Building a generic data structure that handles building related data at an urban scale offers certain challenges. Real world entities must be captured in an environment that allows for the communication of relevant data. This thesis deals with the development of an urban monitoring and simulation framework to investigate building performance and energy demand on a larger scale. An effort is described that aims to enhance a well tested building monitoring system to handle building data at an urban scale. This requires the development of a distributed, generic and enhanceable data store, as well as the conceptualization of a modular and scalable application architecture. The scalable data store is introduced, as well as the modularization process of the application logic, including data handling and communication routines. Beside handling monitoring data, the potential that open government GIS-data offers for the proposed toolkit is investigated. Two-dimensional GIS-data is used to derive simplified geometric building models that can be used to calculate standardized building energy demands. A method that utilizes this geographic building models to automatically assess the respective energy demands according to the ISO 13790:2008 standard is introduced. Beside the calculated energy demands, a building product ontology is introduced that is used to calculate retrofit scenarios for the respective buildings. A prototypical implementation shows how the toolkit can be used based on the example of approximately 900 buildings in Vienna. The building model generation process, an implementation of the proposed energy demand assessment method, and the retrofit calculation method are discussed in detail.