Holistic Benchmarking of Big Linked Data

HOBBIT aims at abolishing the barriers in the adoption and deployment of Big Linked Data by European companies, by means of open benchmarking reports that allow them to assess the fitness of existing solutions for their purposes. These benchmarks are based on data that reflects reality and measures industry-relevant Key Performance Indicators (KPIs) with comparable results using standardized hardware.

Technology Users

Solution Providers

You provide a solution for Linked Data, and you want to assess how good it is.

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Technology Users

Technology Users

Need a Linked Data solutions that fits the best for your requirements?

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Scientific Community

Scientific Community

Working on innovation the Linked Data Lifecycle, you can test your approach.

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HOBBIT JAVA SDK

Summarizing the experience of the successful co-organization of the DEBS Grand Challenge 2017 on the HOBBIT platform, we made one step towards a more lightweight and productive design-development of HOBBIT-related software components. We are happy to announce a standalone software library called the HOBBIT Java SDK. The proposed SDK is targeted to make the design […]

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Ontology Matching (OM 2017)

Since 2004 OAEI organises campaigns aiming at evaluating ontology matching tools and technologies. This year FORTH along with HOBBIT participated in the OAEI 2017 Instance Matching Track and introduced the HOBBIT Link Discovery Track. The Tasks come with two datasets the Sandbox and Mainbox characterized by the number of instances to match (i.e., scale). The […]

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Come and meet the HOBBIT Project @ ISWC-2017

The H2020 project HOBBIT proudly  organises the BLINK 2017 and co-organises the NLIWoD3 at ISWC 2017.  In addition to the workshops, HOBBIT organises the QALD Challenge on Question Answering and participates with the Link Discovery Task at the OAEI Ontology Matching Workshop. We will present all events in the following. The BLINK and NLIWoD3 accepted […]

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Benchmarking Query Answering Systems for Linked Data using HOBBIT Benchmarks

“Alexa, how is the traffic?” This is one of the questions I ask most mornings in my kitchen, while trying to estimate whether I still have the time to complete my slow and painful brain-wake-up sequence or I should rush out, before the roads to work begin to fill up. After the initial excitement, regular […]

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Data Generation in HOBBIT using TomTom’s Mimicking Algorithm

The number of users of navigation services continues to grow, either using the vehicle’s built-in unit, a dedicated device or a smartphone application. This enables the collection of extensive amounts of floating car data, which can be used to extract information relevant to a number of applications like road administration, traffic management and jam avoiding […]

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Generating Big Linked Data for HOBBIT: Mimicking Production Machine and IT Data

With the digitalization in manufacturing and European initiatives like Factory of the Future or national programs like Industrie 4.0 supporting this development, the need for processing big data, coming from sensors, machine logs, Internet of Things (IoT) devices, and other sources is becoming more and more important especially when it comes to bringing added value […]

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Architecture of the HOBBIT Platform

During the runtime of the HOBBIT project, we have collected several requirements from the community which should be fulfilled by a Big Linked Data benchmarking platform. All these requirements influenced the final architecture of our platform. However, this blog post will focus on its central functionality: we want to offer a platform that enables any […]

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Hobbit @ ESWC 2017

The HOBBIT project organized three benchmarking challenges at the ESWC 2017 conference, which took place in Portoroz, Slovenia from May 28th to June 1st, as it aims to bring together and inspire people from academia and industry to come up with fresh and innovative ideas on solving real-life problems concerning Big Linked Data. We are […]

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Hobbit @ DEBS 2017

Using HOBBIT platform at DEBS Grand Challenge considered as major improvement At this year’s Distributed Events Processing Systems conference (DEBS 2017) the HOBBIT platform has demonstrated its ability to objectively quantify the performance of anomaly detection algorithms that process RDF data in real-time. Dr. Roman Katerinenko and Dr. Martin Strohbach, both AGT International were representing […]

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