LexRDF Model: An RDF-based Unified Model for Heterogeneous Biomedical Ontologies (original) (raw)
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Journal of the American Medical Informatics Association, 2009
A b s t r a c t Many biomedical terminologies, classifications, and ontological resources such as the NCI Thesaurus (NCIT), International Classification of Diseases (ICD), Systematized Nomenclature of Medicine (SNOMED), Current Procedural Terminology (CPT), and Gene Ontology (GO) have been developed and used to build a variety of IT applications in biology, biomedicine, and health care settings. However, virtually all these resources involve incompatible formats, are based on different modeling languages, and lack appropriate tooling and programming interfaces (APIs) that hinder their wide-scale adoption and usage in a variety of application contexts. The Lexical Grid (LexGrid) project introduced in this paper is an ongoing community-driven initiative, coordinated by the Mayo Clinic Division of Biomedical Statistics and Informatics, designed to bridge this gap using a common terminology model called the LexGrid model. The key aspect of the model is to accommodate multiple vocabulary and ontology distribution formats and support of multiple data stores for federated vocabulary distribution. The model provides a foundation for building consistent and standardized APIs to access multiple vocabularies that support lexical search queries, hierarchy navigation, and a rich set of features such as recursive subsumption (e.g., get all the children of the concept penicillin). Existing LexGrid implementations include the LexBIG API as well as a reference implementation of the HL7 Common Terminology Services (CTS) specification providing programmatic access via Java, Web, and Grid services.
Medical science monitor: …, 2002
HealthCyberMap (URI: http://healthcybermap.semanticweb.org) aims at mapping health information resources in cyberspace in unique and novel ways, and deliver a semantically superior experience to consumers of these resources. This paper describes the work undertaken in Protégé-2000 to develop a Dublin Core metadata set ontology for HealthCyberMap and a Web resource metadata collection form based on it. The Dublin Core subject field is populated with UMLS terms directly imported from the UMLS Knowledge Source Server using the UMLS tab, a Protégé-2000 plug-in. The ontology and its instances are saved in RDFS/ RDF. The paper also discusses some relevant Semantic Web issues and ways of exploiting Protégé-2000 RDFS/ RDF Output. Although HealthCyberMap's visualisation components (the different types of hypermaps) contribute significantly to the Semantic Web functionality of the project, these are not discussed in this paper.
LexOWL: A Bridge from LexGrid to OWL
Nature Precedings, 2009
The Lexical Grid project is an on-going community driven initiative that provides a common terminology model to represent multiple vocabulary and ontology sources as well as a scalable and robust API for accessing such information. In order to add more powerful functionalities to the existing infrastructure and align LexGrid more closely with various Semantic Web technologies, we introduce the LexOWL project for representing the ontologies modeled within the LexGrid environment in OWL (Web Ontology Language). The crux of this effort is to create a "bridge" that functionally connects the LexBIG (a LexGrid API) and the OWL API (an interface that implements OWL) seamlessly. In this paper, we discuss the key aspects of designing and implementing the LexOWL bridge. We compared LexOWL with other OWL converting tools and conclude that LexOWL provides an OWL mapping and converting tool with well-defined interoperability for information in the biomedical domain.
Medical science monitor : international medical journal of experimental and clinical research, 2002
HealthCyberMap (http://healthcybermap.semanticweb.org/) aims at mapping Internet health information resources in novel ways for enhanced retrieval and navigation. This is achieved by collecting appropriate resource metadata in an unambiguous form that preserves semantics. We modelled a qualified Dublin Core (DC) metadata set ontology with extra elements for resource quality and geographical provenance in Prot g -2000. A metadata collection form helps acquiring resource instance data within Prot g . The DC subject field is populated with UMLS terms directly imported from UMLS Knowledge Source Server using UMLS tab, a Prot g -2000 plug-in. The project is saved in RDFS/RDF. The ontology and associated form serve as a free tool for building and maintaining an RDF medical resource metadata base. The UMLS tab enables browsing and searching for concepts that best describe a resource, and importing them to DC subject fields. The resultant metadata base can be used with a search and inferenc...
BioPortal as a Dataset of Linked Biomedical Ontologies and Terminologies in RDF
Semantic web, 2013
BioPortal is a repository of biomedical ontologies-the largest such repository, with more than 300 ontologies to date. This set includes ontologies that were developed in OWL, OBO and other formats, as well as a large number of medical terminologies that the US National Library of Medicine distributes in its own proprietary format. We have published the RDF version of all these ontologies at http://sparql.bioontology.org. This dataset contains 190M triples, representing both metadata and content for the 300 ontologies. We use the metadata that the ontology authors provide and simple RDFS reasoning in order to provide dataset users with uniform access to key properties of the ontologies, such as lexical properties for the class names and provenance data. The dataset also contains 9.8M cross-ontology mappings of different types, generated both manually and automatically, which come with their own metadata.
07132 Report -- Towards Interoperability of Biomedical Ontologies
2008
The meeting focused on uses of ontologies, with a special focus on spatial ontologies, in addressing the ever increasing needs faced by biology and medicine to cope with ever expanding quantities of data. To provide effective solutions computers need to integrate data deriving from myriad heterogeneous sources by bringing the data together within a single framework. The meeting brought together leaders in the field of what are called 'top-level ontologies' to address this issue, and to establish strategies among leaders in the field of biomedical ontology for the creation of interoperable biomedical ontologies which will serve the goal of useful data integration.
Semantic Grid for Biomedical Ontologies
Int. J. Comput. Appl, 2011
The biomedical ontologies contain the complex distributed heterogeneous data, to analyze and process this data is the big challenge for biomedical communities. The common goal of biomedical communities is to annotate this data. These problems generated a need to use the services of grid on semantic web. Semantic Grid is the integration of Grid with the Semantic web, which will play the vital role in future web. The semantic grid architecture provides semantic and knowledge support. In this paper we discuss two biomedical ontologies, Biological Viruses Community Ontology (BVCO) and the most mature Gene Ontology (GO).