Rule-Based Data Access: A Use Case in Agroecology
Abstract
There is a crucial need for tools to help designing sustainable agrosystems. In this paper, we consider the issue of selecting plant species according to the ecosystem services they are likely to deliver. For that, we rely on the one hand on recent scientific results in agronomy linking functional traits (i.e., measurable characterics of plant species) to ecosystem services, and on the other hand on data collected by the research community in ecology. The architecture of our prototype is inspired by the ontology- based data access paradigm, which clearly distinguishes between the data level and the knowledge representation level, with mappings linking the two levels. Knowledge is represented in a rule langage that extends plain Datalog with computed functions and stratified negation. We detail the construction of a knowledge base devoted to vine grassing, i.e., installing herbaceous service plants in vineyards, and briefly report on the experimental evaluation of the system’s results on this use case.
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