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A performance benchmark over semantic rule checking approaches in construction industry

Abstract : As more and more architectural design and construction data is represented using the Resource Description Framework (RDF) data model, it makes sense to take advantage of the logical basis of RDF and implement a semantic rule checking process as it is currently not available in the architectural design and construction industry. The argument for such a semantic rule checking process has been made a number of times by now. However, there are a number of strategies and approaches that can be followed regarding the realization of such a rule checking process, even when limiting to the use of semantic web technologies. In this article, we compare three reference rule checking approaches that have been reported earlier for semantic rule checking in the domain of architecture, engineering and construction (AEC). Each of these approaches has its advantages and disadvantages. A criterion that is tremendously important to allow adoption and uptake of such semantic rule checking approaches, is performance. Hence, this article provides an overview of our collaborative test results in order to obtain a performance benchmark for these approaches. In addition to the benchmark, a documentation of the actual rule checking approaches is discussed. Furthermore, we give an indication of the main features and decisions that impact performance for each of these three approaches, so that system developers in the construction industry can make an informed choice when deciding for one of the documented rule checking approaches.
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Contributeur : LE2I - université de Bourgogne Connectez-vous pour contacter le contributeur
Soumis le : mercredi 19 juillet 2017 - 12:30:26
Dernière modification le : vendredi 30 septembre 2022 - 04:16:07

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Pieter Pauwels, Tarcisio Mendes de Farias, Chi Zhang, Ana Roxin, Jakob Beetz, et al.. A performance benchmark over semantic rule checking approaches in construction industry. Advanced Engineering Informatics, 2017, 33, pp.68 - 88. ⟨10.1016/j.aei.2017.05.001⟩. ⟨hal-01564987⟩



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