UKOLN is supported by:

Enhancing access to research data:

the e-Science project eBank UK

www.bath.ac.uk

A centre of expertise in digital information management

2005-09-01 www.ukoln.ac.uk

                                                             

Enhancing access to research data: overview

• E-Science: impact of digital technologies on research process

• Scholarly knowledge cycle and publication bottleneck

• eBank project: applying digital library techniques to support data curation in crystallography

• Services, metadata, issues; phase 3

                                                             

Changes in research process

• Increasing data volumes from eScience / Grid-enabled / cyber-infrastructure applications, “big science”, data-driven science

• Changing research methods: high througput technologies, automation, ‘smart labs’

• Potential for re-use of data, new inter-disciplinary research

• Different types of data: observational data, experimental data, computational data: different stewardship and long-term access requirements

                                                             

Diversity of data collections• Very large, relatively homogeneous: Large-scale Hadron

Collider (LHC) outputs from CERN• Smaller, heterogeneous and richer collections: World Data Centre for

Solar-terrestrial Physics CCLRC• Small-scale laboratory results: “jumping robots” project

at the University of Bath• Population survey data: UK Biobank

• Highly sensitive, personal data: patient care records

                                                             

Taxonomy of data collections• Research collections:

jumping robots • Community collections:

Flybase at Indiana (with UC Berkeley )

• Reference collections: Protein Data Bank

Source: NSF Long-Lived Digital Data Collections Draft report March 2005

                                                             

Repository evolution:

1971 Research collection

<12 files

2005 Reference collection

>2700 structures deposited in 6 months

                                                             

1. Issues: research data as content

• Sharing or not; Open Access to data?• Data diversity

– Homo- or heterogeneous– Raw and derived / processed – Sensitivity– Fast or slow growth in volume

• Repository evolution: – Likelihood to scale up (from bytes to petabytes)– Quality assurance (from the start)– Community-based standards development – Relationship between institutional and subject r’s– Build robust services

                                                             

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

Data Overload!

How do we disseminate?

EPSRC National Crystallography

Service

The data deluge: crystallography

Data overload & the publication bottleneck

Cl

Cl

Cl

Cl

Cl

Cl

ClCl Cl

Cl

Cl

ClCl

O

O

O

O

N

N

N

N

N+

O

O

O

N+

O

O

O

25,000,000

2,000,000

300,000

Current Publishing Process• Journal articles: aims, ideas, context, conclusions – only most significant data

• Raw & underlying data required by peers not readily available

                                                             

Context: existing data repositories• National data archives:

– UK Data Archive, Arts and Humanities Data Service, US National Archives and Records Administration (NARA), Atlas Datastore

• Discipline specific archives: – GenBank, Protein Data Bank

• Crystallography archives– Cambridge Crystallographic Data Centre (Cambridge

Structural Database) , Indiana University Molecular Structure Center (Crystal Data Server, Reciprocal Net), FIZ Karlsruhe (Inorganic crystals), Toth Information Systems (CHRYSTMET)

• Journals require deposit of data to support articles– Typically deposit of summary data…. partial coverage

                                                             

eBank UK project overview

• JISC funded in 2003, now in Phase 2 to 2006• Joint effort between crystallographers, computer

scientists, digital library researchers• Investigating contribution of existing digital library

technologies to enable ‘publication at source’• Partners have interest in dissemination of

chemistry research data, open access, OAI, institutional repositories http://www.ukoln.ac.uk/projects/ebank-uk/

                                                             

eBank project team

University of Bath, UKOLN (lead)• Monica Duke, Rachel Heery, Traugott Koch, Liz

Lyon, University of Southampton, School of Chemistry• Simon Coles, Jeremy Frey, Mike HursthouseUniversity of Southampton, School of Electronics

and Computer Science• Leslie Carr, Chris GutteridgeUniversity of Manchester, PSIgate (physical

sciences portal in RDN)• John Blunden-Ellis

                                                             

eBank phase one: achievements• Gathered requirements from crystallographers • Established pilot institutional repository for

crystallography data at Southampton with web interface

• Developed a demonstrator aggregator service at UKOLN (CCDC exploring aggregation service)

• Developed appropriate schema • Demonstrated a search interface as an embedded

service at PSIgate portal• Demonstrated an added value service linking

research data to papers (one-off)

                                                             

Institutional repositories…publication at source

• Institution establishes repository(s)• Institution pro-actively supports deposit

process• OAI provides basis for interoperability • Potential for added value services

• And/Or ….international subject based archives?

