UKOLN Pilot service – technical architecture

31 Comb-e-Chem Project X-Ray e-Lab Analysis Properties Properties e-Lab Simulation Video Diffractometer Grid Middleware Structures Database

32 CNI Spring 200432 Crystallography workflow Initialisation: mount new sample on diffractometer & set up data collection Collection: collect data Processing: process and correct images Solution: solve structures Refinement: refine structure CIF: produce CIF Report: generate Crystal Structure Report

33 CNI Spring 200433

34 CNI Spring 200434 First steps: establishing common ground… Understand the data creation process Terminology and definitions –Data –Metadata –Datafile –Dataset –Data holding Different views –Digital library researchers, computer scientists, chemists –Generic vs specific –Modeller vs practitioner Aim for a common ontology Modelling the domain Creating a metadata schema

35 CNI Spring 200435 ebank_dc record (XML) Crystal structure (data holding) Crystal structure report (HTML) Dataset Institutional repository eBank UK aggregator service ePrint UK aggregator service Subject service Deposit Harvesting OAI-PMH ebank_dc Harvesting OAI-PMH oai_dc Searching, linking and embedding Dataset dc:identifier dcterms:references Linking dc:type=CrystalStructure and/or Collection Model input Andy Powell, UKOLN. PSIgate portal Eprint oai_dc record (XML) dcterms:isReferencedBy dc:type=Eprint and/or Text

36 CNI Spring 200436 Where are we now? Version 1.0 eBank metadata schema Pilot eBank repository for harvesting Exports records as ebank_dc and oai_dc Validation of schema –Against harvesting and searching –Against user requirements –Against other schema Concept of a collection and a Collection Level Description Implementing the pilot service

37 Challenges for the future

38 CNI Spring 200438 What next? The metadata schema…some issues Reduce to its simplest form or reflect the complexity? ebank_dc versus oai_dc Compatibility with other schema –CLRC Scientific Metadata Model vs 1.0 2001 (under revision) http://www-dienst.rl.ac.uk/library/2002/tr/dltr-2002001.pdf Investigate packaging options –METS –MPEG 21 DIDL –?? Expand to include SMART e-Lab metadata e.g. sample preparation

39 CNI Spring 200439 …and also…. Investigate identifiers e.g. International Chemical Identifier Metadata enhancement - subject keyword additions to datasets based on knowledge of keywords in related publications Develop search interface – embedding eBank UK Testing with PSIgate physical sciences portal Explore context sensitive linking: find me –Datasets by this person –Journal articles by this person –Datasets related to this subject –Journal articles on this subject –Learning objects by this person –Learning objects on this subject

40 CNI Spring 200440 Learning & Teaching workflows Research & e-Science workflows Aggregator services: eBank UK Repositories : institutional, e-prints, subject, data, learning objects Data curation: databases & databanks Institutional presentation services: portals, Learning Management Systems, u/g, p/g courses, modules Validation Harvesting metadata 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 Linking

41 CNI Spring 200441 Potential longer term impact 1.Track data, information and workflows in e-research and scholarly communications – knowledge audit?? 2.Validate the accuracy and authenticity of derived works – ideas audit?? 3.Facilitate explicit referencing and acknowledgment of original contributors – intellectual integrity?? 4.Raise standards associated with publication of research outputs – academic publishing rigour?? 5.Implement open access to and dissemination of data and information – enhance the research process?? 6.Give students links to original data underpinning published works – enhance the learning process??

42 CNI Spring 200442

43 Thank you. Questions?…..

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