The University of Southampton
University of Southampton Institutional Repository

Crowdsourcing tasks within linked data management

Crowdsourcing tasks within linked data management
Crowdsourcing tasks within linked data management
Many aspects of Linked Data management – including exposing legacy data and applications to semantic formats, designing vocabularies to describe RDF data, identifying links between entities, query processing, and data curation– are necessarily tackled through the combination of human effort with algorithmic techniques. In the literature on traditional data management the theoretical and technical groundwork to realize and manage such combinations is being established. In this paper we build upon and extend these ideas to propose a framework by which human and computational intelligence can co-exist by augmenting existing Linked Data and Linked Service technology with crowdsourcing functionality. Starting from a motivational scenario we introduce a set of generic tasks which may feasibly be approached using crowdsourcing platforms such as Amazon’s Mechanical Turk, explain how these tasks can be decomposed and translated into MTurk projects, and roadmap the extensions to SPARQL, D2RQ/R2R and Linked Data browsing that are required to achieve this vision.
Simperl, E.
40261ae4-c58c-48e4-b78b-5187b10e4f67
Norton, B.
24e57777-0135-412a-b93f-d24fca273091
Vrandecic, D.
2642fe14-9606-4ee3-8616-67f30849f3b3
Simperl, E.
40261ae4-c58c-48e4-b78b-5187b10e4f67
Norton, B.
24e57777-0135-412a-b93f-d24fca273091
Vrandecic, D.
2642fe14-9606-4ee3-8616-67f30849f3b3

Simperl, E., Norton, B. and Vrandecic, D. (2011) Crowdsourcing tasks within linked data management At Second International Workshop on Consuming Linked Data (COLD 2011), Germany. 23 Oct 2011.

Record type: Conference or Workshop Item (Paper)

Abstract

Many aspects of Linked Data management – including exposing legacy data and applications to semantic formats, designing vocabularies to describe RDF data, identifying links between entities, query processing, and data curation– are necessarily tackled through the combination of human effort with algorithmic techniques. In the literature on traditional data management the theoretical and technical groundwork to realize and manage such combinations is being established. In this paper we build upon and extend these ideas to propose a framework by which human and computational intelligence can co-exist by augmenting existing Linked Data and Linked Service technology with crowdsourcing functionality. Starting from a motivational scenario we introduce a set of generic tasks which may feasibly be approached using crowdsourcing platforms such as Amazon’s Mechanical Turk, explain how these tasks can be decomposed and translated into MTurk projects, and roadmap the extensions to SPARQL, D2RQ/R2R and Linked Data browsing that are required to achieve this vision.

Full text not available from this repository.

More information

Published date: 23 October 2011
Venue - Dates: Second International Workshop on Consuming Linked Data (COLD 2011), Germany, 2011-10-23 - 2011-10-23
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 351665
URI: http://eprints.soton.ac.uk/id/eprint/351665
PURE UUID: 35451590-c33a-41a6-bf80-8179bb454661
ORCID for E. Simperl: ORCID iD orcid.org/0000-0003-1722-947X

Catalogue record

Date deposited: 29 Apr 2013 15:49
Last modified: 18 Jul 2017 04:24

Export record

Contributors

Author: E. Simperl ORCID iD
Author: B. Norton
Author: D. Vrandecic

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×