                                                             

Crystallography good fit….

• Crystallography has well defined data creation workflow

• Tradition of sharing using standard file format

• Crystallography Information File (CIF)

• What about other chemistry sub-disciplines? other scientific disciplines?

                                                             

eBank: UK e-Science testbed ‘Combechem’

– Grid-enabled combinatorial chemistry– Crystallography, laser and surface chemistry

examples– Development of an e-Lab using pervasive

computing technology– National Crystallography Service at

Southampton

Comb-e-Chem Project

X-Raye-Lab

Analysis

Properties

Propertiese-Lab

SimulationVideo

Diff

ract

omet

er

Grid Middleware

StructuresDatabase

Crystallography workflowRAW DATA DERIVED DATA RESULTS DATA

• 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 (Crystallographic Information File)• Validation: chemical & crystallographic checks

Data Collection

Diffraction

Unit Cell

Success

Strategy

Data Collection

Data Process

System Y

PreScans

Yes

Yes

BruNo Mount

BruNo Unmount

Setup via GUI

Sample Tray

No

No

Data Flow in eBank UK

OA

I-P

MH

Submit

Store/link

Harvest (XML)

Index and Search

Data files

Metadatapresent

HTML

present

HTML

Institutional repository

eBank aggregator

Create

                                                             

Southampton digital repository

http://ecrystals.chem.soton.ac.uk

Access to ALL underlying data

                                                             

Harvesting: OAIster

OAI-PMH: harvesting and aggregating

eBank aggregator at UKOLNhttp://eprints-uk.rdn.ac.uk/ebank-demo/

Demonstrating potential for linking between data and journal article

Embedded search service at PSIgate

PSIgate subject gateway:service provider

                                                             

Schema for records made available for harvesting• Data holding (collection of files associated with

experiment)• Qualified Dublin Core data elements plus additional chemical

properties – Chemical formula– International Chemical Identifier (InChI)– Compound Class

• Individual data files• Separate records for stage status of each file

• Description set wrapped into one XML record using METS

• Research metadata/data as a complex object

ebank_dc record (XML)

Crystal structure (data holding)

Crystal structure report (HTML)

Dataset

Dataset

Institutional repositories

eBank UK aggregator service

ePrint UK aggregator service

Other aggregators and services

DepositHarvesting OAI-PMH

ebank_dc

Harvesting OAI-PMH oai_dc,ebank_dc

Harvesting OAI-PMH oai_dc

Dataset

dc:identifier

dcterms:references

Linking

dc:type=“CrystalStructure”

Model input Andy Powell, UKOLN.

Eprint oai_dc record (XML)

dcterms:isReferencedBy

dc:type=“Eprint” and/or ”Text”

eBank data model

Eprint “jump-off” page (HTML)

dc:identifierEprint manifestation (e.g. PDF)

Linking

Dep

osit

                                                             

Creating the metadata

• Potential to embed ‘deposit and disseminate’ into workflow of chemist in automated way

                                                             

eBank phase two work areas

• Sub-disciplines of chemistry, earth sciences, engineering

• Pursue generic data model• Use of identifiers for citing datasets• Subject approach to discovering research

data (keywords, classification, ontology)• Access to research data in teaching and

learning context• Liaise with other digital repository initiatives

                                                             

Related UK projects

• National e-Science Centre NESC• NERC Data Grid (Athmospheric and Oceanographic Data

