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Vispedia: Interactive Visual Exploration of Wikipedia Data via Search-Based Integration

From: Maged N.K. Boulos <mnkboulos@gmail.com>
Date: Sun, 9 Nov 2008 18:01:46 +0000
Message-ID: <dad227630811091001k3cbbd0e6oa337c3546058e798@mail.gmail.com>
To: public-semweb-lifesci@w3.org
Given the recent interests of some members of this list in Wiki applications
like WikiNeuron and novel information visualization techniques, this paper
might prove useful and inspiring:
Chan B, Wu L, Talbot J, Cammarano M, Hanrahan
P.<http://www.ncbi.nlm.nih.gov/pubmed/18988966?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum>
<http://www.ncbi.nlm.nih.gov/pubmed/18988966?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum>
*Vispedia: Interactive Visual Exploration of Wikipedia Data via Search-Based
Integration*.
*IEEE Trans Vis Comput Graph*. 2008 November-December;14(6):1213-1220.

Stanford University.

Wikipedia is an example of the collaborative, semi-structured data sets
emerging on the Web. These data sets have large, non-uniform schema that
require costly data integration into structured tables before visualization
can begin. We present Vispedia, a Web-based visualization system that
reduces the cost of this data integration.&#xD;Users can browse Wikipedia,
select an interesting data table, then use a search interface to discover,
integrate, and visualize additional columns of data drawn from multiple
Wikipedia articles. This interaction is supported by a fast path search
algorithm over DBpedia, a semantic graph extracted from Wikipedia's
hyperlink structure. Vispedia can also export the augmented data tables
produced for use in traditional visualization systems. We believe that these
techniques begin to address the "long tail" of visualization by allowing a
wider audience to visualize a broader class of data. We evaluated this
system in a first-use formative lab study. Study participants were able to
quickly create effective visualizations for a diverse set of domains,
performing data integration as needed.&#xD;

PMID: 18988966 [PubMed - as supplied by publisher]
Received on Sunday, 9 November 2008 18:02:25 UTC

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