The new and exotic infectious animal diseases are an incising threat to countries due to globalisation, movement of passengers and international trade. Traditionally, disease outbreaks are reported through structured multilevel health infrastructure that can lead to delays in transmission of information (Food and Agricultural Organization, 2013). Our project proposes a new methodology in the domain of epidemic intelligence in animal health in order to discover knowledge in web documents dealing with animal disease outbreaks. To address this issue, our global process is based on Information Retrieval (IR) and Information Extraction (IE) approaches (see figure below).

In the context of large amounts of textual data related to agriculture now available, indexing becomes a crucial issue for research organizations. One way to index documents consists of extracting terminology. Our project investigates the use and combination of Text Mining methodologies to highlight and publish in Open Data systems the most appropriate terms extracted with BioTex (in French and in English). Moreover these terms are used to match heterogeneous data of agricultural domain.

Our work deals with knowledge engineering issues of experimental data, extracted from scientific articles, in order to reuse them in decision support systems. Experimental data can be represented by n-ary relations which link a studied object (e.g. food packaging, transformation process) with its features (e.g. oxygen permeability in packaging, biomass grinding) and capitalized in an Ontological and Terminological Ressource (OTR). An OTR associates an ontology with a terminological and/or a linguistic part in order to establish a clear distinction between the term and the notion it denotes (the concept).Our work focuses on n-ary relation extraction from scientific documents in order to populate a domain OTR with new instances. Our contributions are based on Natural Language Processing (NLP) together with data mining approaches guided by the domain OTR.

This project aims at providing new efficient decision making tools for helping agricultural development as well as biodiversity protection in Peru. More precisely it aims at developing a new platform for helping to acquire new data, to share data, to extract knowledge, and to share useful information and knowledge among different actors that are involved in agriculture or biodiversity domains in Peru.