Agronomic Linked Data (AgroLD): a Knowledge-based System to Enable Integrative Biology in Agronomy

Larmande Pierre, El Hassouni Nordine, Venkatesan Aravind, Jonquet Clément, Ruiz Manuel. 2018. Agronomic Linked Data (AgroLD): a Knowledge-based System to Enable Integrative Biology in Agronomy. In : JOBIM 2018 Abstracts. SFBI, GdR BiM, IFB, AMU, INSERM, CNRS. Marseille : SFBI, Résumé, 542-543. Journées Ouvertes Biologie, Informatique et Mathématiques (JOBIM 2018), Marseille, 3 Juillet 2018/6 Juillet 2018.

Résumé : Plant science is a multi-disciplinary scientific discipline that includes research areas such as -omics, physiology, genetics, plant breeding, systems biology and the interaction of plants with the environment to name a few. Among other things, agronomic research aims to improve crop health, production and study the environmental impact on crops. Researchers need to understand deeply the implications and interactions of the various biological processes, by linking data at di↵erent scales (e.g., genomics, proteomics and phenomics). Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of genomics or phenomics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to e↵ectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web o↵ers technologies for the integration of heterogeneous data and its transformation into explicitly knowledge thanks to ontologies. We have developed AgroLD (the Agronomic Linked Data – www.agrold.org), a knowledge-based system that exploits the Semantic Web technology and some of the relevant standard domain ontologies, to integrate genome to phenome information on plant species widely studied by the plant science community. We present some integration results of the project, which initially focused on genomics, proteomics and phenomics. Currently, AgroLD contains hundreds millions of triples created by annotating more than 50 datasets coming from 10 data sources such as Gramene.org [1] and TropGeneDB [2] with 10 ontologies such as Gene Ontology [3] and Plant Trait Ontology [4]. Our objective is to o↵er a domain specific

Auteurs et affiliations

• Larmande Pierre, IRD (FRA)
• El Hassouni Nordine, INRA (FRA)
• Venkatesan Aravind, Institut de Biologie Computationnelle (FRA)
• Jonquet Clément, LIRMM (FRA)
• Ruiz Manuel, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0001-8153-276X

Source : Cirad-Agritrop (https://agritrop.cirad.fr/588857/)

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