Search

FAIR-IMPACT has the ambitious goal of realising an EOSC of FAIR data and services by supporting the implementation of FAIR-enabling practices, tools and services across scientific communities and at national, European and institutional level. The project places its focus on persistent identifiers (WP3), metadata and ontologies (WP4) metrics, guidelines and certification (WP5) and interoperability (WP6) in line with the respective EOSC SRIA action areas. This process of identifying practices, policies, tools and technical specifications to guide a wide spectrum of stakeholders groups starts with real-life use cases integrated in the project’s structure across the social sciences and humanities, the photon and neutron sciences, life sciences, and agri-food and environmental sciences. These efforts are supported by wide synchronisation, engagement and communication activities, including open calls for cascading grants and in-kind support to specific stakeholders. The relation between FAIR-IMPACT’s contribution and the most relevant Operational Objectives and Action Areas of the EOSC SRIA are mapped.

The overall objective of WP7 “Dissemination, exploitation and communication” is to address dissemination, exploitation and communication of the project at all levels and through multiple modalities to ensure the FAIR-IMPACT objectives and impacts are achieved. To assure this, an effective and efficient communication, dissemination and stakeholder engagement strategy and plan is defined in this document. The plan is built around four specific campaigns described in detail in Chapter 4, each one with clear objectives and actions custom designed around the target stakeholders that the project is addressing, which are introduced in Chapter 3. The first campaign will run across the 36 months of the project and is dedicated to the project communication (Chapter 4.1). It aims to position the FAIR-IMPACT project in EOSC and FAIR ecosystems and ensure awareness among target stakeholders. A second campaign aims to disseminate the key project results (Chapter 4.2) to ensure their widespread accessibility and uptake of the guidelines, solutions, success stories and tools developed by the project. Actions to foster implementation and adoption of FAIR solutions are part of a third campaign (Chapter 4.3) which aims to encourage research communities, data service providers, national level initiatives, and other stakeholders to implement FAIR. This will involve stimulating interest in applying to the open calls and providing useful examples of implementing FAIR in different contexts . Last but not least, collaboration and coordination mechanisms (Chapter 4.4) are also designed and planned to maximise the impact of the project by synchronising with related projects and initiatives in the EOSC framework via the Synchronisation Force workshops, engaging ambassadors, multipliers and disseminators of the FAIR-IMPACT outputs via the FAIR Champions and boosting dissemination and impact of the FAIR-IMPACT solutions at national and regional level via the National Roadshow

Musical awareness of the languages spoken in general and that of the French language in particular in the field of teaching French as a foreign language remains today weak, not generalized and much inferior to linguistic and cultural awareness. By placing oneself within the framework of the didactology-didactics of the music of the French language-culture, it appears that modes of conditioning of this spontaneous, intuitive and reflected musical consciousness can logically take their place in accordance with fundamental existence of the music of the French language produced in the spoken mode and of the need for the learner to master it., Musical awareness of languages in general and that of the French language in particular in the field of teaching French as a foreign language remains weak today, not generalized and far inferior to linguistic and cultural awareness. By placing oneself within the framework of the didactology-didactics of the music of the French language-culture, it appears that modes of conditioning of this spontaneous, intuitive and reflected musical consciousness can logically take their place in accordance with the fundamental existence of the music of the French language produced in the spoken mode and of the need for the learner to master it.

In this paper, we report on the outputs and adoption of the Agrisemantics Working Group of the Research Data Alliance (RDA), consisting of a set of recommendations to facilitate the adoption of semantic technologies and methods for the purpose of data interoperability in the field of agriculture and nutrition. From 2016 to 2019, the group gathered researchers and practitioners at the crossing point between information technology and agricultural science, to study all aspects in the life cycle of semantic resources: conceptualization, edition, sharing, standardization, services, alignment, long term support. First, the working group realized a landscape study, a study of the uses of semantics in agrifood, then collected use cases for the exploitation of semantics resources-a generic term to encompass vocabularies, terminologies, thesauri, ontologies. The resulting requirements were synthesized into 39 "hints" for users and developers of semantic resources, and providers of semantic resource services. We believe adopting these recommendations will engage agrifood sciences in a necessary transition to leverage data production, sharing and reuse and the adoption of the FAIR data principles. The paper includes examples of adoption of those requirements, and a discussion of their contribution to the field of data science.

