Post on 18-Dec-2015
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 & profile
3
cop
yri
ght
© 2
01
0 S
ean D
reili
ng
er.
R
ep
rod
uce
d u
nd
er
Cre
ati
ve C
om
mons
license
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
4
Review of Data Management
Questionnaire and interviews
Figure 12. Where do you store your current data? - please tick all that apply
6
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
7
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
8
• Large data stores are unstructured
• Large data stores not shared
• Structured data stores are difficult to adopt
• Structured data stores tend to be task-specific
• Coherent approach to data storage & management needed
Data Management Infrastructure
9
accessibility
manageabili
ty
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
10
AIDA benchmarking, crowdsourcing and launch workshop useful additional
tools
AIDA benchmarking, crowdsourcing and launch workshop useful additional
tools
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
12
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
13
Pilot Projects
Metadata Framework
15
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
http://dl.dropbox.com/u/3404785/microsoft/Pivot%20in%20SP%20-%20HD.mp417
Federated Data Repositories• Repositories
– Institutional
– Discipline
• Link publications to data in different repositories
• Materials Data Centre
– EP2DC
18
www.materialsdatacentre.com
Demo
19
Business planning
Business Plan• Strategy
• Principles
• Policy
• Infrastructure and services
• Business model
Evolving data partnership approach
21
Final Deliverables• Data management framework
• Business Plan
• One-stop shop for data management
• Data management pilots
– Archaeology, nano-fabrication, meta-search
• Training courses and material
• Final report – blueprint document
22
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
23
• www.southamptondata.org
• ktakeda@soton.ac.uk
Expertise
• Fiona Nichols, Pam Wake, Michael Whitton (Library)
• Steve Patterson, Mark Scott (iSolutions)
• Hembo Pagi (Archaeology)
• Richard Boardman, Steven Johnston, Simon Cox, Philippa Reed, Ian Sinclair, Tim Austin, Khalid Abdulbagi (Engineering Sciences)
• Mark Schueler, Niruwan Turnbull (Electronics and Computer Science
24