Abstract
In the practice of building models, we have encountered a number of methodological areas that need to be addressed in order to make the modelling process more robust, scalable, maintainable and transparent. In the context of modelling socio-technical systems (existing infrastructures and businesses) models are primarily data-driven: they contain heterogeneous agents, numerous assumptions and facts about agents and their environment. The data (the facts and assumptions used in the models) span multiple disciplines and are contributed by multiple domain experts. The focus of this chapter is to present new options for improving the management of model data. The issue of data management will be addressed at two levels: that of researchers who need to collaborate when creating and maintaining the model data, and that of data management within a simulation model. The methods proposed in this chapter rely on the use of Semantic Web technologies and philosophies to address data management issues. It is the goal of Semantic Web to make data understandable and useful for both machines and humans. In this chapter we will discuss the complications of modelling socio-technical systems and suggest uses of Semantic Web technologies to aid both collaboration between the modellers and knowledge management for the agents.
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Notes
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Protege 4 does not support SPARQL.
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Within a namespace http://shareddata/. AÂ namespace is an abstract container or environment created to hold a logical grouping of unique identifiers or symbols (i.e. names), see http://en.wikipedia.org/wiki/Namespace_(computer_science).
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Chmieliauskas, A., Davis, C.B., Bollinger, L.A. (2013). Next Steps in Modelling Socio-technical Systems: Towards Collaborative Modelling. In: van Dam, K., Nikolic, I., Lukszo, Z. (eds) Agent-Based Modelling of Socio-Technical Systems. Agent-Based Social Systems, vol 9. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4933-7_9
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