Vincent Emonet

New Generation Metadata vocabulary for Ontology Description and Publication

Scientific communities are using an increasing number of ontologies and vocabularies. Currently, the problem lies in the difficulty to find and select them for a specific knowledge engineering task. Thus, there is a real need to precisely describe these ontologies with adapted metadata, but none of the existing metadata vocabularies can completely meet this need if taken independently. In this paper, we present a new version of Metadata vocabulary for Ontology Description and publication, referred as MOD 1.2 which succeeds previous work published in 2015. It has been designed by reviewing in total 23 standard existing metadata vocabularies (e.g., Dublin Core, OMV, DCAT, VoID) and selecting relevant properties for describing ontologies. Then, we studied metadata usage analytics within ontologies and ontology repositories. MOD 1.2 proposes in total 88 properties to serve both as (i) a vocabulary to be used by ontology developers to annotate and describe their ontologies, or (ii) an explicit OWL vocabulary to be used by ontology libraries to offer semantic descriptions of ontologies as linked data. The experimental results show that MOD 1.2 supports a new set of queries for ontology libraries. Because MOD is still in early stage, we also pitch the plan for a collaborative design and adoption of future versions within an international working group.

YAM++ Online : A Web Platform for Ontology and Thesaurus Matching and Mapping Validation

We present the multi-task web platform YAM++ online for ontology and thesaurus matching, featuring a mapping validation and enrichment interface. The online matcher is based on the YAM++ system. The validator allows to visualize an alignment, edit the relation type and add new mappings discovered through a keyword-based search by a domain expert.

Multilingual Mapping Reconciliation between English-French Biomedical Ontologies

Even if multilingual ontologies are now more common, for historical reasons, in the biomedical domain, many ontologies or terminologies have been translated from one natural language to another resulting in two potentially aligned ontologies but with their own specificity (e.g., format, developers, and versions). Most often, there is no formal representation of the translation links between translated ontologies and original ones and those mappings are not formally available as linked data. However, these mappings are very important for the interoperability and the integration of multilingual biomedical data. In this paper, we propose an approach to represent translation mappings between ontologies based on the NCBO BioPortal format. We have reconciled more than 228K mappings between ten English ontologies hosted on NCBO BioPortal and their French translations. Then, we have stored both the translated ontologies and mappings on a French customized version of the platform, called the SIFR BioPortal, making the whole thing available in RDF. Reconciling the mappings turned more complex than expected because the translations are rarely exactly the same than the original ontologies as discussed in this paper.

Enhanced Functionalities for Annotating and Indexing Clinical Text with the NCBO Annotator

Abstract Summary Second use of clinical data commonly involves annotating biomedical text with terminologies and ontologies. The National Center for Biomedical Ontology Annotator is a frequently used annotation service, originally designed 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 clinical 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 available, 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). Supplementary information Supplementary data are available at Bioinformatics online.