The Open UniversitySkip to content
 

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

Meroño-Peñuela, Albert and Daga, Enrico (2019). List.MID: A MIDI-Based Benchmark for Evaluating RDF Lists. In: Proceedings of the 18th International Semantic Web Conference, The Semantic Web, Springer, (In Press).

Full text available as:
[img]
Preview
PDF (Accepted Manuscript) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview
URL: https://iswc2019.semanticweb.org/
Google Scholar: Look up in Google Scholar

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 evaluating 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.

Item Type: Conference or Workshop Item
ISSN: 0302-9743
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 62675
Depositing User: Enrico Daga
Date Deposited: 01 Aug 2019 15:15
Last Modified: 21 Sep 2019 07:25
URI: http://oro.open.ac.uk/id/eprint/62675
Share this page:

Download history for this item

These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.

Actions (login may be required)

Policies | Disclaimer

© The Open University   contact the OU