Centres)• JISC Digital Repositories Programme: - Spectra (experim. chemistry, high volume

ingestion) - R4L (lab equipment, metadata generation)

- CLADDIER (citation, identifiers, linking) - StORe (data and publ. repository links) - GRADE (reuse of geospatial data)

                                                             

2. Issues: generic data models, metadata schema & terminology

• Validation against generic schema– CCLRC Scientific Data Model Vs 2

• Complex digital objects and packaging options – METS– MPEG 21 DIDL

• Terminologies– Domain: crystallography– Inter-disciplinary e.g. biomaterials– Metadata enhancement: subject keyword additions to

datasets based on related publications – Meaningful resource discovery?

                                                             

3. Issues: linking

• Links to individual datasets within an experiment• Links to all datasets associated with an experiment or a data

collection• Links to derived eprints and published literature • Context sensitive linking: find me

– Datasets by this author / creator– Datasets related to this subject– Learning objects by this author / creator– Learning objects related to this subject

• Identifiers and persistence– “generic” – domain: International Chemical Identifier (InChI code)

• Resource discovery : Google Scholar?• Provenance: authenticity, authority, integrity?

                                                             

4. Issues: identifiers

• Identifiers and persistence– “generic”: DOI, PURL, Handle, ARK – domain: International Chemical Identifier (InChI)– Resolution; lookup

• Resource discovery : Google Scholar?• Granularity (metadata, linking)?• Provenance: authenticity, authority, integrity?

                                                             

5. Issues: embedding and workflow

• Into the crystallographic publishing community International Union of Crystallography

• Into the chemistry research workflow– SMART TEA Digital Lab Book e-synthesis Lab– Other analytical techniques and instrumentation

• Into the curriculum and e-Learning workflows– MChem course – Undergraduate Chemical Informatics courses

                                                             

For the future…

• Who provides added value services?– Authority files, automated subject indexing,

annotation, data mining, visualisation

• What are the preservation issues?– UK Digital Curation Centre http://www.dcc.ac.uk

– National Science Board Draft report on long-lived data collections http://www.nsf.gov/nsb/meetings/2005/LLDDC_draftreport.pdf

• How to manage complex objects descriptions within OAI ?

• Digital curation of research data presents new roles for scientists, computer scientists, data managers….

                                                             

For later use? In use now (and the future)?

Repositories and digital curation

Data preservation Data curation

Static Dynamic

“maintaining and adding value to a trusted body of digital information for current and future use”

                                                             

Provide value-added services

Annotation

• e-Lab books (Smart Tea Project in chemistry)

• Gene and protein sequences

                                                             

Enable “post-processing” and knowledge extraction

The acquisition of newly-derived information and knowledge from repository content

• Run complex algorithms over primary datasets

• Mining (data, text, structures)

• Modelling (economic, climate, mathematical, biological)

• Analysis (statistical, lexical, pattern matching, gene)

• Presentation (visualisation, rendering)

                                                             

6. Issues: “knowledge services”

• Layered over repositories– Annotation– Mining, modelling, analysis– Visualisation

• Across multiple repositories– Grid enabled applications– Highly distributed, dynamic and collaborative

• Associated with curatorial responsibility– UK Digital Curation Centre

http://www.dcc.ac.uk

                                                             

Issues summary1. Research data is diverse, increasing rapidly in

volume and complexity2. Repository collections are dynamic and evolve3. Technical challenges associated with

interoperability, persistence, provenance, resource discovery and infrastructure provision

4. Embedding in workflow is critical: scholarly communications, research practice, learning

5. Knowledge extraction tools will generate new discoveries based on repository content

6. Repository solutions must scale: M2M processing will become the norm

                                                             

Project homepage:http://www.ukoln.ac.uk/projects/ebank-uk/

Duke, M. et al: Enhancing access to research data: the challenge of crystallography. JCDL 2005.http://www.ukoln.ac.uk/projects/ebank-uk/dissemination/jcdl2005/preprint.pdf

Acknowledgement to all project partners for their contributions to this presentation.