1. Community Capability Model for Data-Intensive Research Project Overview
Kenji Takeda
Microsoft Research
Liz Lyon, Monica Duke, Alex Ball, Michael Day, Manjula Patel
UKOLN, University of Bath

2. A Tidal Wave of Scientific Data

3. “Data sets are becoming the new instruments of science”
Dan Atkins, University of Michigan

4. — Douglas Kell, University of Manchester
“One of the greatest challenges for 21st-century science is how we respond to this new era of data-intensive science. This is recognized as a new paradigm beyond experimental and theoretical research and computer simulations of natural phenomena—one that requires new tools, techniques, and ways of working.”
— Douglas Kell, University of Manchester

5. All Scientific Data Online
Many disciplines overlap and use data from other sciences.
Internet can unify all literature and data
Go from literature to computation to data back to literature.
Information at your fingertips –
For everyone, everywhere
Increase Scientific Information
Velocity
Huge increase in Science Productivity
Literature
Derived and recombined data
Raw Data
(From Jim Gray’s last talk)

6. Data-intensive Science
Acquisition & modelling
Collaboration and visualisation
Analysis & data mining
Dissemination & sharing
Archiving and preserving
Tagging to hide QA as part of publication and sign-off prior to dissemination

8. Medical Analogy Symptoms Diagnosis Action
Idea developed with Dave de Roure

9. What are we trying to achieve?
Understand disciplinary and community diversity in data-driven research (consult)
Unpack the “readiness” concept : identify and deconstruct “capability” factors (scope)
Explore components and metrics for the capability factors / parameters (describe)
Develop a Community Capability Model Framework (model, visualise)
Produce domain mini case studies and business usage cases (validate)

10. Application, value, benefits
Research Stakeholders
PIs, research groups, departments
Higher education institutions
Research funding agencies
Industry, business & innovation partners
Gap analysis and dependencies
Inform planning and assist decision-making
Validate funding allocations
Maximise funder investments
Accelerate knowledge transfer between domains and across sectors

11. Community Workshops York: Harvard:
Bristol: 7th International Digital Curation Conference, 5 Dec
Stockholm: 7th IEEE eScience Conference, 5 Dec
Australia: 10 February 2012, Monash University
Washington DC: 2012 (TBC)

12. Definitions Capability Maturity Behaviours
“power or ability to do something, capacity to be used or developed, a facility”
“fully grown, fully-developed”
“mass adoption & shared usage, community consensus & trust, advanced development & exploitation, embedded skills”

13. Defining a Model View as a Capability Spectrum?
Norms? Extremes? Trends?
Components? Taxonomy? Visualisations?
Indicators, benchmarks, metrics?
D-Kuru from Wikimedia Commons

14. Existing Models

15. Metrics and measures (describe)

16. Metrics and measures (describe)

18. Metrics and measures (describe)

19. Exemplar

20. Draft Model Framework

21. Community Capability Model Framework
Independent working  Collaborative working
Closed research  Open research
Standardisation
Information and communications technology
Legal and ethical issues
Economic and business issues
Data sharing in the cloud, with annotations to facilitate discovery and reuse
Sample and manipulate extremely large data collections in the cloud
Top data analytics algorithms, through Excel ribbon running on Azure
Invoke models, perform analytics and visualization
Machine learning over large data sets to discover correlations
Publish data collections and visualizations to the cloud to share insights
Academic issues
Skills and training

22. Parameters / factors (scope)

23. Parameters / factors (scope)

24. Parameters / factors (scope)

25. Parameters / factors (scope)
Discussion for Panel Session

26. Parameters / factors (scope)

27. Parameters / factors (scope)

28. Visualisation
Synergy with other approaches

29. We need your help! Groupings, gaps and metrics?
How can the model help you?

30. Community Capability Model for Data-Intensive Research Panel Session
Alex Wade
Microsoft Research

31. Guest Speakers
Graeme Earl
Dave De Roure

32. Developing a Model
If you were trying to improve the capability for, and amount of, data-intensive research in your group or institution….
What would be the most useful things a model could provide?

