Affiliations: [a] Centre for the Study of Marine Systems, Centro Nacional Patagónico (CENPAT-CONICET), Puerto Madryn, Argentina | [b] Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina | [c] Grupo de Investigación en Lenguajes e Inteligencia Artificial, Departamento de Teoría de la Computación, Universidad Nacional del Comahue (UNCOMA), Neuquén, Argentina | [d] Computer Science and Engineering Department, Universidad Nacional del Sur (UNS), Bahia Blanca, Argentina | [e] Comisión de Investigaciones Científicas, provincia de Buenos Aires, Argentina | [f] Electric and Computer Engineering Department, Universidad Nacional del Sur (UNS), Bahia Blanca, Argentina
Correspondence:
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Corresponding author: Marcos Zárate, Centro Científico Tecnológico (CONICET-CENPAT), Bv. Almirante Brown 2915, Puerto Madryn, Chubut, Argentina. Tel.: +54-9280-4844320; E-mail: zarate@cenpat-conicet.gob.ar.
Note: [1] This work is an extended and revised version of the paper: Zárate et al. (2017) “BioOnto: Towards an Integration of Biological and Biogeographic Data” published in Ontologies and Data in Life Sciences (ODLS 2017), in conjunction with the Joint Ontology Workshops 2017, Bozen-Bolzano, Italy, September 21–23, 2017.
Note: [] Accepted by: Michael Gruninger
Abstract: Great progress to digitize the world’s available Biodiversity and Biogeography data have been made recently, but managing data from many different providers and research domains still remains a challenge. A review of the current landscape of metadata standards and ontologies in Biodiversity sciences suggests that existing standards, such as the Darwin Core terminology, are inadequate for describing Biodiversity data in a semantically meaningful and computationally useful way. As a contribution to fill this gap, we present an ontology-based system, called BiGe-Onto, designed to manage data together from Biodiversity and Biogeography. As data sources, we use two internationally recognized repositories: the Global Biodiversity Information Facility (GBIF) and the Ocean Biogeographic Information System (OBIS). BiGe-Onto system is composed of (i) BiGe-Onto Architecture (ii) a conceptual model called BiGe-Onto specified in OntoUML, (iii) an operational version of BiGe-Onto encoded in OWL 2, and (iv) an integrated dataset for its exploitation through a SPARQL endpoint. We will show use cases that allow researchers to answer questions that manage information from both domains.
