CubeViz: The RDF DataCube Browser.

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CubeViz is a facetted browser for statistical data utilizing the RDF Data Cube vocabulary which is the state-of-the-art in representing statistical data in RDF. This vocabulary is compatible with SDMX and increasingly being adopted. Based on the vocabulary and the encoded Data Cube, CubeViz is generating a facetted browsing widget that can be used to filter interactively observations to be visualized in charts. Based on the selected structure, CubeViz offer beneficiary chart types and options which can be selected by users.

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In order to hide the complexity of the RDF Data Cube vocabulary from users and to facilitate the browsing and exploration of DataCubes we developed the RDF DataCube browser CubeViz. CubeViz can be divided into two parts, both developed as an extension of OntoWiki:

  1. Faceted data selection component, which queries the structural part of a selected RDF graph containing DataCube resources.
  2. Chart visualization component, which queries observations (selected by the faceted selection component) and visualize them with suitable charts.

CubeViz renders facets according to the DataCube vocabulary to select data on the first component, using SPARQL as the query language. Currently, the following facets are available:

  1. Selection of a DataCube DataSet
  2. Selection of a DataCube Slice
  3. Selection of a specific measure and attribute (unit) property encoded in the respective DataCube dataset.
  4. Selection of a set of dimension elements that are part of the dimensions encoded in the respective DataCube data set

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News

DL-Learner 1.1 (Supervised Structured Machine Learning Framework) Released ( 2015-07-22T16:14:57+02:00 by Dr. Jens Lehmann)

2015-07-22T16:14:57+02:00 by Dr. Jens Lehmann

Dear all, we are happy to announce DL-Learner 1.1. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.1 (Supervised Structured Machine Learning Framework) Released"

AKSW Colloquium, 20-07-2015, Enterprise Linked Data Networks ( 2015-07-16T11:20:08+02:00 by Marvin Frommhold)

2015-07-16T11:20:08+02:00 by Marvin Frommhold

Enterprise Linked Data Networks (PhD progress report) by Marvin Frommhold The topic of the thesis is the scientific utilization of the LUCID research project, in particular the LUCID Endpoint Prototype. Read more about "AKSW Colloquium, 20-07-2015, Enterprise Linked Data Networks"

AKSW Colloquium, 13-07-2015 ( 2015-07-13T12:06:56+02:00 by Philipp Frischmuth)

2015-07-13T12:06:56+02:00 by Philipp Frischmuth

Philipp Frischmuth will give a brief presentation regarding the current state of his PhD thesis and Lukas Eipert will present the topic of his upcoming internship: As part of an internship at eccenca a configurable graphical RDF editor will be … Continue reading → Read more about "AKSW Colloquium, 13-07-2015"

AKSW Colloquium, 22-06-2015, Concept Expansion Using Web Tables, Mining entities from the Web, Linked Data Stack ( 2015-06-22T12:11:56+02:00 by Mohamed Sherif)

2015-06-22T12:11:56+02:00 by Mohamed Sherif

Concept Expansion Using Web Tables by Chi Wang, Kaushik Chakrabarti, Yeye He,Kris Ganjam, Zhimin Chen, Philip A. Bernstein (WWW’2015), presented by Ivan Ermilov: Abstract. Read more about "AKSW Colloquium, 22-06-2015, Concept Expansion Using Web Tables, Mining entities from the Web, Linked Data Stack"

AKSW Colloquium, 15-06-2015, Caching for Link Discovery ( 2015-06-12T23:33:25+02:00 TommasoSoru)

2015-06-12T23:33:25+02:00 TommasoSoru

Using Caching for Local Link Discovery on Large Data Sets [PDF] by Mofeed Hassan Engineering the Data Web in the Big Data era demands the development of time- and space-efficient solutions for covering the lifecycle of Linked Data. Read more about "AKSW Colloquium, 15-06-2015, Caching for Link Discovery"