POI Verilerinin Semantik Tanımlarının Oluşturulması ve Görselleştirilmesi

POI verileri, navigasyon, turizm, sosyal ağ, lojistik, çevrimiçi harita yapımı, arttırılmış gerçeklik, akıllı şehir çözümleri ve konum tabanlı oyunlar gibi birçok alanda kullanılmaktadır. Son yıllarda bu alanlardaki uygulamaların yaygınlaşmasıyla birlikte ilgi çekici nokta verilerinin toplanması ve güncellenmesi için kitle kaynak ve gönüllü coğrafi bilgi girişimleri ile üretilen veri kaynaklarına yönelim artmıştır. Bu veri kaynakları, ilgi çekici nokta verileri açısından zengin ve değerli bir veri kaynağıdır. Ancak bu veri kaynakları farklı şemalara sahiptir ve farklı ayrıntı düzeyinde veriler içermektedir. Bu durum, farklı veri kaynaklarından çıkarılan ilgi çekici nokta verilerinin eşleştirilmesinde veya analiz edilmesinde problemlere neden olmaktadır. Farklı veri kaynaklarındaki ilgi çekici nokta verilerinin kullanılabilmesi, sözdizimsel veya semantik ortak bir şemanın tanımlanmasına bağlıdır. Bu çalışmada farklı veri kaynaklarındaki ilgi çekici nokta verilerinin eşleştirilmesi problemi ele alınmıştır. Bu bağlamda, ilgi çekici nokta verilerinin Semantik Web uygulamalarında kullanılabilirliğini sağlamak amacıyla POI Ontolojisi geliştirilmiştir ve ilgi çekici nokta verilerinin semantik tanımları oluşturulmuştur. İlgi çekici nokta verileri, Karma ara yüzünde ontoloji ile ilişkilendirilmiştir ve RDF veri görselleştirme aracı olan Sextant kullanılarak görselleştirilmiştir.

Generating Semantic Definitions and Visualization of POI Data

Points of interest data is used in several areas such as navigation, tourism, social network, logistics, online mapping, augmented reality, smart city solutions, and location based games. In recent years, with the spread of applications in these areas the tendency to data sources produced by crowd sourced and volunteered geographic information initiatives has increased for the gathering and updating of points of interest data. These data sources are a rich and valuable source of POI data. Nevertheless, these data sources have different schemas and contain data at different levels of detail. This causes problems in matching or analyzing points of interest data extracted from different data sources. Usability of points of interest data from different data sources depends on defining a common syntactic or semantic schema. In this study, the problem of matching points of interest data from different data sources is reviewed. In this context, POI Ontology has been developed to ensure the usability of point of interest data in Semantic Web applications and the semantic definitions of points of interest data have been created. Points of interest data is associated with ontologies in the Karma interface and visualized using Sextant, the RDF data visualization tool.

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