A System for Ontology-Based Annotation of Biomedical Data

Jonquet, Clément; Musen, Mark A.; Shah, Nigam H.

doi:10.1007/978-3-540-69828-9_14

Cited by 31 publications

(24 citation statements)

References 9 publications

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“…intent in designing the ontology and its intended scope [20]; the metadata that the users provide about their use of ontologies in their repository, their reviews and ranking of the ontologies [16]; the reviews and quality control that selected experts can provide, similar to editorial boards in journals [25]; the metadata that analytical tools can provide, such as results of running an inference engine over the ontology data or analysis of connections in the ontology; finally, the resources and data that are annotated with the ontology data, with the repository providing access to these resources and data [11].…”

Section: Using a Mapping Repositorymentioning

confidence: 99%

“…For instance, one of the core functionalities of the BioPortal is to enable access to biomedical resources, such as papers, experiment results, standard terminologies, and so on. The Open Biomedical Resources (OBR) component automatically indexes important biomedical data sets available online (e.g., entries in PubMed, the Gene Expression Omnibus, ClinicalTrials.gov) on the basis of metadata annotations, and links the underlying data sets to the terms in the ontologies in BioPortal [11]. As the users browse or query the ontologies they can access the resources annotated with a specific ontology term.…”

Section: Using a Mapping Repositorymentioning

confidence: 99%

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Collecting Community-Based Mappings in an Ontology Repository

Noy

Griffith

Musen

2008

Lecture Notes in Computer Science

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Abstract. Several ontology repositories provide access to the growing collection of ontologies on the Semantic Web. Some repositories collect ontologies automatically by crawling the Web; in other repositories, users submit ontologies themselves. In addition to providing search across multiple ontologies, the added value of ontology repositories lies in the metadata that they may contain. This metadata may include information provided by ontology authors, such as ontologies' scope and intended use; feedback provided by users such as their experiences in using the ontologies or reviews of the content; and mapping metadata that relates concepts from different ontologies. In this paper, we focus on the ontology-mapping metadata and on community-based method to collect ontology mappings. More specifically, we develop a model for representing mappings collected from the user community and the metadata associated with the mapping. We use the model to bring together more than 30,000 mappings from 7 sources. We also validate the model by extending BioPortal-a repository of biomedical ontologies that we have developed-to enable users to create single concept-toconcept mappings in its graphical user interface, to upload and download mappings created with other tools, to comment on the mappings and to discuss them, and to visualize the mappings and the corresponding metadata. Ontology Mapping and the Wisdom of the CrowdsAs the number of ontologies available for Semantic Web applications grows, so does the number of ontology repositories that index and organize the ontologies. Some repositories crawl the Web to collect ontologies (e.g., Swoogle [4], Watson [3] and OntoSelect [2]). In other repositories, users submit their ontologies themselves (e.g., the DAML ontology library 1 and SchemaWeb 2 ). These repositories provide a gateway for users and application developers who need to find ontologies to use in their work. In our laboratory, we have developed BioPortal3 -an open repository of biomedical ontologies. Researchers in biomedical informatics submit their ontologies to BioPortal and others can access the ontologies through the BioPortal user interface or through web services. The BioPortal users can browse and search the ontologies, update the ontologies in the repository by uploading new versions, comment on any ontology (or portion of an ontology) in the repository, evaluate it, describe their experience in using the ontology, 1

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Section: Using a Mapping Repositorymentioning

confidence: 99%

Section: Using a Mapping Repositorymentioning

confidence: 99%

Collecting Community-Based Mappings in an Ontology Repository

Noy

Griffith

Musen

2008

Lecture Notes in Computer Science

Self Cite

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“…In this paper, we present our methodology based on documents in the biomedical domain. The recent advancements in biomedical ontologies have led to several ontology standards being extensively used in information systems [11,12]. We use BioPortal, an online resource with over 250 bio-ontologies, as our source for comprehensive domain knowledge [15].…”

Section: Introductionmentioning

confidence: 99%

Retrieval of Patent Documents from Heterogeneous Sources Using Ontologies and Similarity Analysis

Taduri

Lau

Law

et al. 2011

2011 IEEE Fifth International Conference on Semantic Computing

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Abstract-In the past few years, there has been an explosive growth in scientific and legal information related to the patent system. Patents and related documents are siloed into multiple heterogeneous sources. Retrieving relevant information from diverse sources is a non-trivial task and poses many technical challenges. Among the challenges is the issue of terminological inconsistencies that are used in the documents. We tackle the terminological inconsistency issue by exploring domain knowledge through the use of ontology standards. Furthermore, we take advantage of cross-references and structural dependencies between the information sources to enhance terminological comparison. In this paper, we present a similarity analysis methodology which combines knowledge from two distinct sources -(1) domain ontologies and (2) ontologies which describe the information sources to assist a user in identifying relevant documents across several information sources simultaneously. Specifically, we explore the use of a rule-based system to infer relationships between documents based on pre-defined heuristics. We present our results through a use case in the bio-patent domain with a collection of 1150 patents and 30 court cases.

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“…La richesse et la diversité des données biomédicales aujourd'hui accessibles au public permettent l'intégration translationnelle de multiples études bioinformatiques (translational bioinformatics research) [1] [2]. Cependant, les découvertes qui pourraient être réalisées par la fouille des données biomédicales sont limitées car la plupart des ressources publiques ne sont généralement pas décrites à l'aide de terminologies et d'ontologies.…”

Section: Introductionunclassified

“…Cependant, la variété des données est très importante et celles-ci sont rarement annotées à l'aide de concepts décrits dans des ontologies biomédicales. 1 Le plus souvent, les éléments d'une ressource (e.g., recueil de données expérimentales, diagnostics, maladies, échantillons, descriptions d'essais cliniques, publications, images) sont annotés avec des métadonnées textuelles qui décrivent cet élément. Le problème est que ces descriptions textuelles sont rarement structurées et que le plus souvent elles n'utilisent pas des termes définis dans des ontologies biomédicales.…”

Section: Introductionunclassified