Geo-content

Abstract: While mobile applications typically offer access to standardized ‘basic’ geo-content, there is evidence in the human sciences that people ac-tually prefer subjective information sources for decision making, e.g. personal stories about experiences by family and friends. The success story of content communities in web applications confirms the wide acceptance of innovative information systems that offer the potential to consume, to produce and to rate personalized data. Therefore in this paper an approach for a mobile, interactive and integrated system is presented that do not only deliver basic geo-referenced information, but also allow the users to create location aware information for themselves and other users: information like hints and personal experience will be geo-referenced, time stamped and annotated with text and keyword information. It is stored and exchanged between community members. This individual information creates information content which is continuously growing and updated. Image based and text based information retrieval in combination with location information are used to provide easy access to relevant information. In this paper we outline the system architecture and components that enable these new approaches also providing augmented reality navigation. The approach was tested in a field test study and results and open issues are given. The system worked well and could be applied to future experiments in order to gain more insight in the mobile users’ behavior in real contexts.

Abstract: The Web is changing the way people share and communicate information because of emergence of various Web technologies, which enable people to contribute information on the Web. User-Generated Geo-Content (UGGC) is a potential resource of geographic information. Due to the different production methods, UGGC often cannot fit in geographic information model. There is a semantic gap between UGGC and formal geographic information. To integrate UGGC into geographic information, this study conducts an ontology-based process to bridge this semantic gap. This ontology-based process includes five steps: Collection, Extraction, Formalization, Mapping, and Deployment. In addition, this study implements this process on Twitter messages, which is relevant to Japan Earthquake disaster. By using this process, we extract disaster relief information from Twitter messages, and develop a knowledge base for GeoSPARQL queries in disaster relief information.