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The scientific community’s efforts have increased regarding evaluating the FAIRness of research Digital Objects such as publications, datasets, or research software. However, this requires a steep learning curve for the average researcher when learning the FAIR evaluation frameworks, disengaging some of them in the process. This project aims to use technology close this gap and make this process more accessible by bringing the FAIR evaluation to the researcher’s profiles. “The FAIR extension” is an open-source, web browser extension that allows researchers to make FAIR metricsevaluations directly from scholarly aggregators such as PURE, Google Scholar, or ResearchGate without any additional knowledge. The browser extension follows the FAIR metrics group specification, building on top of the community-accepted FAIR evaluators’ APIs. 🕶 This resource is presented atthe 1st International Conference on FAIR Digital Objectswhich is linked to the following abstract doi.org/10.3897/rio.8.e95006 🧩 Install it in your browser!!Available in the chrome store:"the FAIR extension" 🔍 For more information, please visit the the FAIR extension website &nbsp

International audience; As any resources, ontologies, thesaurus, vocabularies and terminologies need to be described with relevant metadata to facilitate their identification, selection and reuse. For ontologies to be FAIR, there is a need for metadata authoring guidelines and for harmonization of existing metadata vocabularies –taken independently none of them can completely describe an ontology. Ontology libraries and repositories also have to play an important role. Indeed, some metadata properties are intrinsic to the ontology (name, license, description); other information, such as community feedbacks, or relations to other ontologies are typically information that an ontology library shall capture, populate and consolidate to facilitate the processes of identifying and selecting the right ontology(ies) to use. We have studied ontology metadata practices by: (i) analyzing metadata annotations of 805 ontologies; (ii) reviewing the most standard and relevant vocabularies (23 totals) currently available to describe metadata for ontologies (such as Dublin Core, Ontology Metadata Vocabulary, VoID, etc.); (iii) comparing different metadata implementation in multiple ontology libraries or repositories. We have then built a new metadata model for our AgroPortal vocabulary and ontology repository, a platform dedicated to agronomy based on the NCBO BioPortal technology. AgroPortal now recognizes 346 properties from existing metadata vocabularies that could be used to describe different aspects of ontologies: intrinsic descriptions, people, date, relations, content, metrics, community, administration, and access. We use them to populate an internal model of 127 properties implemented in the portal and harmonized for all the ontologies. We –and AgroPortal's users– have spent a significant amount of time to edit and curate the metadata of the ontologies to offer a better synthetized and harmonized information and enable new ontology identification features. Our goal was also to facilitate the comprehension of the agronomical ontology landscape by displaying diagrams and charts about all the ontologies on the portal. We have evaluated our work with a user appreciation survey which confirms the new features are indeed relevant and helpful to ease the processes of identification and selection of ontologies. This paper presents how to harness the potential of a complete and unified metadata model with dedicated features in an ontology repository, however the new AgroPortal's model is not a new vocabulary as it relies on pre-existing ones. A generalization of this work is studied in a community driven standardization effort in the context of the RDA Vocabulary and Semantic Services Interest Group.

International audience; The SIFR BioPortal is an open platform to host French biomedical ontologies and terminologies based on the technology developed by the US National Center for Biomedical Ontology (NCBO). The portal facilitates the use and fostering of terminologies and ontologies by offering a set of services including semantic annotation. The SIFR Anno-tator (http://bioportal.lirmm.fr/annotator) is a publicly accessible, easily usable ontology-based annotation tool to process French text data and facilitate semantic indexing. The web service relies on the ontology content (preferred labels and synonyms) as well as on the semantic of the ontologies (is-a hierarchies) and their mappings. The SIFR BioPortal also offers the possibility of querying the original NCBO Annotator for English text via a dedicated proxy that extends the original functionality. In this paper, we present a preliminary performance evaluation of the generic annotation web service (i.e., not specifically customized) for coding death certificates i.e., annotating with ICD-10 codes. This evaluation is done against the CépiDC/CDC CLEF eHealth 2017 task 1 manually annotated corpus. For this purpose, we have built custom SKOS vocabularies from the CéPIDC/CDC dictionaries as well as training and development corpora, for all three tasks using a most frequent code heuristic to assign ambiguous labels. We then submitted the vocabularies to the NCBO and SIFR BioPortal and used the annotation services on task 1 datasets. We obtained, for our best runs on each corpus the following results: English raw corpus (69.08% P, 51.37% R, 58,92% F1); French raw corpus (54.11% P, 48.00% R, 50,87% F1); French aligned corpus (50.63% P, 52.97% R, 51.77% F1).

