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At least 19 recordsLinked to original sources

Functional annotation of the Arabidopsis genome using controlled vocabularies.

Controlled vocabularies are increasingly used by databases to describe genes and gene products because they facilitate identification of similar genes within an organism or among different organisms. One of The Arabidopsis Information Resource's goals is to associate all Arabidopsis genes with terms developed by the Gene Ontology Consortium that describe the molecular function, biological process, and subcellular location of a gene product. We have also developed terms describing Arabidopsis anatomy and developmental stages and use these to annotate published gene expression data. As of March 2004, we used computational and manual annotation methods to make 85,666 annotations representing 26,624 unique loci. We focus on associating genes to controlled vocabulary terms based on experimental data from the literature and use The Arabidopsis Information Resource-developed PubSearch software to facilitate this process. Each annotation is tagged with a combination of evidence codes, evidence descriptions, and references that provide a robust means to assess data quality. Annotation of all Arabidopsis genes will allow quantitative comparisons between sets of genes derived from sources such as microarray experiments. The Arabidopsis annotation data will also facilitate annotation of newly sequenced plant genomes by using sequence similarity to transfer annotations to homologous genes. In addition, complete and up-to-date annotations will make unknown genes easy to identify and target for experimentation. Here, we describe the process of Arabidopsis functional annotation using a variety of data sources and illustrate several ways in which this information can be accessed and used to infer knowledge about Arabidopsis and other plant species.

Arabidopsis↗

Electronic surveillance of the pharmacology-toxicology literature: the need for controlled vocabularies and registry systems.

Controlled vocabularies of "preferred names" and registry systems are essential in electronic indexing, storing, searching, and retrieving the world's published literature. The most efficient and comprehensive search is accomplished by using the preferred name. Without a controlled vocabulary or a registry system, it would be necessary to remember every name that might have been used by authors since January 1966, in order to retrieve all the citations on a chemical from over 7.8 million citations currently in the National Library of Medicine's MEDLINE and its backfiles. The task of creating the list of subject descriptors that make possible the surveillance of published literature via electronic databases requires the participation of the scientific community in developing domain-specific nomenclature, drug classification, controlled vocabularies, and registry systems as well. The biological unions of the International Council of Scientific Unions and its Committee on Data for Science and Technology are major contributors to the establishment and dissemination of standards for biological terminology and nomenclature. The objectives of the IUPHAR Nomenclature Committee include the development of a rational framework for the nomenclature of receptor classes or families and a classification for therapeutic agents. This will help define rules for the characterization and classification of receptors that are stable and easy to comprehend. The International Union of Pharmacology publishes guidelines for the classification of drugs and the nomenclature of receptors and ion channels.

Abstracting and Indexing↗

Separate but equal? A system comparison study of MEDLINE's controlled vocabulary MeSH.

This study tested the effect of controlled vocabulary search feature implementation on two online systems. Specifically, the study examined retrieval rates using four unique controlled vocabulary search features (explode, major descriptor, descriptor, subheadings). Each search feature was applied to nine search queries obtained from a medical reference librarian. The same queries were searched in the complete MEDLINE file on the Dialog and Ovid systems. The unique records, i.e., those records retrieved in only one of the two systems, were identified and analyzed. Dialog produced equal or more records than Ovid in nearly 20% of the queries. The study demonstrated that users need to be aware of system-specific designs that may require differing input strategies across different systems for the same unique controlled vocabulary search features. The paper concludes by making recommendations and suggestions for future research.

Evaluation Studies as Topic↗

Coping with changing controlled vocabularies.

For the foreseeable future, controlled medical vocabularies will be in a constant state of development, expansion and refinement. Changes in controlled vocabularies must be reconciled with historical patient information which is coded using those vocabularies and stored in clinical databases. This paper explores the kinds of changes that can occur in controlled vocabularies, including adding terms (simple additions, refinements, redundancy and disambiguation), deleting terms, changing terms (major and minor name changes), and other special situations (obsolescence, discovering redundancy, and precoordination). Examples are drawn from actual changes appearing in the 1993 update to the International Classification of Diseases (ICD9-CM). The methods being used at Columbia-Presbyterian Medical Center to reconcile its Medical Entities Dictionary and its clinical database are discussed.

Medical Records Systems, Computerized↗

Planned NLM/AHCPR large-scale vocabulary test: using UMLS technology to determine the extent to which controlled vocabularies cover terminology needed for health care and public health.

The National Library of Medicine (NLM) and the Agency for Health Care Policy and Research (AHCPR) are sponsoring a test to determine the extent to which a combination of existing health-related terminologies covers vocabulary needed in health information systems. The test vocabularies are the 30 that are fully or partially represented in the 1996 edition of the Unified Medical Language System (UMLS) Metathesaurus, plus three planned additions: the portions of SNOMED International not in the 1996 Metathesaurus Read Clinical Classification, and the Logical Observations Identifiers, Names, and Codes (LOINC) system. These vocabularies are available to testers through a special interface to the Internet-based UMLS Knowledge Source Server. The test will determine the ability of the test vocabularies to serve as a source of controlled vocabulary for health data systems and applications. It should provide the basis for realistic resource estimates for developing and maintaining a comprehensive "standard" health vocabulary that is based on existing terminologies.

Computer Communication Networks↗

Evaluation of controlled vocabulary resources for development of a consumer entry vocabulary for diabetes.

