Prediction of domain behaviour through dynamic well-being domain model analysis

Research output: Contribution to journalArticle

Abstract

As the concept of context-awareness is becoming more popular, the demand for improved quality of context-aware systems increases too. Due to the inherent challenges posed by context-awareness, it is harder to predict what the behavior of the systems and their context will be once provided to the end-user than is the case for non-context-aware systems. A domain where such upfront knowledge is highly important is that of well-being. In this paper, we introduce a method to model the well-being domain and to predict the effects the system will have on its context when implemented. This analysis can be performed at design time. Using these predictions, the design can be fine-tuned to increase the chance that systems will have the desired effect. The method has been tested using three existing well-being applications. For these applications, domain models were created in the Dynamic Well-being Domain Model language. This language allows for causal reasoning over the application domain. The models created were used to perform the analysis and behavior prediction. The analysis results were compared to existing application end-user evaluation studies. Results showed that our analysis could accurately predict success and possible problems in the focus of the systems, although certain limitations regarding the predictions should be kept into consideration.
LanguageUndefined
Pages11
Number of pages11
JournalScientific world journal
Volume2015
DOIs
StatePublished - 2015

Keywords

  • EWI-25973
  • SCS-Services
  • Well being
  • IR-96932
  • Impact analysis
  • Domain model
  • METIS-312578
  • Context-aware system

Cite this

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title = "Prediction of domain behaviour through dynamic well-being domain model analysis",
abstract = "As the concept of context-awareness is becoming more popular, the demand for improved quality of context-aware systems increases too. Due to the inherent challenges posed by context-awareness, it is harder to predict what the behavior of the systems and their context will be once provided to the end-user than is the case for non-context-aware systems. A domain where such upfront knowledge is highly important is that of well-being. In this paper, we introduce a method to model the well-being domain and to predict the effects the system will have on its context when implemented. This analysis can be performed at design time. Using these predictions, the design can be fine-tuned to increase the chance that systems will have the desired effect. The method has been tested using three existing well-being applications. For these applications, domain models were created in the Dynamic Well-being Domain Model language. This language allows for causal reasoning over the application domain. The models created were used to perform the analysis and behavior prediction. The analysis results were compared to existing application end-user evaluation studies. Results showed that our analysis could accurately predict success and possible problems in the focus of the systems, although certain limitations regarding the predictions should be kept into consideration.",
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author = "S. Bosems and {van Sinderen}, {Marten J.}",
note = "Open Access",
year = "2015",
doi = "10.1155/2015/931931",
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volume = "2015",
pages = "11",
journal = "Scientific world journal",
issn = "2356-6140",
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Prediction of domain behaviour through dynamic well-being domain model analysis. / Bosems, S.; van Sinderen, Marten J.

In: Scientific world journal, Vol. 2015, 2015, p. 11.

Research output: Contribution to journalArticle

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