A centre of expertise in digital information management

www.ukoln.ac.uk

UKOLN is supported by:

Changing Roles, Responsibilities and Relationships

Dr Liz Lyon, Director, UKOLN

Associate Director, UK Digital Curation Centre

Opening the research data lifecycle, JISC Conference 2007

This work is licensed under a Creative Commons LicenceAttribution-ShareAlike 2.0

Preliminary findings from a JISC study• Terms of Reference for UKOLNTo define how institutions (collectively and individually) and

scientific data centres can together effectively achieve – Preservation– Access – Managed and open– Re-use – Data citation, data mining and re-interpretation

• October 2006 – March 2007

• N.B. Work in progress!

Some of the data stakeholders?

Funders

• Interviews: 4 Research Councils + 1 charity• Support for data curation is (still) patchy• Mixed approaches: proactive to passive• Gaps in infrastructure support for data outputs• Limited formal links between programme planning and

support infrastructure• Some Data management and sharing policies• Some use of Data Management Plans• Wellcome Trust – Policy + Q&A January 2007

                                                             

A centre of expertise in digital information management

www.ukoln.ac.uk

January 2007

Data Management and Sharing Plan required “if creating or developing a resource for the research community as the primary goal” or “involve the generation of a significant quantity of data that could potentially be shared for added benefit”

Funders 2

• Limited advocacy work

• Funding models for infrastructure support vary

• Funding models for research programmes vary

• Some productive partnerships e.g. MRC and Wellcome Trust, CCLRC and Wellcome

• Some examples of good practice

Hierarchy of drivers (for data sharing) Acknowledgement: Mark Thorley, NERC

• Level 0: deliver project.

• Level 1: meet ‘good scientific practice’.

• Level 2: support own science.

• Level 3: employer’s requirements.

• Level 4: funder’s requirements.

• Level 5: public policy requirements.

NATURALENVIRONMENTRESEARCH COUNCIL

NERC has:

7 designated data centres

Data Management Co-ordinator

DataGrid

MRC developing a data support plan Acknowledgement Alan Sudlow

Data centres & Data services• Interviews with 5 data services• Deep levels of expertise and subject knowledge• Exemplars of good practice: standards, policies, manuals, robust

curation / preservation practice• Limited sharing of expertise between centres• Some effective partnerships:

– AHDS Stormont Papers with Queens Belfast – BADC with CLADDIER Project

• Wide range of community awareness• Use of licences but IPR issues: performing arts, • Technical issues: complexity of data sets, version control, identifiers,

application profiles

Data centres & Data services 2• Exemplar of good practice

– European Bio-informatics Institute – Microarray data to inform gene expression– Consensus on community standards MIAME– Data pipelines at source via Laboratory Information Management

Systems LIMS– User tools MIAMExpress & value-added services– Annotation of data using the Gene Ontology– Submission & deposit is embedded in community culture: requirement for

publication– Training programme, eLearning materials coming– This level of data curation is expensive!!

Reactome

EnsEMBLGenome

Annotation

EMBL-BankDNA sequences

UniProtProtein Sequences

Array-ExpressMicroarray

Expression Data

EMSDMacromolecularStructure Data

IntActProtein Interactions Source: Graham

Cameron, EBI

Flybase

MGD

SGD

BRENDA

Chemicaldata

resources

Medical data resources

Biodiversitydata

resources

IMGT

Pasteur DBs

Eumorphia/Phenotypes

Corebiomolecular

resources

Specialist biomolecular data resource examples

Mutants

Large resources in related disciplines

Model organism resource examples

Mouse AtlasSource: Graham

Cameron, EBI

General Data Selection Criteria• Usability

– Quality of data– Usable data format– Conditions of Use– Reputable Author– Documentation

• Usefulness– Data quality– Uniqueness of data– Potential Strategic Use– Usefulness of parameters

Institutions & Data Repositories

• Not much data…. or duplication …… (yet?)• Departmental audits of research data practice at

University of Southampton to inform developing institutional data & curation policy

• Barriers to data sharing: – IPR and geospatial data– Lack of awareness amongst researchers– Cultural roots and resistance to change

• Exemplars of good practice: eBank Project

Aggregator services

Institutional data repositories

Deposit , Validation

Publication

ValidationData analysis

Search, harvest

Presentation services / portals

Data discovery, linking, citation

Laboratory repository

Deposit

eCrystals ‘Global Federation’ Model

Publishers: peer-review journals, conference proceedings, etc

Curation

Preservation

Subject Repository

Institution Library & Information Services

Data creation & capture in “Smart lab”

Data discovery, linking, citation

Search, harvest

Search, harvest

Deposit

Deposit

Deposit

Roles, Rights & Responsibilities

• ‘Scientist’: Creation and use of data.• ‘Data centre’: Curation of and access to data.

• ‘User’: Use of 3rd party data.

• ‘Funder’: Set / react to public policy drivers.• ‘Publisher’: Maintain integrity of the scientific

record.

Acknowledgement: Mark Thorley, NERCNATURALENVIRONMENTRESEARCH COUNCIL

Closing thoughts

• Co-ordination and join up – High level and strategic : Funders– Operational level and practical : JISC data services

& research council data centres

• Funding– Are current economic models for preservation &

data sharing infrastructure a) appropriate? b) adequate? c) sustainable?

– Should inform prioritisation and investment

Closing thoughts 2

• Good Practice requirements– Data management and sharing Policies– Data Management Plans (peer-reviewed)– Institutional data curation policies & planning

• Technical interoperability and integration– Data are diverse and complex– JISC IIE vision of discovery across repositories– Contextual linking offers opportunity for data centres and

institutional repositories to realise synergies and work more closely together

Closing thoughts 3

• Advocacy – Programmes to reach across sectors– Harmonisation and consistent messages – Tailored & targeted to disciplines– Researcher has some curatorial responsibility

• Training– Lack of skills– eLearning opportunity– Data scientists? Recognition and career development– “Native” data scientists are coming….

“Dealing with the Data Deluge”

• JISC Repositories Programme• Supporting Institutions in the Digital Age• Digital Repositories Conference• 5-6 June 2007• University of Manchester• Research Data Strand