SEMERGY: Semantic Web Technology Support for Comprehensive Building Design Assessment
FromA . Mahdavi , U . Pont , F . Shayeganfar , N . Ghiassi , A . Anjomshoaa , S . Fenz , J . Heurix , T . Neubauer and A . M . Tjoa: eWork and eBusiness in Architecture, Engineering and Construction, ECPPM 2012, Edited by Gudni Gudnason and Raimar Scherer, CRC Press 2012,Pages 363–370, Print ISBN: 978-0-415-62128-1, eBook ISBN: 978-0-203-07796-2, DOI: 10.1201/b12516-58
Applications for evaluation of alternative building design and retrofit options require a large amount of information (Mahdavi and El-Bellahy 2005). Instances of such information are building components’ cost and technical properties, relevant microclimatic data, applicable codes and standards, as well as available financing and subsidy opportunities. Conventional methods toward collating such information are cumbersome, time-consuming, and errorprone (Pont et al. 2011). This circumstance can deter building professionals from in-depth exploration of the aforementioned design and retrofit options in view of their relative functional, economical, and ecological advantages and disadvantages. Consequently, the decision-making quality and the subsequent performance level of buildings could be negatively affected. Hence, efforts are necessary to support efficient information search and collation processes toward populating building models that would fit into performance evaluation routines and applications. Previous efforts relevant to this problem – such as those related to IFC and IFD frameworks (Buildingsmart 2012) – have partially improved the circumstances. However, to make further progress in this area, the rather ill-structured nature of available design relevant information needs to be taken into account. Specifically, the web undoubtedly contains extensive amount of potentially useful information. This web-based potential remains, however, mostly unexploited, as its extraction is hampered by lack of sufficient structure in the encapsulation and presentation of the information. In this context, semantic web technology (Berners-Lee et al. 2001, Shayeganfar et al. 2008) represents a promising opportunity to improve and expedite the process of information acquisition and collation toward population of design analysis models. The present research represents an effort in this direction.