Abstract. Computerized maintenance management systems (CMMS) aim to assist administration and maintenance agents in their asset maintenance tasks (e.g., building, network, air conditioning, faucets maintenance). In this context, geospatial data can help to have a better understanding of the assets they represent by providing additional information: spatial, thematic, temporal, or inter-object relationships. Using such information often leads to interoperability issues as different domains describe them with different data models, like Building Information Modeling (using the Industry Foundation Classes format) and Geographic Information System (using the CityGML format). Spatial information, and particularly 2D or 3D geometry, are stored using heterogeneous representations (e.g., triangle soup, boundary representation, sweep volume, composite solids). Visualization and navigation in the information provided by multiple data sources remain a problem, as there is a need to understand the domains, languages, and models used to describe them. Furthermore, there is a need for solutions to integrate geometric data to manage and visualize existing 2D or 3D representations of assets in geospatial data stores while being able to retrieve additional information using semantic data stores. We propose, in this paper, a methodology to integrate heterogeneous geospatial data in the same viewer by transforming geometric data to a standardized format while keeping a link to sources, in order to navigate in the context of an asset by visualizing its spatial and thematic information.

With the widespread availability of a large volume of urban data, stakeholders from different domains require advanced tools to manage, visualize and understand cities and their evolution. During the last few years, researchers have proposed numerous research works and applications to illustrate the cities of the past and possible scenarios of the future under different conditions. However, many of these approaches are one‐time solutions and not based on standards, making them obsolete and unusable for reproducible research. In this article, we present UD‐SV: an Urban data‐Services and Visualization open‐source framework for multidisciplinary research to handle complex processing, analysis, and visualization of urban data. However, our goal is not to present a one‐time monolithic software solution for urban data management and analysis, but we demonstrate the design and development of an open and interoperable software framework driven by use cases from diverse users to solve applied research challenges. The main contribution of UD‐SV is that it uses open standards and open data with documented and reproducible processes with a particular emphasis on the reuse of existing open‐source software components. We also show an enhanced use of standards to enable a shift toward components that are interchangeable or composable with other existing components in the GIS community.