Biomedical Resource Ontology

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VO: Vaccine Ontology

Vaccine research, as well as the development, testing, clinical trials, and commercial uses of vaccines involve complex processes with various biological data that include gene and protein expression, analysis of molecular and cellular interactions, study of tissue and whole body responses, and extensive epidemiological modeling. Although many data resources are available to meet different aspects of vaccine needs, it remains a challenge how we are to standardize vaccine annotation, integrate data about varied vaccine types and resources, and support advanced vaccine data analysis and inference. To address these problems, the community-based Vaccine Ontology (VO, "http://www.violinet.org/vaccineontology":http://www.violinet.org/vaccineontology) has been developed through collaboration with vaccine researchers and many national and international centers and programs, including the National Center for Biomedical Ontology (NCBO), the Infectious Disease Ontology (IDO) Initiative, and the Ontology for Biomedical Investigations (OBI). VO utilizes the Basic Formal Ontology (BFO) as the top ontology and the Relation Ontology (RO) for definition of term relationships. VO is represented in the Web Ontology Language (OWL) and edited using the Protégé-OWL. Currently VO contains more than 2000 terms and relationships. VO emphasizes on classification of vaccines and vaccine components, vaccine quality and phenotypes, and host immune response to vaccines. These reflect different aspects of vaccine composition and biology and can thus be used to model individual vaccines. More than 200 licensed vaccines and many vaccine candidates in research or clinical trials have been modeled in VO. VO is being used for vaccine literature mining through collaboration with the National Center for Integrative Biomedical Informatics (NCIBI). Multiple VO applications will be presented.
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VO: Vaccine Ontology

The collaborative, community-based Vaccine Ontology (VO) was developed to promote vaccine data standardization, integration, and computer-assisted reasoning. Currently VO covers a variety of aspects of the vaccine domain, with an emphasis on classification of vaccines and vaccine components, and on host immune response to vaccines. VO can be used for a number of applications, e.g., ontology-based vaccine literature mining through collaboration with the National Center for Integrative Biomedical Informatics (NCIBI)

Towards richer descriptions of our collection of genomes andmetagenomes

In this commentary, we advocate building a richer set of descriptions about our invaluable and exponentially growing collection of genomes and metagenomic datasets through the construction of consensus-driven data capture and exchange mechanisms. Standardization activities must proceed within the auspices of open-access and international working bodies, and to tackle the issues surrounding the development of better descriptions of genomic investigations we have formed the Genomic Standards Consortium (GSC). Here, we introduce the 'Minimum Information about a Genome Sequence' specification in the hopes of gaining wider participation in its development and discuss the resources that will be required to support it (standardization of annotations through the use of ontologies and mechanisms of metadata capture, exchange). As part of its wider goals, the GSC also strongly supports improving the 'transparency' of the information contained in existing genomic databases that contain calculated analyses and genomic annotations

Ontology-­based Tools to Enhance the Curation Workflow

In order to effectively search, retrieve, and analyze data oftentimes it is curated and tagged with ontology terms. However, the amount of effort to curate the existing set of data resources is beyond the limits of purely manual curation. We present three ontology-based tools developed by the National Center for Biomedical Ontology to enhance the curation workflow: Ontology Widgets, Notes, and the Annotator. The Ontology Widgets provide a mechanism to use ontologies in Web-based forms without the need to locally parse and store the ontology. The widgets provide a variety of functionality including term autocompletion and ontology visualization. The Ontology Widgets are implemented for all BioPortal ontologies, including those from the OBO Foundry and Unified Medical Language System. The Notes feature of BioPortal allows structured term proposals to be submitted in order to request the addition or modification of a term in an ontology. The term proposals can be added directly via the BioPortal Web interface or programmatically via the Notes Web service. Notification of new Notes and replies are both RSS- and Email-enabled. Once the term curation process is complete, the OWL class or OBO stanza can be generated via the Notes Web service. Finally, the Annotator can be used to automatically process textual metadata to identify ontology terms found within the text. The Annotator can be accessed programmatically via the Annotator Web service and can be used with all BioPortal ontologies. In summary, the Ontology Widgets, Notes, and Annotator provide mechanisms to enhance curation by helping collect annotated data upon data submission, by facilitating ontology term curation, and by tagging unstructured textual data with ontology terms

smartAPI: Towards a more intelligent network of Web APIs

Data science increasingly employs cloud-based web application programming interfaces (apis). However, automatically discovering and connecting suitable apis for a given application is difficult due to the lack of explicit knowledge about the structure and datatypes of web api inputs and outputs. To address this challenge, we conducted a survey to identify the metadata elements that are crucial to the description of web apis and subsequently developed the smartapi metadata specification and associated tools to capture their domain-related and structural characteristics using the fair (findable, accessible, interoperable, reusable) principles. This paper presents the results of the survey, provides an overview of the smartapi specification and a reference implementation, and discusses use cases of smartapi. We show that annotating apis with smartapi metadata is straightforward through an extension of the existing swagger editor. By facilitating the creation of such metadata, we increase the automated interoperability of web apis. This work is done as part of the nih commons big data to knowledge (bd2k) api interoperability working group