Institutional Data Management Blueprint

Institutional Data Management Blueprint

Kenji Takeda (Engineering Sciences), Mark Brown (University Librarian), Simon Coles (Chemistry), Les Carr (ECS, EPrints), Jeremy Frey (Chemistry), Graeme Earl (Archaeology) Peter Hancock (iSolutions), Wendy White (Library)

Introduction• Why data management?

• IDMB project

• Key findings

• Recommendations

• Business plan

• Conclusions

www.southamptondata.org 2

Data Management @ Southampton• What do we mean?

– Everything• Why do we care?

– Foundation for all of our research• How should it be managed?

– We want to find out from users• How can the University help?

– What do researchers need?• Key outcomes

– Impact & profile3

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IDMB Project Overview• Produce framework for managing research data for

an HEI

• Scope and evaluate a pilot implementation plan for an institution-wide data model

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Policy Best Practice

Pilot Projects

Training &

Workshops

Review of Data Management

Where do you store your data?

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How much electronic data do you currently retain?

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How long do you keep your data for?

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How frequently do you backup your data?

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Where do you backup your data?

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Key Findings• Schools research practice is embedded and unified

• Schools data management capabilities vary widely

• Data management is carried out on an ad-hoc basis in many cases

• Researchers demand for storage is significant

• Researchers resort to their own best efforts in many cases, where central support does not meet their needs

• Users want more support for backup, particularly for large quantities of data

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Key Findings• Researchers want to

keep their data for a long time

• There is a need from researchers to share data, both locally and globally

• Data curation and preservation support needs to be improved

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Gap Analysis• Policy and governance is robust, but is not

communicated to researchers in the most accessible way

• Services and infrastructure are in place, but lack capacity and coherence

• There is a lack of training and guidance on data management

• Lack of coherence and sustainable business model

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Recommendations

Recommendations• Short-term (1 year)

– Develop an institutional data repository– Develop a scalable business model– One-stop shop for data management advice and guidance

• Medium-term (1-3 years)

– Comprehensive and affordable backup service for all– Open research data mandate, and supporting

infrastructure– Research data lifecycle management– Embedding data management training and support

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Long-term recommendations• Provide coherent data

management support across all disciplines

• Embed exemplary data management practice across the institution

• Agile business plan for continual improvement

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Pilot Projects

Archaeology Data Management• Archaeology is all

about data and metadata

• Spectrum of data is huge– Laser scans– Photography– Geophysics– CAD– CGI

• Context is everything

http://www.portusproject.org/

SharePoint 2010 Data Management

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Data Browsing in Context

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Business planning

Business Plan• Strategy

• Principles

• Policy

• Infrastructure and services

• Business model

• Partnership approach between all stakeholders– Senior management,

Researchers, IT, Library, Research & Innovation Services, Finance, Legal 26

Institutional Data Management Policy• Help researchers

– Provide guidance on what is expected

– Provide guidance on how to manage their data

• Help the institution– Define what is

required• Comply with funders

• Provide governance and decision-making process 27

Cost Modelling• Data management is

expensive

• Who is responsible?

• Who pays for it?

• How does it scale?

• What if somebody cannot afford it?

• Not just about hardware

• Sustainability28

Researcher

Cloud Possibilities

Cloud Solutions• Data storage demand growing

at frightening rate

– Users can accommodate this locally very cheaply

– Difficult to satisfy with current server-based storage

• Potential to provide:

– Zero capital cost– Burst capability– Scalability 30

Cloud Benefits

31Diagram courtesy of Dr Steven Johnston

Cloud Issues• Cost models

– Dropbox £8k per TB– Data transfer charges

• Security

• Reliability

– Amazon!

• Legal implications

• Vendor lock-in

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Conclusions

• Good data management is vital for better research

• Two-pronged approach– Bottom-up to

augment researcher’s world

– Top-down to provide support and guidance

• Providing a roadmap for the future – including Cloud

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Researcher

Faculty

University

• www.southamptondata.org

• [email protected]