33. Community Capability Model for Data-Intensive Research: Group Discussion Session

35. Medical Analogy Symptoms Diagnosis Action
Idea developed with Dave de Roure

36. What are we trying to achieve?
Understand disciplinary and community diversity in data-driven research (consult)
Unpack the “readiness” concept : identify and deconstruct “capability” factors (scope)
Explore components and metrics for the capability factors / parameters (describe)
Develop a Community Capability Model Framework (model, visualise)
Produce domain mini case studies and business usage cases (validate)

37. Visualisation
Synergy with other approaches

38. ”People want more guidance at the start of their project – there is a black hole in this area.”
“People make do with what they can find – this may not be best practice”
“not very well signposted even in support departments”
“There are skills barriers but not particularly high – researchers are quite trainable.”
“not sure we give them enough technical support to store & organise their data”
“Researchers can hire cloud time but they don’t know what to do with it yet.”

39. Developing a Model
If you were trying to improve the capability for, and amount of, data-intensive research in your group or institution….
What would be the most useful things a model could provide?

40. What would be the most useful things a model could provide?
Human
Economic
Technical
Rewards
Incentives
Legal/ethical issues
Collaborative working
Closed/open research
Skills & training
Startup funding
Operational costs
Transactional costs
Sustainability
ICT
Platforms
Access
Exposure
Standards
Data-intensive research 42
Microsoft Confidential
Microsoft Confidential

41. What is holding research back?
Human
Economic
Technical
Rewards
Incentives
Legal/ethical issues
Collaborative working
Closed/open research
Skills & training
Startup funding
Operational costs
Transactional costs
Sustainability
ICT
Platforms
Access
Exposure
Standards
Data-intensive research 43
Microsoft Confidential
Microsoft Confidential

42. What would be the most useful things a model could provide?
Rewards/incentives
Good for teaching (e.g. UCI)
Define tenure – is data
Metrics of success
Collaborative research drives data sharing – in order to be invited/stay on teams
Modellers vs experimentors
Consumers vs producers
Peer-review for data?
Skills and training
Look at what grad students an postdocs are doing?
Legal & ethical
Not sharing copyright material
Send analysis to the data
Medical data
Human
Rewards
Incentives
Legal/ethical issues
Collaborative working
Closed/open research
Skills & training
Impact metric

43. What would be the most useful things a model could provide?
Economic
Startup funding
Operational costs
Transactional costs
Sustainability
How to provide analytics against data stored at an institution
e.g. who pays for the processing
Cost model
Transparent pricing
How do you make RoI

44. What would be the most useful things a model could provide?
Technical
ICT
Platforms
Access
Exposure
Standards
Agreed practice NOT standards!
Discipline semantics
Interop and fragmentation
Exposing services to the web
e.g. clusters
Bandwidth issues
Disconnect between secondary use

45. Case Studies Exemplars of shared data success stories Archaeology
Hydrology
Chemistry
Music – data for testing algorithms
Million song dataset – giving away features
Oceanography
Ecology
Astronomy
Philologists
Group of communities
Hathi Trust
Digging into Data Challenges

46. Parameters / factors (scope)
What metrics/axes could be used to describe capability in each area?

47. Methods & tools

48. Data Management

49. Communication & collaboration

50. Community Capability Model for Data-Intensive Research
Kenji Takeda
Microsoft Research

51. Summary Community Capability Model for
Researchers
Institutions
Funders
Provide insight into data-intensive research

52. Next steps
2012 Prepare White Paper describing the CCM Framework for consultation
Develop case studies (PIs, institutions, funding agencies) and business case
Australia and Washington DC workshops: (validate) - test the strawman Framework
Kenji Takeda –
Liz Lyon –