To achieve energy-efficient design in urban communities, the design phase needs to adopt reliable energy modeling approaches. However, current urban modeling approaches often use abstract and low level information to describe buildings because of the difficulties of collecting and managing building data on the large scale required of such urban communities. This abstraction of building data creates large uncertainties in the modeling and simulation of energy scenarios at the community level. An important part of the solution to this challenge relies on the integration of information systems at the scale of both urban communities and individual buildings, which are based on geographic information system (GIS) and building information modeling (BIM) respectively. Since current technologies do not sufficiently address the interoperability between GIS and BIM, the existing conversion between GIS and BIM does not satisfy the data requirements for community energy design. This paper investigates this challenge and presents an approach that uses semantic web technologies, including web ontology language (OWL) and resource description framework (RDF), to integrate GIS and BIM data. In this approach, we use an extract, transform and load (ETL) tool to convert GIS and BIM data to RDF and conduct queries on the integrated RDF to provide the required information for energy simulation. The approach is tested through a case study of the University of British Columbia campus.