Creating a Time Machine of Future Pasts: Data Integration and Interoperability for Cross-disciplinary Research on Urban Heritage Clusters

Historic clusters of heritage buildings comprise the core of a great number of European cities and represent the fabric based on which today's municipalities have developed historically. The sustainable development of these environments is often threatened by urbanization, gentrification or depopulation phenomena. These urban environments should not be studied and analysed as static formations disconnected from the contemporary fabric of a city, but rather as an assemblage of tangible and intangible assets subjected to dynamic pressures of economic, environmental, and social activities. The value of the historic built environment for local communities, as a tangible result of the cultural heritage of a place, does not only lie in preserving a continuity with past societies, but it can become important in achieving more resilient futures for the city [1]. The cross-disciplinary nature of the pressing challenges posed by said phenomena requires the development of novel data-driven methods [2] for the re-use, regeneration and safeguarding of neglected areas of our cities' existing building stock. Digitisation of the construction industry [3] and urban data analytics [4] offer new opportunities for historic cities that undergo transformations. The presentation will discuss about the methodological and technical framework required for the creation of a platform that will function as a time machine of our cities in the future. A time machine that does not aim only at representing how our cities used to be in the past, but rather one that curates and stores current transformations of our built environment, with the objective to enable dynamic observation of the existing building stock at neighborhood scale in present and future times. In this context, the presentation will be occupied with the significance of bringing the building scale (architectural) data together with neighbourhood scale (environmental) data in the same digital environment to enable deeper and cross-disciplinary insights of built heritage assets' conditions. This data-driven study is enabled by the use of Building Information Modelling (BIM) tools for the common management of multi-scale and multi-discipline datasets generated by the 3D documentation, non-destructive testing and metadata integration of conservation state analyses and historic architecture information of building assets. In this context, the presentation will be occupied with the significance of bringing the building scale (architectural) data together with neighbourhood scale (environmental) data in the same digital environment to enable deeper and cross-disciplinary insights of built heritage assets' conditions. This data-driven study is enabled by the use of Building Information Modelling (BIM) tools for the common management of multi-scale and multi-discipline datasets generated by the 3D documentation, non-destructive testing and metadata integration of conservation state analyses and historic architecture information of building assets. Finally the presentation will offer a description of the requirements for integrating these datasets in online repositories for the open access of the public and relevant stakeholders to spatial data analytics that can be used for territorial planning, energy monitoring, educational purposes and smart historic city applications [5]. This research responds to the need for storing, accessing, analysing, and updating heterogeneous data of heritage buildings, which currently, are found in unstructured data repositories of in scattered, inaccessible databases.