Visual Exploration of RDF Data
We have developed and implemented [1,2] infrastructure and RDF storage for the Semantic Web. When we filled it with data the need for some tool that could explore the data became evident. Unfortunately, none of existing solutions fulfills requirements imp
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1 Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic [email protected] Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia [email protected]
Abstract. We have developed and implemented [1,2] infrastructure and RDF storage for the Semantic Web. When we filled it with data the need for some tool that could explore the data became evident. Unfortunately, none of existing solutions fulfills requirements imposed by the data and users expectations. This paper presents our RDF visualizer that was designed specifically to handle large RDF data by means of incremental navigation. A detailed description of the algorithm is given as well as actual results produced by the visualizer.
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Introduction
The RDF [3] is one of data formats of the Semantic Web. In RDF the information is encoded as a set of statements about resources. These statements may abstractly be viewed as a graph. The data storage for RDF data is at the core of the Semantic Web infrastructure that was created at the Faculty of Mathematics and Physics of the Charles University in Prague [4]. Since its creation a lot of RDF data was loaded into the storage and a query API is available to access the data. However, not knowing the exact structure of the data even programmers using the infrastructure find it difficult to create a meaningful query. We have therefore decided that some kind of visualization tool is definitely necessary to support further development. Working with RDF data brings up several issues. Most important of them is the size of the data. The data can be huge (millions of nodes and edges) and contain nodes with extremely high degree (thousands or even hundreds of thousands). This not only limits the possibilities of drawing the graph but also the acceptable complexity (both time and space) of the drawing algorithm. Traditional graph-based techniques work very well for small graphs. Unfortunately, the difficulty of finding readable layout extremely increases with the size of graph. We have therefore focused on finding an approach that is effective both from complexity and user point of view. One possibility to partially overcome the
This research was supported in part by the National programme of research (Information society project 1ET100300419) and VEGA 1/3106/06.
V. Geffert et al. (Eds.): SOFSEM 2008, LNCS 4910, pp. 672–683, 2008. c Springer-Verlag Berlin Heidelberg 2008
Visual Exploration of RDF Data
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problem with large data is an incremental navigation [5]. We decided to use the incremental navigation enhanced by our novel node merging technique so that we can draw even nodes with large degree. To make the drawing easily readable we proposed a triangle layout algorithm [6,7]. The structure of the paper is as follows. Section 2 gives the overview and comparison of known layout algorithms. It also gives a detailed description of our triangle layout. Implementation issues—including the node merging—are described in Section 3. Closing remarks appear in Secti
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