e-Infrastructure for Large-Scale Social Simulation

1. e-Infrastructure for Large-Scale Social Simulation Mark Birkin Andy Turner

2. Simulation Infrastructure • Background • Features • Capabilities • Current developments, plans and priorities

3. Background • Aim: • Exploring the extent to which it is possible to develop robust representations (models) of cities and regions: • - as they are • - as they will be • - as they could be

4. Background • Objectives • Realistic representations of cities • Medium-term projections • Changing behaviours and activity patterns Service utilisation Resource planning Scenario-based forecasting • Technology interfaces

5. Background • The Population Reconstruction Model (PRM) Deprivation in Leeds, 2001

6. Background • The Dynamic Model: Elderly Population 2031 2001

7. Background • The Scenario Model: Air Quality 2001 2031 Traffic Intensity * 2015 * Traffic Intensity=Traffic load/Road capacity

8. Background Population and average speed changes in Leeds from 2001 to 2031

9. Features (1) • A formidable requirement for processing and storage: • PRM takes anything from several minutes to several days depending on the choice of algorithm and spatial extent • a typical set of forecasts • 800,000 individuals • 30 characteristics • 30 time periods • 20 scenarios • now duplicate for the ‘other’ 58 million!

10. Features (2) • An array of data sources which are potentially distributed: • Small Area Statistics • Sample of Anonymised Records • Special Migration Statistics • ONS Vital Statistics • BHPS • General Household Survey • Health Survey for England • Map boundaries and other spatial datasets • and so on...

11. Features (3) • Requires a capability for interrogation of data/ models/ scenarios and visualisation of the resulting outputs: Map Chart Table Report

12. Features • Architecture

13. Features • Service-Oriented Architecture

14. Capabilities

17. Dynamic Spatial Microsimulation

18. e-Social Science

19. Reports

20. Plans and Prospects • National e-Infrastructure for Spatial Simulation (NeISS) • 1/4/09-31/3/12, 18 man years, £2 million budget • JISC Information Environment Programme: • “Developing e-Infrastructure to support research disciplines” • - production-level simulation tools and services • - social simulation exemplars • - integration of tools and respositories • - establish standards and frameworks • - work with stakeholders: raise awareness, build capacity, provide new services

28. Current Plans

29. WP - Simulation

30. WP - Composition

31. WP - Architecture

32. WP - Deployment

33. Plug-and-play architecture? Workflow Research Object Portlet

34. NeISS: Letters of Support • Partners: Leeds, Manchester, Southampton, UCL, Glasgow, STFC, Stirling • E-Infrastructure service providers and stakeholders: NGS; NeSC; CCSR; Mimas; ESRC; UKRDS; Census Programme; UKOLN; EGI • User community: NCRM; Autodesk; Demographic Decisions; COMPASS; CGS; Newcastle School of Civil Engineering and Geosciences; Agriculture and Agri-food Canada; Liverpool School of Geography; Reading School of Systems Engineering; Royal Town Planning Institute; Macaulay Institute; AGI; EUAsiaGrid

35. NeISS Community • Three tiers: • end-users (naïve) • research users (sophisticated) • contributors (“power users”) • Lifecycle model?

36. Questions • What other simulations can we add to the portfolio? • Is it possible to build a community of both users and developers for social simulation? • What additional functions and services can be provided to support a social services infrastructure? • What are key datasets for the simulation community? • How important is computational grunt as a constraint? Are there other bottlenecks to simulation modelling which might be overcome through an e-infrastructure?

37. Conclusions • NCeSS programme has introduced a platform and elements for the establishment of a research infrastructure for social simulation • NeISS project will provide the resources to implement a ‘production level’ version of these technologies • The project will stand or fall by its ability to engage with the social simulation research community • - your support is crucially important!!

38. References • Birkin M, Townend P, Turner A, Wu B, Xu J (2007) An Architecture for Social Simulation Models to Support Spatial Planning • http://www.ncess.ac.uk/events/conference/2007/papers/paper214.pdf • (Social Science Computing Review, in press). • Townend P, Xu J, Birkin M, Turner A, Wu B (2008) Modelling and Simulation for e-Social Science Through the Use of Service-Orientation and Web 2.0 Technologies • http://www.ncess.ac.uk/events/conference/programme/workshop1/?ref=/programme/fri/4ctownend.htm • (Philosophical Transactions of the Royal Society, in press)