Frank: The LOD cloud at your fingertips?

Wouter Beek, Laurens Rietveld

Research output: Contribution to ConferencePaperOther research output

Abstract

Large-scale, algorithmic access to LOD Cloud data has been hampered by the absence of queryable endpoints for many datasets, a plethora of serialization formats, and an abundance of idiosyncrasies such as syntax errors. As of late, very large-scale — hundreds of thousands of document, tens of billions of triples — access to RDF data has become possible thanks to the LOD Laundromat Web Service. In this paper we showcase Frank, a command-line interface to a very large collection of standards-compliant, real-world RDF data that can be used to run Semantic Web experiments and stress-test Linked Data applications.
Original languageEnglish
Number of pages6
Publication statusPublished - 2015

Fingerprint

Semantic Web
Web services
Experiments

Cite this

@conference{c0d3f8b79d574d49a286377515c14b7b,
title = "Frank: The LOD cloud at your fingertips?",
abstract = "Large-scale, algorithmic access to LOD Cloud data has been hampered by the absence of queryable endpoints for many datasets, a plethora of serialization formats, and an abundance of idiosyncrasies such as syntax errors. As of late, very large-scale — hundreds of thousands of document, tens of billions of triples — access to RDF data has become possible thanks to the LOD Laundromat Web Service. In this paper we showcase Frank, a command-line interface to a very large collection of standards-compliant, real-world RDF data that can be used to run Semantic Web experiments and stress-test Linked Data applications.",
author = "Wouter Beek and Laurens Rietveld",
year = "2015",
language = "English",

}

Frank: The LOD cloud at your fingertips? / Beek, Wouter; Rietveld, Laurens.

2015.

Research output: Contribution to ConferencePaperOther research output

TY - CONF

T1 - Frank: The LOD cloud at your fingertips?

AU - Beek, Wouter

AU - Rietveld, Laurens

PY - 2015

Y1 - 2015

N2 - Large-scale, algorithmic access to LOD Cloud data has been hampered by the absence of queryable endpoints for many datasets, a plethora of serialization formats, and an abundance of idiosyncrasies such as syntax errors. As of late, very large-scale — hundreds of thousands of document, tens of billions of triples — access to RDF data has become possible thanks to the LOD Laundromat Web Service. In this paper we showcase Frank, a command-line interface to a very large collection of standards-compliant, real-world RDF data that can be used to run Semantic Web experiments and stress-test Linked Data applications.

AB - Large-scale, algorithmic access to LOD Cloud data has been hampered by the absence of queryable endpoints for many datasets, a plethora of serialization formats, and an abundance of idiosyncrasies such as syntax errors. As of late, very large-scale — hundreds of thousands of document, tens of billions of triples — access to RDF data has become possible thanks to the LOD Laundromat Web Service. In this paper we showcase Frank, a command-line interface to a very large collection of standards-compliant, real-world RDF data that can be used to run Semantic Web experiments and stress-test Linked Data applications.

M3 - Paper

ER -