List.MID: A MIDI-Based Benchmark for Evaluating RDF Lists

Albert Meroño-Peñuela*, Enrico Daga

*Corresponding author for this work

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

Abstract

Linked lists represent a countable number of ordered values, and are among the most important abstract data types in computer science. With the advent of RDF as a highly expressive knowledge representation language for the Web, various implementations for RDF lists have been proposed. Yet, there is no benchmark so far dedicated to evaluate the performance of triple stores and SPARQL query engines on dealing with ordered linked data. Moreover, essential tasks for evaluating RDF lists, like generating datasets containing RDF lists of various sizes, or generating the same RDF list using different modelling choices, are cumbersome and unprincipled. In this paper, we propose List.MID, a systematic benchmark for evaluating systems serving RDF lists. List.MID consists of a dataset generator, which creates RDF list data in various models and of different sizes; and a set of SPARQL queries. The RDF list data is coherently generated from a large, community-curated base collection of Web MIDI files, rich in lists of musical events of arbitrary length. We describe the List.MID benchmark, and discuss its impact and adoption, reusability, design, and availability.

Original languageEnglish
Title of host publicationThe Semantic Web – ISWC 2019
Subtitle of host publication18th International Semantic Web Conference, , Auckland, New Zealand, October 26–30, 2019, Proceedings, Part II
EditorsChiara Ghidini, Olaf Hartig, Maria Maleshkova, Vojtech Svátek, Isabel Cruz, Aidan Hogan, Jie Song, Maxime Lefrançois, Fabien Gandon
PublisherSpringer
Pages246-260
Number of pages15
Volume2
ISBN (Electronic)9783030307967
ISBN (Print)9783030307950
DOIs
Publication statusPublished - 2019
Event18th International Semantic Web Conference, ISWC 2019 - Auckland, New Zealand
Duration: 26 Oct 201930 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11779 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Semantic Web Conference, ISWC 2019
Country/TerritoryNew Zealand
CityAuckland
Period26/10/1930/10/19

Keywords

  • Benchmarks
  • Linked lists
  • RDF

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