National audience; Scientific communities are using an increasing number of ontologies. Repositories make them available, like the NCBO BioPortal which currently hosts more than 500 biomedical ontologies. Now the question is how to find the ontology we need? One solution is to describe each ontology with appropriate metadata. However, none of the existing metadata vocabularies can completely meet this need if taken independently. We have reviewed a large number of vocabularies, such as Dublin Core, OMV, DCAT, or VOID, as well as the properties implemented by common ontology repositories. We then listed those properties into a simplified model of 124 properties. We present a few examples of use of these properties within the AgroPortal, an ontology repository for agronomy, and explain how the portal handles these properties to facilitate ontology description and selection.; Les communautés scientifiques utilisent un nombre croissant d'ontologies. Pour les mettre à disposition, il existe des portails d'ontologies, à l'exemple du NCBO BioPortal qui regroupe actuellement plus de 500 ontologies biomédicales. Mais face à cette avalanche de ressources, comment trouver l'ontologie qui répondra à nos besoins ? Une solution consiste à décrire chaque ontologie avec des métadonnées appropriées. Or, il n'existe pas à ce jour de vocabulaire de métadonnées suffisamment exhaustif pour répondre à ce besoin. Nous avons passé en revue un grand nombre de vocabulaires, tels que Dublin Core, OMV, DCAT ou VOID ainsi que les propriétés implémentées par les portails d'ontologies les plus courant. Nous en avons produit un modèle simplifié composé de 124 propriétés. Nous présentons ici quelques exemples d'utilisation de ces propriétés dans AgroPortal, un portail d'ontologies dédié à l'agronomie, et nous expliquons comment elles sont gérées et utilisées pour la description et l'identification d'ontologies.

International audience; Similarly to what happens in biomedicine, communities engaged in agronomic research need to access specific sets of ontologies for data annotation and integration. For instance, it has been established that the scientific challenges in plant breeding have switched from genetics to phenotyping and that standard traits/phenotypes vocabularies are necessary to facilitate breeder’s data integration and comparison. In parallel of very specific crop dictionaries, important organizations have produced large reference vocabularies such as AGROVOC (Food and Agriculture Organization), NAL Thesaurus (National Agricultural Library) or the CAB Thesaurus (Centre for Agricultural Bioscience International). The more ontologies are being produced in the domain, the more the need to create, store and retrieve alignments between those ontologies become important. In fact, there exists a need of a one-stop-shop for agronomical, environmental and food related ontologies enabling to identify and select an ontology for a specific task as well as offering generic services to exploit them in search, annotation or other scientific data management processes

International audience; Summary: Second use of clinical data commonly involves annotating biomedical text with terminologies and ontolo-gies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally de-signed for biomedical data, but not very suitable for clinical text annotation. In order to add new functionalities to the NCBO Annotator without hosting or modifying the original Web service, we have designed a proxy architecture that enables seamless extensions by pre-processing of the input text and parameters, and post processing of the annotations. We have then implemented enhanced functionalities for annotating and indexing free text such as: scoring, detection of context (negation, experiencer, temporality), new output formats, and coarse-grained concept recognition (with UMLS Semantic Groups). In this paper, we present the NCBO Annotator+, a Web service which incorporates these new functionalities as well as a small set of evaluation results for concept recognition and clini-cal context detection on two standard evaluation tasks (Clef eHealth 2017, SemEval 2014).Availability and Implementation: The Annotator+ has been successfully integrated into the SIFR BioPortal platform –an implementation of NCBO BioPortal for French biomedical terminologies and ontologies– to annotate English text. A Web user interface is available for testing and ontology selection (http://bioportal.lirmm.fr/ncbo_annotatorplus); however the Annotator+ is meant to be used through the Web service application programming interface (http://services.bioportal.lirmm.fr/ncbo_annotatorplus). The code is openly availa-ble, and we also provide a Docker packaging to enable easy local deployment to process sensitive (e.g., clinical) data in-house (https://github.com/sifrproject).Contact: andon.tchechmedjiev@lirmm.fr and jonquet@lirmm.frSupplementary information: Technical details and documentation available online.

Many vocabularies and ontologies are produced to represent and annotate agronomic data. Therefore, there is a need of a common platform to identify, host and use them in agro-informatics application. By reusing the NCBO BioPortal technology, we have designed AgroPortal an ontology repository for the agronomy domain. The AgroPortal project aims at reusing the scientific outcomes and experience of the biomedical domain in the context of plant, agronomy, food, and biodiversity. We offer an ontology portal which features ontology hosting, search, versioning, visualization, comment, recommendation, enables semantic annotation, as well as storing and exploiting ontology alignments. All of these within a fully semantic web compliant infrastructure. The AgroPortal specifically pays attention to respect the requirements of the agronomic community in terms of ontology formats (e.g., SKOS, trait dictionaries) or supported features. In this demonstration, we will present our platform currently open and accessible at http://agroportal.lirmm.fr.