Workflows for Quantitative Data Analysis in The Social Sciences

The background is given to how statistical analysis is used by quantitative social scientists. Developing statistical analyses requires substantial effort, yet there are important limitations in current practice. This has motivated the authors to create a more systematic and effective methodology with supporting tools. The approach to modelling quantitative data analysis in the social sciences is presented. Analysis scripts are treated abstractly as mathematical functions and concretely as web services. This allows individual scripts to be combined into high-level workflows. A comprehensive set of tools allows workflows to be defined, automatically validated and verified, and automatically implemented. The workflows expose opportunities for parallel execution, can define support for proper fault handling, and can be realised by non-technical users. Services, workflows and datasets can also be readily shared. The approach is illustrated with a realistic case study that analyses occupational position in relation to health

Modelling Realistic User Behaviour in Information Systems Simulations as Fuzzing Aspects

In this paper we contend that the engineering of information systems is hampered by a paucity of tools to tractably model, simulate and predict the impact of realistic user behaviours on the emergent properties of the wider socio-technical system, evidenced by the plethora of case studies of system failure in the literature. We address this gap by presenting a novel approach that models ideal user behaviour as workflows, and introduces irregularities in that behaviour as aspects which fuzz the model. We demonstrate the success of this approach through a case study of software development workflows, showing that the introduction of realistic user behaviour to idealised workflows better simulates outcomes reported in the empirical software engineering literature

Semantic model-driven development of service-centric software architectures

Service-oriented architecture (SOA) is a recent architectural paradigm that has received much attention. The prevalent focus on platforms such as Web services, however, needs to be complemented by appropriate software engineering methods. We propose the model-driven development of service-centric software systems. We present in particular an investigation into the role of enriched semantic modelling for a modeldriven development framework for service-centric software systems. Ontologies as the foundations of semantic modelling and its enhancement through architectural pattern modelling are at the core of the proposed approach. We introduce foundations and discuss the benefits and also the challenges in this context