MoSeS: Modelling and Simulation for e-Social Science

Townend, Paul; Jie, Xu; Birkin, Mark; Turner, Andy; Wu, Belinda

doi:10.1098/rsta.2009.0041

Cited by 9 publications

(11 citation statements)

References 2 publications

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“…The suitability of social simulation models for massive parallelization has also been demonstrated previously (George et al 1997). Computational support for decision-making with social simulation has been explored through a series of projects funded through the UK e-Social Science programme (Birkin et al 2005;Townend et al 2009).…”

Section: Neiss Motivation and Overviewmentioning

confidence: 99%

Elements of a computational infrastructure for social simulation

Birkin

Procter

Allan

et al. 2010

Phil. Trans. R. Soc. A.

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Applications of simulation modelling in social science domains are varied and increasingly widespread. The effective deployment of simulation models depends on access to diverse datasets, the use of analysis capabilities, the ability to visualize model outcomes and to capture, share and re-use simulations as evidence in research and policymaking. We describe three applications of e-social science that promote social simulation modelling, data management and visualization. An example is outlined in which the three components are brought together in a transport planning context. We discuss opportunities and benefits for the combination of these and other components into an e-infrastructure for social simulation and review recent progress towards the establishment of such an infrastructure.

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Section: Neiss Motivation and Overviewmentioning

confidence: 99%

Elements of a computational infrastructure for social simulation

Birkin

Procter

Allan

et al. 2010

Phil. Trans. R. Soc. A.

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“…The social simulation modelling process can be seen as a 'life cycle' with four essential components: data assembly and integration; model implementation and deployment; interpretation and evaluation of the model results; and publication and preservation of each of these analytical components [6]. The overall objective of the infrastructure is to support this life cycle in either research or policy applications.…”

Section: (B) Components Of the Infrastructurementioning

confidence: 99%

Towards victim-oriented crime modelling in a social science e-infrastructure

Malleson

Birkin

2011

Phil. Trans. R. Soc. A.

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The National e-Infrastructure for Social Simulation (NeISS) is a multi-disciplinary collaboration between computation and social science within the UK Digital Social Research programme. The project aims to develop new tools and services for social scientists and planners to assist in performing 'what-if' scenario predictions in a variety of policy contexts. A key part of the NeISS remit is to explore real-world scenarios and evaluate real policy applications. Research into the processes and drivers behind crime is an important application area that has major implications for both improving crime-related policy and developing effective crime prevention strategies. This paper will discuss how the current e-infrastructure and available microsimulation tools can be used to improve an existing agent-based burglary simulation (BurgdSIM) by including a more realistic representation of the victims of crime. Results show that the model produces different spatial patterns when individual-level victim data are used and a risk profile of the synthetic victims suggests which types of people have the largest burglary risk.

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“…MSM uses population reconstruction and dynamic modelling techniques to synthesize populations for the techniques involved, see Townend et al, 2009. Individual records from the HSAR are reweighted to reproduce known characteristics from the CAS.…”

Section: Initialisationmentioning

confidence: 99%

“…For example, students will be weighted heavily in areas close to the university area while elderly residents will be favoured in retirement towns. A variety of secondary data sources are fed into this process, including vital statistics births and deaths for small areas, household formation and marriage rates, and profiles for both domestic and international migrants (Townend et al, 2009). The microsimulation model used is a component of the Flexible Modelling Framework (FMF) created by Harland and described in Smith, Clarke and Harland (2007).…”

Section: Initialisationmentioning

confidence: 99%