Prediction of Domain Behavior through Dynamic Well-Being Domain Model Analysis
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-...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2015/931931 |
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| _version_ | 1832564109347913728 |
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| author | Steven Bosems Marten van Sinderen |
| author_facet | Steven Bosems Marten van Sinderen |
| author_sort | Steven Bosems |
| collection | DOAJ |
| description | 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 limitation regarding the
predictions should be kept into consideration. |
| format | Article |
| id | doaj-art-20afda4ade4b479d85869b48aa216be1 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-20afda4ade4b479d85869b48aa216be12025-02-03T01:11:42ZengWileyThe Scientific World Journal2356-61401537-744X2015-01-01201510.1155/2015/931931931931Prediction of Domain Behavior through Dynamic Well-Being Domain Model AnalysisSteven Bosems0Marten van Sinderen1Faculty of EEMCS, University of Twente, P.O. Box 217, 7500 AE Enschede, NetherlandsFaculty of EEMCS, University of Twente, P.O. Box 217, 7500 AE Enschede, NetherlandsAs 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 limitation regarding the predictions should be kept into consideration.http://dx.doi.org/10.1155/2015/931931 |
| spellingShingle | Steven Bosems Marten van Sinderen Prediction of Domain Behavior through Dynamic Well-Being Domain Model Analysis The Scientific World Journal |
| title | Prediction of Domain Behavior through Dynamic Well-Being Domain Model Analysis |
| title_full | Prediction of Domain Behavior through Dynamic Well-Being Domain Model Analysis |
| title_fullStr | Prediction of Domain Behavior through Dynamic Well-Being Domain Model Analysis |
| title_full_unstemmed | Prediction of Domain Behavior through Dynamic Well-Being Domain Model Analysis |
| title_short | Prediction of Domain Behavior through Dynamic Well-Being Domain Model Analysis |
| title_sort | prediction of domain behavior through dynamic well being domain model analysis |
| url | http://dx.doi.org/10.1155/2015/931931 |
| work_keys_str_mv | AT stevenbosems predictionofdomainbehaviorthroughdynamicwellbeingdomainmodelanalysis AT martenvansinderen predictionofdomainbehaviorthroughdynamicwellbeingdomainmodelanalysis |