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Visual analytics in the web of data

Authors: Paul D. Yoo; Marcello Leida; Kamal Taha Khalifa; Maryam AlShehhi; Benjamin Hirsch;

Visual analytics in the web of data

Abstract

Nowadays the web is composed of huge, complex, and heterogeneous datasets. Making sense of this huge amount of data is challenging. Two emerging technologies developed to solve this issue namely, Linked Data, and Visual Analytics. Linked Data provides structured data over the web. Structured data are understandable by machines therefore smart queries, automated visualization, and linked between different datasets over the web might be possible. On the other hand, Visual Analytics amplify analyst cognitive ability by providing data analysis process enhanced with interactive visualization. In our project, we are aiming to integrate these two technologies to provide a powerful Visual Analytics System.

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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