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

Current Team

Publications

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News

AKSW Colloquium, 04-05-2015, Automating RDF Dataset Transformation and Enrichment, Structured Machine Learning in Life Science ( 2015-05-03T21:50:38+02:00 by Mohamed Sherif)

2015-05-03T21:50:38+02:00 by Mohamed Sherif

Automating RDF Dataset Transformation and Enrichment by Mohamed Sherif With the adoption of RDF across several domains, come growing requirements pertaining to the completeness and quality of RDF datasets. Read more about "AKSW Colloquium, 04-05-2015, Automating RDF Dataset Transformation and Enrichment, Structured Machine Learning in Life Science"

AKSW Colloquium, 27-04-2015, Ontotext’s RDF database-as-a-service (DBaaS) via Self-Service Semantic Suite (S4) platform via & Knowledge-Based Trust ( 2015-04-23T17:21:00+02:00 JoergUnbehauen)

2015-04-23T17:21:00+02:00 JoergUnbehauen

This colloquium features two talks. First the Self-Service Semantic Suite (S4) platform is presented by Marin Dimitrov (Ontotext), followed up by Jörg Unbehauens report on Googles effort on using factual correctness as a ranking factor. Read more about "AKSW Colloquium, 27-04-2015, Ontotext’s RDF database-as-a-service (DBaaS) via Self-Service Semantic Suite (S4) platform via & Knowledge-Based Trust"

Talk by Kleanthi Georgala ( 2015-04-22T22:48:27+02:00 by Dr. Amrapali Zaveri)

2015-04-22T22:48:27+02:00 by Dr. Amrapali Zaveri

Last week on Friday, 17th April, Kleanthi Georgala visited AKSW and gave a talk entitled “Traces Through Time: Probabilistic Record Linkage – Medieval and Early Modern”. More information below. Read more about "Talk by Kleanthi Georgala"

SAKE Projekt website goes live ( 2015-04-22T11:50:43+02:00 by Simon Bin)

2015-04-22T11:50:43+02:00 by Simon Bin

Hi all! The project website for the BMWi funded Smart Data Web Project “SAKE” is now on-line at www.sake-projekt.de. Read more about "SAKE Projekt website goes live"

AKSW Colloquium, 20-04-2015, OWL/DL approaches to improve POS tagging ( 2015-04-20T08:21:00+02:00 by Markus Ackermann)

2015-04-20T08:21:00+02:00 by Markus Ackermann

In this colloquium Markus Ackermann will touch on the ‘linguistic gap‘ of recent POS tagging endeavours (as perceived by C. Manning, [1]). Read more about "AKSW Colloquium, 20-04-2015, OWL/DL approaches to improve POS tagging"