Thesis
Visual language for exploring massive RDF data sets
Washington State University
Master of Science (MS), Washington State University
2010
Handle:
https://hdl.handle.net/2376/107270
Abstract
We demonstrate a novel method for visually exploring and browsing large collections of semistructured data modeled in RDF, a W3C standard for emerging web applications. The method hinges on a theoretical coupling between query language expressivity and structural summaries of data. For standard RDF query languages, this amounts to a bisimulation partitioning of the data. We adapt the classic Kanellakis-Smolka algorithm (KSA) for interactively computing the bisimulation relation, allowing user interaction through a graphical user interface (GUI). The GUI allows users to intuitively filter and structure results, implemented under the hood as a refinement of the underlying bisimulation partition by using KSA. Data is initially presented in the GUI as a single node, representing the totality of the data, and from which the user can iteratively search the data by repeatedly calling a filter or refinement step. The actions on a node cause new nodes to be created, which are connected to the previous node. A new node will contain a subset of the partition from the previous node. Any non-empty node can be used to further refine the search. This paper, will overview our approach and illustrate a current working prototype based on the methodology.
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Details
- Title
- Visual language for exploring massive RDF data sets
- Creators
- Juston Morgan
- Contributors
- Wayne O. Cochran (Degree Supervisor)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University; Pullman, Wash. :
- Identifiers
- 99900525384501842
- Language
- English
- Resource Type
- Thesis