"Confortation": About a New Category for Analyzing Biomedical Texts

International audienceIn this paper we present a new approach to the expression of certainty and uncertainty in scientific experimental articles. This will permit to ascertain the validity of knowledge extracted from biological literature and used to automatically populate a domain ontology. We argue that lexical terms such as show, find, observe... express a semantic category different from the one characterized by markers such as demonstrate, validate, support... We name the latter category “confortation” as it conveys a notion of strengthening and we propose five other semantic categories: lack of knowledge, objects of study, hypothesis, observations, and general knowledge. This last category and the linguistic phenomenon of reported speech are respectively examined as consensual truth and as knowledge reported from identified scientific sources

A Knowledge Management Platform for Documentation of Case Reports in Pharmacovigilance

Most countries have developed information systems to report drug adverse effects. However, as in other domains where systematic reviews are needed, there is little guidance on how systematic documentation of drug adverse effects should be performed. The objective of the VigiTermes project is to develop a platform to improve documentation of pharmacovigilance case reports for the pharmaceutical industry and regulatory authorities. In order to improve systematic reviews of adverse drug reactions, we developed a prototype that first reproduces and standardizes search strategies, then extracts information from the Medline abstracts which were retrieved and annotates them. The platform aims at providing transparent access and analysis tools to pharmacovigilance experts investigating relevance of safety signals related to drugs. The platform's architecture consists in the integration of two vendor tools ITM® and Luxid® and one academic web service for knowledge extraction from medical literature. Whereas a manual search performed by a pharmacovigilance expert retrieved 578 publications, the system proposed a list of 229 publications thus decreasing time required for review by 60%. Recall was 70% and additional developments are required in order to improve exhaustivity

Digital Technology To Support Organic Growers ? Mesclun: A Web App To Help Designing Complex Organic Vegetable Production

For organic vegetable growers, combining long rotations involving a high level of plant diversity with intercropping can bring economic and ecological benefits but often increase management complexity and workload. To support the decision making of farmers facing such challenges, the research-action objective of the MESCLUN programme is to develop a web application based on the innovative computer technologies of knowledge graphs and semantic web. In this French transdisciplinary project, we articulate methods and frameworks from different fields (agronomy, economy, design, knowledge and computer engineering) with expertise of agricultural practitioners (organic growers, advisors, teachers, organic farming students). Through an iterative and participatory approach based on co-innovation workshops in 4 contrasted regions of France, we design, develop and test web app prototypes to help farmers to appropriate systemic thinking, explore and assess their “own” solutions in the organisation of complex organic vegetables systems. We will present functionalities/interface of the first web app prototype. We will for example show how the web app can help growers to plan their crops in space and time considering contrasted fertility and plants health strategies as well as marketing requirements. We will also illustrate how different simulations can be assessed from a socio-economic perspective (workload and income). Based on those first results, we will examine the specificities, added value and blind spots of our web app compared to other decision making tools in the organic agricultural sector. To feed a more general debate, we will provide critical discussion points on the potentialities and limitations of innovative digital solutions to support decision making in complex organic farming systems

Results of the Ontology Alignment Evaluation Initiative 2021

The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2021 campaign offered 13 tracks and was attended by 21 participants. This paper is an overall presentation of that campaig

OntoPop or how to annotate documents and populate ontologies from texts

from text

Web Sémantique et Informatique Linguistique : propositions méthodologiques et réalisation d'une plateforme logicielle

This thesis approaches the issues related to semantic annotation and ontology population within the framework defined by the Semantic Web. The explicit representation of the contents of the Web resources is possible thanks to domain ontologies. They model the concepts, their attributes and the relations used to annotate the contents of the documents. And the knowledge base, associated with the ontology, must contain the instances to be used for semantic annotation. The idea suggested here is to combine the Information Extraction tools (IE) with the WS knowledge representation ones for the tasks of annotation and population. But there is currently a gap between the formats of representation used by these tools. This thesis proposes to fill this gap by designing a mediator able to transform the tags generated by the IE tools into a more formal representation, being the semantic annotations or the ontology instances.Cette thèse aborde les problématiques liées à l'annotation sémantique et au peuplement d'ontologies dans le cadre défini par le Web Sémantique. La représentation explicite des contenus des ressources du Web est possible grâce aux ontologies. Elles modélisent les concepts, leurs attributs et les relations utilisées pour annoter le contenu des documents. Et la base de connaissance, associée à cette ontologie, doit contenir les instances à utiliser pour l'annotation sémantique. L'idée proposée ici est de combiner les outils d'extraction d'information (EI) avec les outils de représentation des connaissances du WS pour les tâches d'annotation et de peuplement. Mais il existe actuellement un fossé entre les formats de représentation utilisés par chacun de ces outils. Cette thèse propose de combler ce fossé en concevant un médiateur capable de transformer les étiquettes générées par les outils d'EI en une représentation plus formelle, que ce soit sous la forme des annotations sémantiques ou des instances d'une ontologie

Enrichissement automatique d'une base de connaissances biologiques à l'aide des outils du Web sémantique

International audienceCollecter, lire, interpréter et annoter une grande masse de données textuelles n'est pas chose facile depuis le développement des nouvelles technologies dont Internet qui propose pléthore d'informations. Ces tâches sont d'autant plus fastidieuses à mener dans le domaine de la biologie où les intervenants doivent constamment être informés des nouveautés mais aussi réaliser des expériences sur la paillasse pour publier à leur tour leurs travaux et rester concurrentiels. Cet article propose de construire une ontologie, de la peupler automatiquement grâce à une méthode de traitement automatique des langues : les patrons lexico-syntaxiques. Une évaluation de l'extraction de connaissances est réalisée et présente une précision de 72% ainsi qu'un rappel de 50%

Francart T: A Semantic Web Portal with HLT Capabilities

Semantic Web, semantic annotations, information extraction, knowledge base enrichment