LOD lab: Scalable linked data processing

Wouter Beek, Laurens Rietveld, F. Ilievski, Stefan Schlobach*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

With tens if not hundreds of billions of logical statements, the Linked Open Data (LOD) is one of the biggest knowledge bases ever built. As such it is a gigantic source of information for applications in various domains, but also given its size an ideal test-bed for knowledge representation and reasoning, heterogeneous nature, and complexity. However, making use of this unique resource has proven next to impossible in the past due to a number of problems, including data collection, quality, accessibility, scalability, availability and findability. The LOD Laundromat and LOD Lab are recent infrastructures that addresses these problems in a systematic way, by automatically crawling, cleaning, indexing, analysing and republishing data in a unified way. Given a family of simple tools, LOD Lab allows researchers to query, access, analyse and manipulate hundreds of thousands of data documents seamlessly, e.g. facilitating experiments (e.g. for reasoning) over hundreds of thousands of (possibly integrated) datasets based on content and meta-data. This chapter provides the theoretical basis and practical skills required for making ideal use of this large scale experimental platform. First we study the problems that make it so hard to work with Semantic Web data in its current form. We’ll also propose generic solutions and introduce the tools the reader needs to get started with their own experiments on the LOD Cloud.

Original languageEnglish
Title of host publicationReasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering - 12th International Summer School 2016, Tutorial Lectures
PublisherSpringer/Verlag
Pages124-155
Number of pages32
Volume9885 LNCS
ISBN (Print)9783319494920
DOIs
Publication statusPublished - 2017
Event12th International Summer School on Reasoning Web Summer School, RW 2016 - Aberdeen, United Kingdom
Duration: 5 Sep 20169 Sep 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9885 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference12th International Summer School on Reasoning Web Summer School, RW 2016
CountryUnited Kingdom
City Aberdeen
Period5/09/169/09/16

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