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Explainable artificial intelligence has received limited attention in construction despite its growing importance in various other industrial sectors. In this paper, we provide a narrative review of XAI to raise awareness about its potential in construction. Our review develops a taxonomy of the XAI literature comprising its precepts and approaches. Opportunities for future XAI research focusing on stakeholder desiderata and data and information fusion are identified and discussed. We hope the opportunities we suggest stimulate new lines of inquiry to help alleviate the scepticism and hesitancy toward AI adoption and integration in construction., 56 pages, 3 figures. arXiv admin note: text overlap with arXiv:1910.10045 by other authors

Explainable artificial intelligence is an emerging and evolving concept. Its impact on construction, though yet to be realised, will be profound in the foreseeable future. Still, XAI has received limited attention in construction. As a result, no evaluation frameworks have been propagated to enable construction organisations to understand the what, why, how, and when of XAI. Our paper aims to fill this void by developing a content, context, process, and outcome evaluation framework that can be used to justify the adoption and effective management of XAI. After introducing and describing this novel framework, we discuss its implications for future research. While our novel framework is conceptual, it provides a frame of reference for construction organisations to make headway toward realising XAI business value and benefits., Comment: 43 pages, 5 figures

With the development of Geographic Information System (GIS), the concept of digital city is implemented widely. However, in practice, most of the GIS models are relatively poorly attributed, semantically. Building Information Modeling (BIM) is a process involving the generation and management of digital representations of physical and functional characteristics of building, which is most used in small scale projects. In order to address the target problem of completing the semantic attribution of 3D digital city model, a framework of integrating BIM technology into GIS is demonstrated. A new concept of city information modeling (CIM) is proposed with the goal of bringing great benefits to the urban construction and city management. The composition of city information model is discussed. The data schema behind BIM and GIS (i.e. IFC and CityGML) are compared and mapped with each other. A case study of land planning of campus is demonstrated to present the potential benefits of CIM.