HOBBIT: A platform for benchmarking Big Linked Data

Röder, Michael; Kuchelev, Denis; Ngomo, Axel-Cyrille Ngonga

doi:10.3233/ds-190021

Cited by 13 publications

(11 citation statements)

References 33 publications

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“…Overview. ORCA is a benchmark built upon the HOBBIT benchmarking platform [18]. 15 This FAIR benchmarking platform allows Big Linked Data systems to be benchmarked in a distributed environment.…”

Section: Methodsmentioning

confidence: 99%

ORCA - a Benchmark for Data Web Crawlers

Röder¹,

Souza²,

Kuchelev³

et al. 2021

2021 IEEE 15th International Conference on Semantic Computing (ICSC)

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The number of RDF knowledge graphs available on the Web grows constantly. Gathering these graphs at large scale for downstream applications hence requires the use of crawlers. Although Data Web crawlers exist, and general Web crawlers could be adapted to focus on the Data Web, there is currently no benchmark to fairly evaluate their performance. Our work closes this gap by presenting the ORCA benchmark. ORCA generates a synthetic Data Web, which is decoupled from the original Web and enables a fair and repeatable comparison of Data Web crawlers. Our evaluations show that ORCA can be used to reveal the different advantages and disadvantages of existing crawlers. The benchmark is open-source and available at https://github.com/dice-group/orca.

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Section: Methodsmentioning

confidence: 99%

ORCA - a Benchmark for Data Web Crawlers

Röder¹,

Souza²,

Kuchelev³

et al. 2021

2021 IEEE 15th International Conference on Semantic Computing (ICSC)

Self Cite

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“…To test whether the reference implementation and all following implementations fulfil the criteria that the given standard sets, compliance benchmarking can be used. [13] created the first compliance benchmark for GeoSPARQL 1.0 using the HOBBIT benchmarking platform [34]. Once an execution of the GeoSPARQL compliance benchmark is finished, it may produce a benchmark result in RDF (https: //github.com/hobbit-project/platform/issues/531, accessed on 30 October 2021).…”

Section: Compliance Benchmarkingmentioning

confidence: 99%

GeoSPARQL 1.1: Motivations, Details and Applications of the Decadal Update to the Most Important Geospatial LOD Standard

Car

Homburg

2022

IJGI

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In 2012, the Open Geospatial Consortium published GeoSPARQL defining “an RDF/OWL ontology for [spatial] information”, “SPARQL extension functions” for performing spatial operations on RDF data and “RIF rules” defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to “better present” the standard, that is to better link all the standard’s parts and better document and exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. This paper describes motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1’s use.

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“…To test whether the reference implementation and all following implementations fulfill the criteria that the given standard sets, compliance benchmarking can be used. [13] created the first compliance benchmark for GeoSPARQL 1.0 using the HOBBIT benchmarking platform [33]. Once an execution of the GeoSPARQL compliance benchmark is finished, it may produce a benchmark result in RDF 20 .…”

Section: Compliance Benchmarkingmentioning

confidence: 99%

“…The original intention of the GeoSPARQL SWG, when formed in 2019, was to publish a 1.1 version of GeoSPARQL, and then possible a 1.2 and a 2.0, as described in Section 1. While the scope of GeoSPARQL 1.1 has been in keeping with the original estimates for that version and there are still known un-tackled change requests that the SWG has tagged for a possible 1.2 version 33 , the SWG has entertained many thoughts about a more comprehensive tackling of spatial Semantic Web concerns that might require a different direction altogether, for example non-earth geometries, comprehensive handling of rasters 34 or a whole new ontological handling of Coordinate Reference Systems.…”

Section: Work Beyond Geosparql 11mentioning

confidence: 99%

GeoSPARQL 1.1: An Almost Decadal Update to the Most Important Geospatial LOD Standard

Car¹,

Homburg²

2021

Preprint

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In 2012 the Open Geospatial Consortium published GeoSPARQL defining “an RDF/OWL ontology for [spatial] information”, “SPARQL extension functions” for performing spatial operations on RDF data and “RIF rules” defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to “better present” the standard, that is to better link all the standard’s parts and better document &amp; exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. In this paper, we describe motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1’s use.

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HOBBIT: A platform for benchmarking Big Linked Data

Cited by 13 publications

References 33 publications

ORCA - a Benchmark for Data Web Crawlers

ORCA - a Benchmark for Data Web Crawlers

GeoSPARQL 1.1: Motivations, Details and Applications of the Decadal Update to the Most Important Geospatial LOD Standard

GeoSPARQL 1.1: An Almost Decadal Update to the Most Important Geospatial LOD Standard

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