Interleaving Semantics for Multi-Disciplinary Collaborative Design

Abstract

‘Collaboration is an important aspect of the architects' education.' (Kalay, Jeong 2001). The teaching of architectural design is facing with increasing urgency those aspects of the pedagogy related to the collaboration within the learning activity. The legacy of design as problem solving has been to consider collaboration a problem of effective communication where massive amounts of data must be shared among heterogeneous participants. Therefore, achieving interoperability among different CAD systems by way of organizing efficient databases has been the core research issue. The initial effort started with standardizing product descriptions including geometric information and constructing databases to organize them. The underlying theoretical assumption of these efforts is that a building is a product composed of the heterogeneous products. This assumption has been relatively valid and even successfully realized in several related industries, such as the automotive and shipbuilding manufacturing industries. However, the building and construction industry continues to lag behind in this development because constructing a centralized product database has turned out to be not feasible because the shared database quickly becomes too large and unwieldy to support the dynamic process of multi-disciplinary collaborative design. In contrast to the failed centralized database model, we propose to develop a distributed model, where each domain of expertise retains its own data in the form most appropriate for its needs, and where ‘intelligent' filters translate data into and from a neutral data structure. The disciplinespecific filters will transform the neutral representations into semantically-rich ones, as needed by their domains of expertise. Conversely, they will translate semantically-rich, domain-specific data into a neutral representation that can be accessed by other domain-specific filters. To the participants, therefore, the data they see will appear semantically rich, even when it was generated by another professional, thereby facilitating a high level of shared understanding. We also develop a computational methodology that will prove that computer-analyzed and generated design suggestions can actually help designers to achieve their goals better and/or faster. It will also let them know ahead of time what will be the implications of their proposed actions, as seen from other participants' points of view. Once the participants contribute their knowledge to the representation, it would be possible that each of them could see the other's point of view. The dynamic and semantically-rich representation would allow incoherent/favorable situations to be highlighted and managed in real time and the participants to make alternatives reflecting their intents more effectively. The impact of a network-based collaborative design transforms a hierarchical/linear partitioned process into a distributed and interleaved one. In the filter medipaper ated communication model, the participating professionals can affect one another bi- or multidirectionally. We propose the filter mediated communication model and its process to reflect the characteristics of multidisciplinary collaborative design without sacrificing human-centered aspects, and to solve real-world collaboration problems by focusing on a semantically rich representational method at three different levels that are mediated by intelligent filters. By fulfilling the discussed tasks, the experts from different disciplines participating in an AEC project are expected to better understand the dynamic process of design, to achieve a high level of shared understanding. and to facilitate the onset and dissemination of creative ideas.