Son yıllarda, Konum Destekli Hizmetler (KDH - Location Based Services), cep telefonları ve avuç içi bilgisayarları gibi mobil cihazların ekran ve işlemci kapasitesinin gelişmesi ile ön planda yer almıştır. Mobil cihaz kullanıcısının talepleri doğrultusunda anlık konum bilgilerinin ölçülmesi, değerlendirilmesi ve sunumu, tüm gelişmelere rağmen özellikle cep telefonlarındaki kısıtlı donanım yapılandırması sebebiyle çözüm gerektiren bir konudur. GPS ve diğer özel algılayıcıların günlük hayatımıza girmesi ile bilgisayarlar tarafından insan davranışlarının belirli düzeyde tespit olanağı sağlanmıştır. Bu da uygun modellemeler ile durum duyarlı uygulamalara imkân vermektedir. İnsan-bilgisayar ilişkisi çerçevesinde bilgisayarların insan dilini anlayamaması birçok konuda sorun yaratmaktaydı. Bu durum bilgisayar bilimlerinde anlamsal (semantik) yaklaşımlar ile aşılmaya çalışılmıştır. Anlamsal bilgisayar dilleri hem insanın hem de makinelerin anlayabileceği bir dil üretmiştir: OWL (Ontology Web Language). Bu dil, varlık felsefesinden doğan “ontoloji” (varlık teorisi) ile, internet dünyasındaki devasal web bilgi yığınını bilgisayarların anlayacağı bir duruma getirmek maksadıyla ortaya konulmuştur. Daha sonrasında tanımsal mantık (description logics) ile desteklenmesi ile durum-duyarlı uygulamalar için neredeyse bir standart halini almıştır. Bu çalışmada çevresel durum duyarlı (context-aware) bir görselleştirme için küme tasarımı ve üretim aşamaları açıklanmaktır. Varlık modelinin oluşturulabilmesi için öncelikle mekânsal veri türlerinin varlıksal tanımları ve birbirleri arasındaki ilişkileri ortaya konmuştur. Çevresel durum duyarlı uygulamaların en önemli gereksinimi tutarlı bir kontext modeldir. Bu modelin tutarlılığı uygulamanın değişik durumlara karşı olan duyarlılık hassasiyetini belirler. Anahtar Kelimeler: Ontoloji, mekansal veri, Konum Destekli Hizmetler (KDH), görselleştirme. Recently, the visualization of spatial data has been gaining importance in ubiquitous computing. In Geoinformatics, such as distributed GIS or Location-Based Services, context models are responsible for the robust communication between the mobile user and the system. "Context" and "context awareness" are the key notions in realisation of the situational information. Context is information characterising the situation of an entity and one of the important entities of the context definition itself is "person". A well-defined context-aware system should fulfil the user's task appropriately. Context-aware systems are a serious consideration in ubiquitous systems and these systems reflect the delicate effect of the designed context. An efficient contextual system needs ontologies. Characteristics of chosen ontology languages determine not only the achievement of the representation of the context but also the capabilities of its reasoning. Ontology Web Language (OWL), an improved version of the DAML+OIL Web Ontology Language, particularly enables description logic support. Description Logics (DLs) allows knowledge representation with concept descriptions and role constructors. OWL-DL is the preferred subset of the OWL to provide reasoning in a well-defined way. To develop a user-adaptive ontological model, users' different situations should be defined properly. In Location-Based Services (LBS), a very intelligent system ignores the effect of user's states and roles except the user's location. Customised visualisation style, however, needs different user profiles in order to provide relevant spatial data. In the computer and cartographic sciences, individual and short-term usage have brought about term of egocentric maps for mobile devices. Design patterns of egocentric maps satisfying user's ego-centre determine visualisation parameters such as centring, redundant encoding, continuous varying of level of details, multiple levels of details, space contraction, single window with details on demand, augmented focusing, orientation gesture and affective emphasis. The aim of this research is to define mobile contextual ontologies (classes and properties) which obey relevance theories so as to define any user's relevant visualisation profile on the mobile devices. The kind of intelligent system proposed here can therefore reason over the complete semantic model of the OWL language by an inference engine. A contextual ontology (OWL-DL) for relevancy has been edited in an ontology editor and knowledge acquisition system. Consequently, the inference engine retrieves criteria for relevant visualisation profiles with its reasoning algorithms or defined SWRL (Semantic Web Rule Language) as a server. In the article, the visual parameter concept has been added to the upper context model to state the visual components of the spatial data as an important part of the system. Data type properties of the visual parameter concept have also been placed on the upper ontology. Subconcepts of the visual parameter have been defined as line and node. The relation between a concept and a subconcept is "is a" relation. Therefore, it can be stated that a line is a visual parameter and a node is a visual parameter. Actually, spatial data can be represented in three main geographic features: point, line and polygon. In the research, the polygon feature has been eliminated while representing spatial data. All polygonal data have been converted to the central point of it because of the limited display size of the mobile devices. Consequently, the visualization has been realized as the line and the node. Egocentric design of a Map-based service which provides relevant visualisation for mobile users is implemented in the campus area of the Istanbul Technical University. Implementation of the service is intended to test consistency of the proposed model for the real user world. A multi-tier technological architecture has been designed that includes spatial database, knowledge base and web map server (WMS). To connect the mobile devices to the servers, a web server and a proxy server have also been set up as in the middleware architecture. GPRS connection, that is the only wireless connection provided by the mobile phone operators, has been used in the research. The UMTS has not been provided yet in Turkey. A GUI that collects information from mobile users has been designed. The architecture has been composed with Java 2EE and Java 2ME programming. To implement the inference procedure the semantic query language (nRQL) has been used. Keywords: Ontology, spatial data, Location-Based Services (LBS), visualisation
