NCBO Ontology Recommender 2.0: An Enhanced Approach for Biomedical Ontology Recommendation

Biomedical researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a new recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies. It also can be customized to fit the needs of different scenarios. Ontology Recommender 2.0 combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available.Comment: 29 pages, 8 figures, 11 table

Improving data identification and tagging for more effective decision making in agriculture

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Harnessing the power of unified metadata in an ontology repository: The case of AgroPortal

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: (1) analyzing metadata annotations of 805 ontologies; (2) 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.); (3) 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 preexisting 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

TactoColor : conception et évaluation d’une interface d’exploration spatiale du web pour malvoyants

Nous nous intéressons, dans le cadre de cette recherche, à l’accès à l’internet des personnes malvoyantes. Plusieurs types d’outils destinés à ce public sont disponibles sur le marché, comme les lecteurs et les agrandisseurs d’écran, en fonction de l’acuité visuelle de la personne. Bien que ces outils soient utiles et régulièrement utilisés, les malvoyants (ainsi que les aveugles) évoquent souvent leur aspect frustrant. Plusieurs raisons sont citées, comme le manque d’organisation spatiale du contenu lu avec les lecteurs d’écran ou le fait de ne solliciter qu’un seul sens. La présente recherche consiste à adapter pour les malvoyants un système en développement le TactoWeb (Petit, 2013) qui permet une exploration audio-tactile du Web. TactoWeb a été conçu pour les handicapés ayant une cécité complète et n’offre donc aucune propriété visuelle. Nous proposons ici une adaptation du système pour les handicapés n’ayant qu’une déficience visuelle partielle. Nous espérons fournir à cette population des outils performants qui leur permettront de naviguer sur l’internet de façon efficace et agréable. En effet, grâce à une exploration non-linéaire (qui devrait améliorer l’orientation spatiale) et une interface multimodale (qui sollicite la vue, l’ouïe et le toucher), nous pensons réduire fortement le sentiment de frustration qu’évoquent les malvoyants. Nous avons posé l’hypothèse qu’une exploration non-linéaire et trimodale d’un site internet avec TactoColor est plus satisfaisante et efficace qu’une exploration non-linéaire bimodale avec TactoWeb (sans retour visuel). TactoColor a été adapté pour les malvoyants en ajoutant des indices visuels traduisant les composantes de la page (liens, menus, boutons) qui devraient rendre l’exploration plus aisée. Pour vérifier notre hypothèse, les deux versions du logiciel ont été évaluées par des malvoyants. Ainsi, les participants ont commencé soit avec TactoWeb, soit avec TactoColor afin de ne pas favoriser une des versions. La qualité de la navigation, son efficacité et son efficience ont été analysées en se basant sur le temps nécessaire à l’accomplissement d’une tâche, ainsi que la facilité ou la difficulté évoquée par le participant. Aussi, à la fin de chaque session, nous avons demandé leur avis aux participants, grâce à un questionnaire d’évaluation, ce qui nous a permis d’avoir leur retour sur notre logiciel après leur brève expérience. Tous ces relevés nous ont permis de déterminer que l’ajout des couleurs entraine une exploration plus rapide des pages web et une meilleure orientation spatiale. Par contre les performances très différentes des participants ne permettent pas de dire si la présence des couleurs facilite la complétion des tâches.For this research we wanted to focus on how we could improve the satisfaction of visually impaired people when surfing the internet. Many applications are being developed and used to help the disabled on the web, but almost all of them are criticized. Two of the main complaints are that you can only use one of your senses to interact with them and that it is very difficult to figure out how a page is organized. As Human Beings, we are used to use at least two senses at a time, for example you cannot help smelling and seeing. Thus, being forced to depend only on your hearing is very frustrating. This research wants to adapt, for visually impaired people, a new software, TactoWeb which allows an audio-tactile exploration of the web. As TactoWeb was conceived for blind people, there is no visual element. TactoWeb is a nonlinear screen reader designed to read the elements depending on where they are on the page. By answering the principal needs mentioned by blind people, TactoWeb could be an excellent product. Therefore, our hypothesis is that a nonlinear and tri-modal exploration of a web site is more efficient and satisfying than a bimodal. As many people are first visually impaired before being completely blind, we worked on a version, TactoColor, which would suit their special needs. We added visual elements (links, menu, button) that should make any exploration easier. We asked two groups of visually impaired to test both programs, one starting with TactoWeb and the others with TactoColor, in order not to favor any version. We analyzed the quality of the exploration, its efficacy and efficiency by looking at how long the participants took to fulfill their task and whether or not they found it easy. Thanks to these data, we were able to determine that participants completed their tasks faster. The exploration was also easier thanks to the colors which helped them understand the organization of the elements of the page. However, it is difficult to say if the colors make completion easier because the participant’s results are too different

Building a biomedical ontology recommender web service

<p>Abstract</p> <p>Background</p> <p>Researchers in biomedical informatics use ontologies and terminologies to annotate their data in order to facilitate data integration and translational discoveries. As the use of ontologies for annotation of biomedical datasets has risen, a common challenge is to identify ontologies that are best suited to annotating specific datasets. The number and variety of biomedical ontologies is large, and it is cumbersome for a researcher to figure out which ontology to use.</p> <p>Methods</p> <p>We present the <it>Biomedical Ontology Recommender web service</it>. The system uses textual metadata or a set of keywords describing a domain of interest and suggests appropriate ontologies for annotating or representing the data. The service makes a decision based on three criteria. The first one is <it>coverage</it>, or the ontologies that provide most terms covering the input text. The second is <it>connectivity</it>, or the ontologies that are most often mapped to by other ontologies. The final criterion is <it>size</it>, or the number of concepts in the ontologies. The service scores the ontologies as a function of scores of the annotations created using the National Center for Biomedical Ontology (NCBO) <it>Annotator web service</it>. We used all the ontologies from the UMLS Metathesaurus and the NCBO BioPortal.</p> <p>Results</p> <p>We compare and contrast our Recommender by an exhaustive functional comparison to previously published efforts. We evaluate and discuss the results of several recommendation heuristics in the context of three real world use cases. The best recommendations heuristics, rated ‘very relevant’ by expert evaluators, are the ones based on coverage and connectivity criteria. The Recommender service (alpha version) is available to the community and is embedded into BioPortal.</p