This paper presents a tool, TyDI, and methods experimented in the building of a termino-ontology, i.e. a lexicalized ontology aimed at fine-grained indexation for semantic search applications. TyDI provides facilities for knowledge engineers and domain experts to efficiently collaborate to validate, organize and conceptualize corpus extracted terms. A use case on biotechnology patent search demonstrates TyDI's potential.

[FR] Le cinquième numéro de la revue Synergies Espagne que nous avons l’honneur et le plaisir de présenter est le fruit d’une succession de collaborations institutionnelles, universitaires, scientifiques, humaines. Nous tenons à remercier tout d’abord l’Agence Universitaire de la Francophonie, Bureau de l’Europe de l’Ouest (BEO) pour son soutien financier, fondé sur une évaluation préalablement positive du projet, facteur déterminant dans la réalisation et l’orientation de ce numéro. Cet appui, en symbiose parfaite avec l’idée initiale de l’Equipe de la revue Synergies Espagne et la Mission du GERFLINT, visait à encourager, mobiliser, promouvoir et diffuser les études et recherches de futurs auteurs, collaborateurs, chercheurs francophones débutants et confirmés en provenance de diverses zones géographiques et travaillant dans des domaines de pointe de l’aménagement linguistique et de la formation professionnelle dans le but de répondre à des besoins stratégiques pour le développement scientifique et technique.

Web semantic access in specific domains calls for specialized search engines with enhanced semantic querying and indexing capacities, which pertain both to information retrieval (IR) and to information extraction (IE). A rich linguistic analysis is required either to identify the relevant semantic units to index and weight them according to linguistic specific statistical distribution, or as the basis of an information extraction process. Recent developments make Natural Language Processing (NLP) techniques reliable enough to process large collections of documents and to enrich them with semantic annotations. This paper focuses on the design and the development of a text processing platform, Ogmios, which has been developed in the ALVIS project. The Ogmios platform exploits existing NLP modules and resources, which may be tuned to specific domains and produces linguistically annotated documents. We show how the three constraints of genericity, domain semantic awareness and performance can be handled all together.

Studies of different term extractors on a corpus of the biomedical domain revealed decreasing performances when applied to highly technical texts. The difficulty or impossibility of customising them to new domains is an additional limitation. In this paper, we propose to use external terminologies to influence generic linguistic data in order to augment the quality of the extraction. The tool we implemented exploits testified terms at different steps of the process: chunking, parsing and extraction of term candidates. Experiments reported here show that, using this method, more term candidates can be acquired with a higher level of reliability. We further describe the extraction process involving endogenous disambiguation implemented in the term extractor YaTeA.

This paper gives an overview of the Caderige project. This project involves teams from different areas (biology, machine learning, natural language processing) in order to develop high-level analysis tools for extracting structured information from biological bibliographical databases, especially Medline. The paper gives an overview of the approach and compares it to the state of the art.

We study the adaptation of Link Grammar Parser to the biomedical sublanguage with a focus on domain terms not found in a general parser lexicon. Using two biomedical corpora, we implement and evaluate three approaches to addressing unknown words: automatic lexicon expansion, the use of morphological clues, and disambiguation using a part-of-speech tagger. We evaluate each approach separately for its effect on parsing performance and consider combinations of these approaches. In addition to a 45% increase in parsing efficiency, we find that the best approach, incorporating information from a domain part-of-speech tagger, offers a statistically signicant 10% relative decrease in error. The adapted parser is available under an open-source license at http://www.it.utu.fi/biolg.

In this paper, we propose a method to adapt a general parser (Link Parser) to sublanguages, focusing on the parsing of texts in biology. Our main proposal is the use of terminology (identication and analysis of terms) in order to reduce the complexity of the text to be parsed. Several other strategies are explored and finally combined among which text normalization, lexicon and morpho-guessing module extensions and grammar rules adaptation. We compare the parsing results before and after these adaptations.