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9 octobre 2019
- handle: 10670/1.6vv7h3
- halshs: halshs-02314003
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info:eu-repo/grantAgreement//820323/EU/Time Machine : Big Data of the Past for the Future of Europe/
http://creativecommons.org/licenses/by-sa/ , info:eu-repo/semantics/OpenAccess
Mots-clés
FAIR principles Ontology Building Methodology Digital history CIDOC CRM Virtual research environmentSujets proches
Scientific research Science research Science--Research Nurture and nature Nature versus nurture Genetics and environment Nature--Nurture Environment Heredity and environment Environment Ecological science Environmental biology Bionomics Ecological sciences Environment Balance of nature Oecology Biology--Ecology Ecological processes EnvironmentCiter ce document
Francesco Beretta et al., « Geohistorical FAIR data: data integration and Interoperability using the OntoME platform », HAL-SHS : histoire, ID : 10670/1.6vv7h3
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The poster focus on the basic workflow of model alignment and data integration that can be built using the Ontology management environment OntoME application in connection with the virtual research environment Geovistory (http://geovistory.com/). The integration of data from different sources is based on an explicit documentation of each original model, then on the alignment of these models with classes and properties designed within the conceptual framework of CIDOC CRM (ISO 21127:2014). For this purpose, new classes and properties close to the research domain can be added in OntoME within namespaces dedicated to the different projects. They will then be aligned with the more abstract classes of CIDOC CRM in order to achieve data interoperability.The poster present the essential steps and first results in the process of integrating data from different sources carried out in the Huygens ING/CLARIAH Geovistory pilot project (http://forum.dataforhistory.org/node/150). The aim of this project is to import sets of data into the Geovistory online application, currently developed by Kleio Lab GmbH, in order to allow historians to reuse the data, analyze it and visualize it. At the end of the process, the wrangled data can be made available to other researchers and the public on a human readable webpage or a SPARQL endpoint.