## 1 Introduction  
With the increasing size and complexity of public buildings or institutions, such as universities, hotels, airports or office buildings, there is also an increasing need for mature indoor location based services (Indoor LBS), such as indoor maps or indoor routing [1]. Both research and economy entities recently became aware of this trend. Global companies such as Google, Navteq or Bing started to extend their well-known outdoor map applications towards indoors [2; 3; 4]; however until now they have mainly focused on the two-dimensional visualization of building representation. For simple indoor map visualization this approach seems to be feasible. In contrast, the visualization of three-dimensional (3D) routes between several floors in a building with a two-dimensional representation can always only provide a brief overview, but not properly visualize vertical parts (_i.e._, transferring from one floor to another) of a route. Essentially, 2D environments have revealed serious limitations when considering multi-level structures [5]. In contrast, a 3D map or model allows a better presentation of the provided information. It has been proven that 3D city models are advantageous for (mobile) navigation [6] and the actual need for 3D information has been elaborated [7]. Widespread outdoor applications and newly developed indoor applications are typically based on commercially provided data, which has been collected by professionals such as surveyors, architects or commercial data providers. However, in most cases this data is proprietary and licensed by the corresponding data provider, thus the development of own applications with such data is limited according to the individual licenses. Also, commercially collected data can be quite expensive to acquire. In contrast, within the last years a new source for geodata, namely crowdsourced geodata or volunteered geographic information (VGI), has evolved. Thereby, a community (normally aiming for some distinct goal) collaboratively collects geodata and provides it in the Internet. That is, VGI can be regarded as a spatially enriched type of user-generated content (UGC), a typical trend of the future Internet [8]. Similar to the UGC phenomenon of the Web 2.0, everybody is able to use VGI for different applications at no charge. Regarding the increasing availability of GPS-enabled devices, such as cameras or smart phones, there is an enormous potential arising from \"_billions of humans acting as remote sensors_\" [9]. Regarding the quality and quantity of the data, several evaluations of OpenStreetMap (OSM, one of the most prominent examples of VGI) have revealed that OSM is, especially in urban areas, able to compete against commercially collected geodata [10; 11; 12]. The usage of OSM data is free and open under the Open Data Commons Open Database License (ODbL). Trying to utilize the power of VGI, researchers have attempted to extend such communities to indoor spaces. Especially for OSM there is a very detailed _IndoorOSM_ mapping proposal available [13], which initially originated from research on the demands and requirements of crowdsourced indoor geodata [14]. The main contribution of this paper is the development of a web-based 3D application, capable of both visualization of building interiors as well as computing and depicting (multi-level) routes inside a building. Essentially, the developed application utilizes existing (and future) HTML standards; the application runs on most modern browsers as well as on some mobile devices. A method for the automatic extraction of building interiors from crowdsourced geodata of OSM is presented, whereby this information can be used for automatically creating XML3D geometries. XML3D is an emerging technology based on the Extensible Markup Language (XML) for the declarative generation of 3 Dcontent in the browser [15]. The route computation itself is based on the Dijkstra algorithm [16], whereas the Open Source implementation _pgrouting_ for PostgreSQL databases has been utilized.