Overview
GENeSIS: GENerative E-SocIal Science
'Generative social science' is widely regarded as one of the grand challenges of the social sciences. The term was popularised by Epstein and Axtell of the Brookings Institution in the book (1996) Growing Artificial Societies: Social Science from the Bottom Up who define it as simulation that "...allows us to grow social structures in silico demonstrating that certain sets of micro-specifications are sufficient to generate the macro-phenomena of interest". It is consistent with the development of the complexity sciences, with the development of decentralised and distributed agent-based simulation, and with ideas about social and spatial emergence. It requires large-scale data bases for its execution as well as powerful techniques of visualisation for its understanding and dissemination. It provides experimental conditions under which key policy initiatives can be tested on large-scale populations simulated at individual level. It is entirely coincident with the development of e-social science which provides the infrastructure on which such modelling must take place.
The Centre for Advanced Spatial Analysis (CASA) at University College London, and the Centre for Spatial Analysis and Policy (CSAP) at the University of Leeds are collaborating on a proposal to develop this kind of science for the simulation of cities and regions. These two groups have a long history of developing urban and regional models beginning with spatial interaction-allocation models and moving these to aggregate dynamics of urban structure and more recently embracing new approaches at more disaggregate levels which build on microsimulation and agent based modelling. We are proposing to develop a series of demonstrators which will be implemented using e-infrastructures which are emerging from experiments in grid computing and Web 2.0. The interfaces will be highly visual building on CASA's GeoVUE and on CSAP's MoSeS projects which have been funded under ESRC's National Centre for e-Social Science.
People
Professor Michael Batty
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Professor Paul
Longley
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Professor Anthony
Steed
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Professor Alan
Wilson
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Richard Milton
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Dr. Kiril Stanilov
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Outputs
Batty, M. Carvalho, R., Hudson-Smith, A., Milton, R., Duncan Smith, D., and Steadman, P. (2008) Scaling and Allometry in the Building Geometries of Greater London, European Physical Journal B, 63, 303-318.
Batty, M., Hudson-Smith, A., Milton, R. and Crooks, A. (2010) Map Mashups, Web 2.0 and the GIS Revolution, Annals of GIS, 16(1), 1-13.
Hudson-Smith, A., Crooks, A., Gibin, M., Milton, R., and Batty, M. (2009) NeoGeography and Web 2.0: Concepts, Tools and Applications, Journal of Location Based Services, 3, 118-145
Hudson-Smith, A., Crooks, A., Milton, R., and Batty, M. (2009) Mapping for the Masses: Accessing Web 2.0 Through Crowdsourcing, Social Science Computer Review, 27, 4, 524-538.
Lin, H. and Batty, M. (Editors) (2009) Virtual Geographic Environments, Science Press, Beijing, China, vi + 350 pp. (with H. Lin)
Stanilov, K. and Batty, M. (2011) Exploring the Historical Determinants of Urban Growth Patterns through Cellular Automata, Transactions in GIS, 15(3), 253-271
Impact
The GENESIS project merges the activities of two existing nodes in the National Centre for e-Social Science - MoSeS at Leeds University whose objective is to develop microsimulation for social scientists across different spatial scales, their current focus being on simulating population structure and dynamics for all households in the UK, and GeoVUE at UCL whose focus in on the development of visual environments for social science, specifically building on 2D and 3D mapping technologies.
The following general objectives define the impact of the project and these are:
- To develop for the first time in the UK, methods, data and e-infrastructure for generative social science which will include advances in agent-based models and their aggregation across spatial scales.
- To link e-social science to the emerging sciences of complexity, building on developments in agent-based modelling (ABM) and microsimulation.
- To generate new computational platforms integrating desktop, web- and grid-based environments, creating shared Collaboratories for the application of ABM by social scientists in research and policy analysis.
- To exploit, demonstrate, and impress the advances being put in place by ESRC, JISC, and other agencies involving large data sets as under the Census and National Data Sets Strategy programmes.
- To provide capacity through NCeSS for e-social science which is both usable and sustainable for the wider research community.
We realise this vision through:
- A series of generic demonstrators dealing with different sectoral simulations of the urban and regional system from local to national scales, focussing on residential and retail structure and dynamics as a precursor to more comprehensive dynamic urban simulations.
- A series of specific demonstrators focusing upon congestion and crowding at local scales, residential segregation and differentiation at neighbourhood scales, and demographic, life cycle and income effects at more aggregative scales. These will reflect key issues of contemporary social and economic policy in cities and regions.
- A set of interlinked visual environments building on non-proprietary web-based services such as those developed by Google and ESRI, two of our key partners, as well as developments in GIS, multimedia, virtual worlds, and related techniques of visualisation.
- Advances in the dynamics of geodemographics which enable rapid prototyping of new classifications through time related to the various demonstrators that we will develop.
- The NCeSS e-infrastructure platform, specifically through the general portal and specific portlets tailored to enable customisation of our demonstrators.