@article{9e2261d01d7143e09204f97e148eca36,
title = "Alternatives for facilitating automatic transformation of BIM data using semantic query languages",
abstract = "In the Architecture Engineering and Construction (AEC) industry, Building Information Model (BIM) authoring tools enable the creation of digital representations of buildings. Each tool implements its own building data model, which makes it difficult to achieve the desired interoperability when building data have to be exchanged with other software (e.g., building energy simulation tools). The representation of BIM models through open standards (e.g., IFC) and Semantic Web technologies can facilitate building data transformation in an automated and flexible way. This is achieved by taking advantage of the logical basis of the Resource Description Framework (RDF) data model and queries created in the Semantic Web query languages. The result is a pragmatic mechanism to transform the data from one data domain to another. This article analyses the potential of Semantic Web query languages to facilitate the data transformation of building data through different alternatives. The first contribution is the identification of fourteen data mapping patterns and three cases of data transformation that enable transforming one data model into another, considering the semantic and structural differences between them. The second contribution is the review and comparison of query languages to carry out the transformations through two different alternatives: using SPARQL-Generate and SPARQL Construct queries. And finally, the third contribution is the definition of a metric to assess the complexity of SPARQL queries.",
keywords = "Benchmark, Data transformation, SPARQL Construct, SPARQL-generate, Semantic web",
author = "G. Costa and A. Sicilia",
note = "Funding Information: Part of the work presented in this paper is based on research conducted within the project “Optimised Energy Efficient Design Platform for Refurbishment at District Level”, which has received funding from the European Union Horizon 2020 Framework Programme (H2020/2014-2020) under grant agreement no 680676. We would like to thank Micol Mattedi from Habitech (Distretto Tecnologico Trentino) for her contribution to providing the BIM models used in this research. Funding Information: Part of the work presented in this paper is based on research conducted within the project “Optimised Energy Efficient Design Platform for Refurbishment at District Level”, which has received funding from the European Union Horizon 2020 Framework Programme (H2020/2014-2020) under grant agreement no 680676 . We would like to thank Micol Mattedi from Habitech (Distretto Tecnologico Trentino) for her contribution to providing the BIM models used in this research. Funding Information: The case study introduced in this section consists in the application of the transformation queries as a part of a communication process developed in the OptEEmAL project, a research project (2015–2019) funded by the European Union Horizon 2020 Framework Programme. Here, the part corresponding to the queries is a piece that is combined with other components to facilitate building energy simulations using BIM models as one of the data sources. Documentation and articles related to other parts of the data transformation process, as well as about the conception of the platform, can be found in [ 38–43 ]. Publisher Copyright: {\textcopyright} 2020 Elsevier B.V.",
year = "2020",
month = dec,
doi = "10.1016/j.autcon.2020.103384",
language = "English",
volume = "120",
journal = "Automation in Construction",
issn = "0926-5805",
publisher = "Elsevier",
}