The Basic Formal Ontology as a Reference Framework for Modeling the Evolution of Administrative Units Felix Gantner,* Bettina Waldvogel,* Rolf Meile* and Patrick Laube † *GIS Unit, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland † Department of Geography, University of Zurich, Switzerland Abstract In information systems, ontologies promise advantages such as enhanced interoperability, knowledge sharing, and integration of data sources. In this article, we show that the upper ontology Basic Formal Ontology can facilitate the modeling of an evolution of administrative units. This is demonstrated by creating a spatiotemporal ontology for the administrative units of Switzerland. The ontology tackles the problem that the geometric data is typically captured by taking snapshots at regular intervals while the thematic data is continually updated. The ontology presented merges time-stamped geometries with a formally described history of administrative units, allowing for complex spatiotemporal queries neither standard approach would support. The resulting populated knowledge base was evaluated against a set of spatiotemporal test queries. The evaluation showed that this knowledge base supports a wide range of queries on the evolution of the administrative units of Switzerland between 1960 and 2010. 1 Introduction Ontologies have had significant influence on database design in recent years (Stewart Hornsby and Joshi 2010). They not only provide an effective means to define the basic con- cepts and terms of a model, but also facilitate the integration of different data sources (Agarwal 2005). Unlike domain, task, and application ontologies, upper ontologies define the basic entities that constitute the universe (Guarino 1998). Upper ontologies, such as the Basic Formal Ontology (BFO) (Grenon and Smith 2004), provide a common reference framework for modeling the entities of a domain, and thereby enhance interoperability and knowledge sharing (Noy 2004). At the same time, substantial progress has been made toward temporal GIS (Yuan 2008). Nevertheless, a comprehensive system that offers integrated functions to manage, analyze, and query spatiotemporal data is still lacking. Modeling spatial change has therefore been a con- siderable challenge for decades. In addition to traditional approaches that propose recording a collection of time slices or snapshots, object- and event-oriented models have also been suggested. Address for correspondence: Patrick Laube, GIS Unit, Department of Geography, University of Zurich UZH, Winterthurerstrasse 190, 8057 Zürich, Switzerland. E-mail: patrick.laube@geo.uzh.ch Acknowledgments: The authors sincerely thank Dr. Thomas Scharrenbach for technical advice with regard to Pellet and Virtuoso and Dr. Tomi Kauppinen for providing insights into SAPO. Furthermore, the authors wish to thank PD Dr. Rolf Grütter for his critical thoughts and the Swiss Federal Office for the Environment (FOEN) for funding this research. Finally, they thank three anonymous reviewers for their valuable comments. Research Article Transactions in GIS, 2013, 17(2): 206–226 © 2012 Blackwell Publishing Ltd doi: 10.1111/j.1467-9671.2012.01356.x