Integrating Data and Knowledge to Support the Selection of Service Plant Species in Agroecology - LIRMM - Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier
Preprints, Working Papers, ... (Preprint) Year : 2022

Integrating Data and Knowledge to Support the Selection of Service Plant Species in Agroecology

Abstract

There is a crucial need for tools to help designing sustainable agroecosystems based on agroecology. Indeed, such agroecosystems are inherently complex and their design requires to integrate various data and unstabilized scientific knowledge. In this paper, we consider the issue of selecting service plant species according to their potential to provide ecosystem services. The architecture of our system is inspired by the ontology-based data access paradigm, which allows to combine data and knowledge in a principled way. We provide a methodology to acquire scientific knowledge in the form of diagrams linked to data sources, as well as a formalization in a logical rule-based language. Importantly, our rules are independent from specific diagrams and data, to ensure genericity and facilitate the evolution of the system. We detail the construction of a knowledge base devoted to vine grassing, i.e., installing herbaceous service plants in vineyards, and present an evaluation of the system's results on this use case. We finally discuss the lessons learned and further challenges to be met.
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Dates and versions

lirmm-03879910 , version 1 (30-11-2022)

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  • HAL Id : lirmm-03879910 , version 1

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Elie Najm, Marie-Laure Mugnier, Christian Gary, Jean-François Baget, Raphael Metral, et al.. Integrating Data and Knowledge to Support the Selection of Service Plant Species in Agroecology. 2022. ⟨lirmm-03879910⟩
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