The document discusses the HOBBIT project, which aims to provide holistic benchmarking of big linked data technologies. It notes the large volumes of linked data and number of available technologies. HOBBIT will identify key performance indicators and benchmarks for critical steps in the linked data lifecycle, including generation, analysis, storage, and visualization. It will gather industry performance needs and provide a platform for standardized benchmarking and challenges to compare technology performance. The project is coordinated by researchers in Europe and runs for three years under the Horizon 2020 program.

1. Holistic Benchmarking of Big Linked Data
HOBBIT
Irini Fundulaki
Institute of Computer Science - FORTH
Greece
4th Graph-TA
Barcelona, Spain, March 3, 2016
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2. Voluminous Datasets
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1http://www.ibmbigdatahub.com/infographic/four-vs-big-data
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3. Large number of Linked Data Technologies
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2https://cdn.datafloq.com/cms/os_big_data_open_source_tools-v2.png
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4. Issues to address for Linked Data Technologies
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Which are the critical steps of the Linked
Data lifecycle?
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Which are the current bottlenecks?
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Which are the available market solutions?
√
Which are the relevant key performance
indicators?
√
What is the performance of existing tools
w.r.t. relevant performance indicators?
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5. Holistic Benchmarking of Big Linked Data
(HOBBIT)
HOBBIT focuses on Big Linked Data and intends to cover the
business-critical steps of the Linked Data lifecycle
√
Objectives
Gather real Performance indicators and Performance thresholds from
industry
Develop benchmarks based on real data
Provide universal benchmarking platform on standardized hardware to
provide comparable results
Provide periodic benchmarking challenges and reporting
Found independent Hobbit association
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6. HOBBIT Benchmarks
√
Generation and Acquisition: will test the performance of the systems that
implement approaches for extracting RDF data from
semi-structured data streams such as sensor data (smart metering) and
unstructured data streams (Twitter, RSS feeds, etc.)
√
Analysis and Processing
linking benchmark will test the performance of instance matching
methods for Linked Data
analytics benchmark will test the performance of supervised and
unsupervised machine learning methods
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7. HOBBIT Benchmarks
√
Storage and Curation
storage benchmark will test the performance storage components and
small storage subsystems
versioning benchmark will examine how versioning systems perform
w.r.t. size of the multi-version repository and the efficiency of
cross-snapshot query answering
√
Visualization and Services: will test the performance of systems regarding
question answering and
faceted browsing.
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8. HOBBIT Overview
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9. HOBBIT Logistics
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Horizon 2020, 3 years duration (01/12/2016–30/11/2018)
√
Coordinator: Dr. Axel-Cyrille Ngonga-Ngomo, Institute of Applied
Informatics, Germany
√
Partners:
Institute for applied informatics (InfAI), Germany
Fraunhofer IAIS, Germany
Foundation for Research and Technology (FORTH), Greece
National Center for Scientific Research "Demokritos" (NCSR), Greece
iMinds, Belgium
USU Software AG, Germany
ONTOS AG, Switzerland
OpenLink, UK
AGT Group R&D GMBH, Germany
TomTom, Poland
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