HOBBIT: Holistic Benchmarking of Big Linked Data

HOBBIT is a European project that develops a holistic open-source platform and industry-grade benchmarks for benchmarking big linked data.

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Summary

Big Data is one of the key assets of the future. However, the cost and efforts required for introducing Big Data technology in a value chain is significant. Mastering the creation of value from Big Data will enhance European competitiveness will result in economic growth and jobs and will deliver societal benefit. To facilitate the use of Big Linked Data, the European Union funds a research and innovation project called "HOBBIT". A European consortium, led by the Institute for Applied Informatics (InfAI) e.V., aims to develop a holistic benchmarking platform for big linked data and corresponding industry-grade benchmarks.

Premises

A key step towards abolishing the barriers to the adoption and deployment of Big Data is to provide European companies with open benchmarking reports that allow them to assess the fitness of existing solutions for their purposes. Achieving this goal demands: The deployment of benchmarks on data that reflects reality within realistic settings. The provision of corresponding industry-relevant key performance indicators. The computation of comparable results on standardized hardware.

Goals

HOBBIT aims to address these tasks by means of a strong team composed of leading research institutes, large industry customers and innovative small and medium-sized enterprises. In particular, the consortium will aim to achieve the following goals: Define benchmarks for domains of industrial relevance in Europe that make use of Big Linked Data. Determine the key performance indicators for processing Big Linked Data by collaborating with stakeholders from industry and research. Create an open benchmarking platform to evaluate the performance of state-of-the-art systems on standardized hardware. Organize yearly evaluation campaigns, using the platform and the industry-defined KPIs.

About HOBBIT

HOBBIT is a project within the EU’s "Horizon 2020" framework program and started on December 1st, 2015. The consortium consists of InfAI (coordinator, Germany), Fraunhofer IAIS (Germany), FORTH (Greece), NCSR "Demokritos" (Greece), iMinds (Belgium), USU Software AG (Germany), Ontos AG (Switzerland), OpenLink Software (UK), AGT Group R&D GmbH (Germany) and TomTom (Poland).

  • Duration: 12/2015–11/2018
  • Funding Programme: EU H2020 Research and Innovation Program

Publications

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News

AKSW Colloquium, 23.01.2017, Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction ( 2017-01-20T14:02:35+01:00 by Ivan Ermilov)

2017-01-20T14:02:35+01:00 by Ivan Ermilov

Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction On the upcoming colloquium on 23.01. Read more about "AKSW Colloquium, 23.01.2017, Automatic Mappings of Tables to Knowledge Graphs and Open Table Extraction"

PRESS RELEASE: “HOBBIT so far.” is now available ( 2017-01-09T14:22:29+01:00 by Sandra Bartsch)

2017-01-09T14:22:29+01:00 by Sandra Bartsch

The latest release informs about the conferences our team attended in 2016 as well as about the published blogposts. Read more about "PRESS RELEASE: “HOBBIT so far.” is now available"

4th Big Data Europe Plenary at Leipzig University ( 2016-12-16T14:33:41+01:00 by Sandra Bartsch)

2016-12-16T14:33:41+01:00 by Sandra Bartsch

The meeting, hosted by our partner InfAI e. V., took place on the 14th to the 15th of December at the University of Leipzig. Read more about "4th Big Data Europe Plenary at Leipzig University"

SANSA 0.1 (Semantic Analytics Stack) Released ( 2016-12-09T15:41:04+01:00 by Dr. Jens Lehmann)

2016-12-09T15:41:04+01:00 by Dr. Jens Lehmann

Dear all, The Smart Data Analytics group /AKSW are very happy to announce SANSA 0.1 – the initial release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.1 (Semantic Analytics Stack) Released"

AKSW wins award for Best Resources Paper at ISWC 2016 in Japan ( 2016-12-09T15:05:00+01:00 by Sandra Bartsch)

2016-12-09T15:05:00+01:00 by Sandra Bartsch

Our paper, “LODStats: The Data Web Census Dataset”, won the award for Best Resources Paper at the recent conference in Kobe/Japan, which was the premier international forum for Semantic Web and Linked Data Community. Read more about "AKSW wins award for Best Resources Paper at ISWC 2016 in Japan"