ber 1993) or a "shared understanding of some domain of interest" (Uschold and Gruninger 1996). Being confronted with the variety of uses of the term ontology I will not add another definition. Instead I find it useful studying what is going on under the label of ontology. The reader will find that even the papers collected in this issue differ in their understanding of ontology. It is up to the authors to define their approach exactly. A synopsis tums out to be stimulating and promising: the work done in ontology and epistemology research is beyond conceptual modeling. The work asks for referential transparency or grounding of models; it makes the commitments to the world beyond the knowledge base itself explicit (Guarino and Poli 1995). It seems to be the only way to link different models with the external world and thus with other models. At a recent conferencel people from different disciplines - philosophy, cognitive science, geography, engineering, mathematics, and computer sci

This paper discusses the ontological status of remote sensing images, from a GIScience perspective. We argue that images have a dual nature---they are fields at the measurement level and fiat objects at the classification level---and that images have an ontological description of their own, distinct and independent from the domain ontology a domain scientist uses. This paper proposes a multi-level ontology for images, combining both field and object approaches and distinguishing between image and user ontologies. The framework developed contributes to the design of a new generation of integrated GISs, since two key benefits are achieved: (1) the support for multiple perspectives for the same image and (2) an emphasis on using images for the detection of spatial-temporal configurations of geographic phenomena.

Abstract. As location-based applications become part of our everyday life, ranging from traffic prediction systems to services over mobile phones providing us with information about our surroundings, the call for more semantics and accurate services is emerging. In this work, we analyze and register the data semantics of Location-based Services (LBS). Initially, we categorize LBS data according to the related concepts and use. We distinguish the (a) Domain Data, including spatial and temporal concepts, namely, position, location, movement and time, (b) Content Data, describing the LBS specific content, and (c) Application Data, consisting of the user profile and the services provided by LBS. Next, we model these three data categories in a way that captures their peculiarities and allows their sharing and exchange among different LBS, when desired. For this, we use semantically rich and expressive models, like UML, as well as the long-praised method of ontologies, realized in the open source, ontology and knowledge-based editor Protégé. To argue about the design choices and show their applicability, we present examples from two characteristic realworld applications, both in the Athens Metropolitan Area: an LBS for tourists carrying mobile devices, and a traffic LBS informing drivers about troublesome situations. 1