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Semantic micro-contributions with decentralized nanopublication services

While the publication of Linked Data has become increasingly common, the process tends to be a relatively complicated and heavy-weight one. Linked Data is typically published by centralized entities in the form of larger dataset releases, which has the downside that there is a central bottleneck in...

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Autores principales: Kuhn, Tobias, Taelman, Ruben, Emonet, Vincent, Antonatos, Haris, Soiland-Reyes, Stian, Dumontier, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959648/
https://www.ncbi.nlm.nih.gov/pubmed/33817033
http://dx.doi.org/10.7717/peerj-cs.387
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author Kuhn, Tobias
Taelman, Ruben
Emonet, Vincent
Antonatos, Haris
Soiland-Reyes, Stian
Dumontier, Michel
author_facet Kuhn, Tobias
Taelman, Ruben
Emonet, Vincent
Antonatos, Haris
Soiland-Reyes, Stian
Dumontier, Michel
author_sort Kuhn, Tobias
collection PubMed
description While the publication of Linked Data has become increasingly common, the process tends to be a relatively complicated and heavy-weight one. Linked Data is typically published by centralized entities in the form of larger dataset releases, which has the downside that there is a central bottleneck in the form of the organization or individual responsible for the releases. Moreover, certain kinds of data entries, in particular those with subjective or original content, currently do not fit into any existing dataset and are therefore more difficult to publish. To address these problems, we present here an approach to use nanopublications and a decentralized network of services to allow users to directly publish small Linked Data statements through a simple and user-friendly interface, called Nanobench, powered by semantic templates that are themselves published as nanopublications. The published nanopublications are cryptographically verifiable and can be queried through a redundant and decentralized network of services, based on the grlc API generator and a new quad extension of Triple Pattern Fragments. We show here that these two kinds of services are complementary and together allow us to query nanopublications in a reliable and efficient manner. We also show that Nanobench makes it indeed very easy for users to publish Linked Data statements, even for those who have no prior experience in Linked Data publishing.
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spelling pubmed-79596482021-04-02 Semantic micro-contributions with decentralized nanopublication services Kuhn, Tobias Taelman, Ruben Emonet, Vincent Antonatos, Haris Soiland-Reyes, Stian Dumontier, Michel PeerJ Comput Sci Human-Computer Interaction While the publication of Linked Data has become increasingly common, the process tends to be a relatively complicated and heavy-weight one. Linked Data is typically published by centralized entities in the form of larger dataset releases, which has the downside that there is a central bottleneck in the form of the organization or individual responsible for the releases. Moreover, certain kinds of data entries, in particular those with subjective or original content, currently do not fit into any existing dataset and are therefore more difficult to publish. To address these problems, we present here an approach to use nanopublications and a decentralized network of services to allow users to directly publish small Linked Data statements through a simple and user-friendly interface, called Nanobench, powered by semantic templates that are themselves published as nanopublications. The published nanopublications are cryptographically verifiable and can be queried through a redundant and decentralized network of services, based on the grlc API generator and a new quad extension of Triple Pattern Fragments. We show here that these two kinds of services are complementary and together allow us to query nanopublications in a reliable and efficient manner. We also show that Nanobench makes it indeed very easy for users to publish Linked Data statements, even for those who have no prior experience in Linked Data publishing. PeerJ Inc. 2021-03-08 /pmc/articles/PMC7959648/ /pubmed/33817033 http://dx.doi.org/10.7717/peerj-cs.387 Text en © 2021 Kuhn et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Human-Computer Interaction
Kuhn, Tobias
Taelman, Ruben
Emonet, Vincent
Antonatos, Haris
Soiland-Reyes, Stian
Dumontier, Michel
Semantic micro-contributions with decentralized nanopublication services
title Semantic micro-contributions with decentralized nanopublication services
title_full Semantic micro-contributions with decentralized nanopublication services
title_fullStr Semantic micro-contributions with decentralized nanopublication services
title_full_unstemmed Semantic micro-contributions with decentralized nanopublication services
title_short Semantic micro-contributions with decentralized nanopublication services
title_sort semantic micro-contributions with decentralized nanopublication services
topic Human-Computer Interaction
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959648/
https://www.ncbi.nlm.nih.gov/pubmed/33817033
http://dx.doi.org/10.7717/peerj-cs.387
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