School of Geography CENTRE FOR SPATIAL ANALYSIS AND POLICY e-Infrastructure for Large-Scale Social Simulation Mark Birkin Andy Turner

Simulation Infrastructure  Background  Features  Capabilities  Current developments, plans and priorities

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

Background Objectives 1) Realistic representations of cities 2) Medium-term projections 3) Changing behaviours and activity patterns Service utilisation Resource planning Scenario-based forecasting 4) Technology interfaces

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

Background The Dynamic Model: Elderly Population

Background The Scenario Model: Air Quality * Traffic Intensity=Traffic load/Road capacity Traffic Intensity *

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

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!

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...

Features (3) Requires a capability for interrogation of data/ models/ scenarios and visualisation of the resulting outputs: Map ReportTable Chart

Features Architecture

Features Service-Oriented Architecture

Capabilities

Dynamic Spatial Microsimulation

e-Social Science

Reports

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

Current Plans

WP - Simulation

WP - Composition

WP - Architecture

WP - Deployment

Plug-and-play architecture? Workflow Research Object Portlet

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

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

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?

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!!

References Birkin M, Townend P, Turner A, Wu B, Xu J (2007) An Architecture for Social Simulation Models to Support Spatial Planning (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 (Philosophical Transactions of the Royal Society, in press)