An Ontological Approach to Knowledge Building by Data Integration

This paper discusses the uncertainty in the automation of knowledge building from heterogeneous raw datasets. Ontologies play a critical role in such a process by providing a well consolidated support to link and semantically integrate datasets via interoperability, as well as semantic enrichment an...

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Autores principales: Pileggi, Salvatore Flavio, Crain, Hayden, Yahia, Sadok Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304717/
http://dx.doi.org/10.1007/978-3-030-50436-6_35
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author Pileggi, Salvatore Flavio
Crain, Hayden
Yahia, Sadok Ben
author_facet Pileggi, Salvatore Flavio
Crain, Hayden
Yahia, Sadok Ben
author_sort Pileggi, Salvatore Flavio
collection PubMed
description This paper discusses the uncertainty in the automation of knowledge building from heterogeneous raw datasets. Ontologies play a critical role in such a process by providing a well consolidated support to link and semantically integrate datasets via interoperability, as well as semantic enrichment and annotations. By adopting Semantic Web technology, the resulting ecosystem is fully machine consumable. However, while the manual alignment of concepts from different vocabularies is reasonable at a small scale, fully automatic mechanisms are required once the target system scales up, leading to a significant uncertainty.
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spelling pubmed-73047172020-06-22 An Ontological Approach to Knowledge Building by Data Integration Pileggi, Salvatore Flavio Crain, Hayden Yahia, Sadok Ben Computational Science – ICCS 2020 Article This paper discusses the uncertainty in the automation of knowledge building from heterogeneous raw datasets. Ontologies play a critical role in such a process by providing a well consolidated support to link and semantically integrate datasets via interoperability, as well as semantic enrichment and annotations. By adopting Semantic Web technology, the resulting ecosystem is fully machine consumable. However, while the manual alignment of concepts from different vocabularies is reasonable at a small scale, fully automatic mechanisms are required once the target system scales up, leading to a significant uncertainty. 2020-05-25 /pmc/articles/PMC7304717/ http://dx.doi.org/10.1007/978-3-030-50436-6_35 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Pileggi, Salvatore Flavio
Crain, Hayden
Yahia, Sadok Ben
An Ontological Approach to Knowledge Building by Data Integration
title An Ontological Approach to Knowledge Building by Data Integration
title_full An Ontological Approach to Knowledge Building by Data Integration
title_fullStr An Ontological Approach to Knowledge Building by Data Integration
title_full_unstemmed An Ontological Approach to Knowledge Building by Data Integration
title_short An Ontological Approach to Knowledge Building by Data Integration
title_sort ontological approach to knowledge building by data integration
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304717/
http://dx.doi.org/10.1007/978-3-030-50436-6_35
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