RDF data exploration and visualization

Deligiannidis, Leonidas; Kochut, Krys J.; Sheth, Amit P.

doi:10.1145/1317353.1317362

Cited by 46 publications

(35 citation statements)

References 21 publications

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“…There are two main trends in visualizing and navigating RDF datasets [6]: via browsing a labeled oriented graph or displaying RDF properties as browsable facets of a node. The main issue of both approaches is to filter information which is not relevant for the explorative task.…”

Section: Swoc: Semantic Wonder Cloudmentioning

confidence: 99%

Semantic Wonder Cloud: Exploratory Search in DBpedia

Mirizzi

Ragone

Noia

et al. 2010

Current Trends in Web Engineering

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Abstract. Inspired by the Google Wonder Wheel1 , in this paper we present Semantic Wonder Cloud (SWOC): a tool that helps users in knowledge exploration within the DBpedia dataset by adopting a hybrid approach. We describe both the architecture and the user interface. The system exploits not only pure semantic connections in the underlying RDF graph but it mixes the meaning of such information with external non-semantic knowledge sources, such as web search engines and tagging systems. Semantic Wonder Cloud allows the user to explore the relations between resources of knowledge domain via a simple and intuitive graphical interface.

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Section: Swoc: Semantic Wonder Cloudmentioning

confidence: 99%

Semantic Wonder Cloud: Exploratory Search in DBpedia

Mirizzi

Ragone

Noia

et al. 2010

Current Trends in Web Engineering

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“…Much research effort in semantic-based visualization has been spent on finding ways of visualizing complex graphs that derive from the interlinking of semantic data, the relation between different concepts [28], the different granularities [31], and (dis)connections [19]. The result is a large number of ontology-based visualization systems (some are reviewed in [9]). …”

Section: Related Workmentioning

confidence: 99%

Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data

Petrelli

Mazumdar

Dadzie

et al. 2009

Lecture Notes in Computer Science

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Abstract. Semantic formalisms represent content in a uniform way according to ontologies. This enables manipulation and reasoning via automated means (e.g. Semantic Web services), but limits the user's ability to explore the semantic data from a point of view that originates from knowledge representation motivations. We show how, for user consumption, a visualization of semantic data according to some easily graspable dimensions (e.g. space and time) provides effective sense-making of data. In this paper, we look holistically at the interaction between users and semantic data, and propose multiple visualization strategies and dynamic filters to support the exploration of semantic-rich data. We discuss a user evaluation and how interaction challenges could be overcome to create an effective user-centred framework for the visualization and manipulation of semantic data. The approach has been implemented and evaluated on a real company archive.

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“…Despite significant diversity of available visualization tools, only a few of them can be used to visualize large data. Most of the tools display the whole graph [7] or some part of it [10], [2] without using some kind of clusters for adapting the view. There are also visualizers, where we can find some kind of clustering.…”

Section: Related Workmentioning

confidence: 99%

Using Clusters in RDF Visualization

Dokulil

Katreniaková

2009

2009 Third International Conference on Advances in Semantic Processing

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Clustered graph visualization techniques are an easy to understand way of hiding complex parts of a visualized graph when they are not needed by the user. When visualizing RDF, there are several situations where such clusters are defined in a very natural way. Using this techniques, we can give the user optional access to some detailed information without unnecessarily occupying space in the basic view of the data. This paper describes algorithms for clustered visualization used in the Trisolda RDF visualizer. Most notable is the newly added clustered navigation technique.

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RDF data exploration and visualization

Cited by 46 publications

References 21 publications

Semantic Wonder Cloud: Exploratory Search in DBpedia

Semantic Wonder Cloud: Exploratory Search in DBpedia

Multi Visualization and Dynamic Query for Effective Exploration of Semantic Data

Using Clusters in RDF Visualization

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