BACKGROUND: Digital information technology can facilitate informed decision making by individuals regarding their personal health care. The digital divide separates those who do and those who do not have access to or otherwise make use of digital information. To close the digital divide, health care communications research must address a fundamental issue, the consumer vocabulary problem: consumers of health care, at least those who are laypersons, are not always familiar with the professional vocabulary and concepts used by providers of health care and by providers of health care information, and, conversely, health care and health care information providers are not always familiar with the vocabulary and concepts used by consumers. One way to address this problem is to develop a consumer entry vocabulary for health care communications. OBJECTIVES: To evaluate the potential of controlled vocabulary resources for supporting the development of consumer entry vocabulary for diabetes. METHODS: We used folk medical terms from the Dictionary of American Regional English project to create extended versions of 3 controlled vocabulary resources: the Unified Medical Language System Metathesaurus, the Eurodicautom of the European Commission's Translation Service, and the European Commission Glossary of popular and technical medical terms. We extracted consumer terms from consumer-authored materials, and physician terms from physician-authored materials. We used our extended versions of the vocabulary resources to link diabetes-related terms used by health care consumers to synonymous, nearly-synonymous, or closely-related terms used by family physicians. We also examined whether retrieval of diabetes-related World Wide Web information sites maintained by nonprofit health care professional organizations, academic organizations, or governmental organizations can be improved by substituting a physician term for its related consumer term in the query. RESULTS: The Dictionary of American Regional English extension of the Metathesaurus provided coverage, either direct or indirect, of approximately 23% of the natural language consumer-term-physician-term pairs. The Dictionary of American Regional English extension of the Eurodicautom provided coverage for 16% of the term pairs. Both the Metathesaurus and the Eurodicautom indirectly related more terms than they directly related. A high percentage of covered term pairs, with more indirectly covered pairs than directly covered pairs, might be one way to make the most out of expensive controlled vocabulary resources. We compared retrieval of diabetes-related Web information sites using the physician terms to retrieval using related consumer terms We based the comparison on retrieval of sites maintained by non-profit healthcare professional organizations, academic organizations, or governmental organizations. The number of such sites in the first 20 Results from a search was increased by substituting a physician term for its related consumer term in the query. This suggests that the Dictionary of American Regional English extensions of the Metathesaurus and Eurodicautom may be used to provide useful links from natural language consumer terms to natural language physician terms. CONCLUSIONS: The Dictionary of American Regional English extensions of the Metathesaurus and Eurodicautom should be investigated further for support of consumer entry vocabulary for diabetes.

Community Participation↗

microntology: a lightweight, data-driven controlled vocabulary to describe earth's microbial habitats.

MOTIVATION: Data-enabled studies of microbial ecology and evolution depend on high-quality descriptions of microbial habitats, based on curated and consolidated vocabularies. RESULTS: We introduce microntology v1.0, a pragmatic controlled vocabulary of 148 terms to describe microbial habitats and lifestyles, and provide manually curated microntology annotations for >300k metagenomic samples from public repositories. AVAILABILITY: microntology controlled vocabulary terms and term hierarchies (doi: 10.5281/zenodo.19730167), and curated annotations for 305 626 metagenomic samples (doi: 10.5281/zenodo.18164252) are available via Zenodo and spire.embl.de/downloads. Underlying code is available via github.com/grp-schmidt/microntology and Zenodo (doi: 10.5281/zenodo.20323497). User feedback, suggestions and bug reports are welcome at github.com/grp-schmidt/microntology/issues.

Ecosystem↗

The use of common ontologies and controlled vocabularies to enable data exchange and deposition for complex proteomic experiments.

Controlled vocabularies provide a roadmap through complex biological data. Proteomic data is increasing in volume and is currently poorly served by public repositories due to the large number of different formats in which the data is generated and stored. The Human Proteome Organization Proteome Standards Initiative is establishing standards for data transfer and deposition. These standards utilize ontologies and controlled vocabularies to describe experimental procedures and common processes such as sample preparation This paper will discuss the development of such ontologies by the user community and their current utilization in the fields of protein:proein interactions and mass spectrometry.

Computational Biology↗

Searching biomedical databases on complementary medicine: the use of controlled vocabulary among authors, indexers and investigators.

BACKGROUND: The optimal retrieval of a literature search in biomedicine depends on the appropriate use of Medical Subject Headings (MeSH), descriptors and keywords among authors and indexers. We hypothesized that authors, investigators and indexers in four biomedical databases are not consistent in their use of terminology in Complementary and Alternative Medicine (CAM). METHODS: Based on a research question addressing the validity of spinal palpation for the diagnosis of neuromuscular dysfunction, we developed four search concepts with their respective controlled vocabulary and key terms. We calculated the frequency of MeSH, descriptors, and keywords used by authors in titles and abstracts in comparison to standard practices in semantic and analytic indexing in MEDLINE, MANTIS, CINAHL, and Web of Science. RESULTS: Multiple searches resulted in the final selection of 38 relevant studies that were indexed at least in one of the four selected databases. Of the four search concepts, validity showed the greatest inconsistency in terminology among authors, indexers and investigators. The use of spinal terms showed the greatest consistency. Of the 22 neuromuscular dysfunction terms provided by the investigators, 11 were not contained in the controlled vocabulary and six were never used by authors or indexers. Most authors did not seem familiar with the controlled vocabulary for validity in the area of neuromuscular dysfunction. Recently, standard glossaries have been developed to assist in the research development of manual medicine. CONCLUSIONS: Searching biomedical databases for CAM is challenging due to inconsistent use of controlled vocabulary and indexing procedures in different databases. A standard terminology should be used by investigators in conducting their search strategies and authors when writing titles, abstracts and submitting keywords for publications.

Abstracting and Indexing↗

The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries.

BACKGROUND: With the vast amounts of biomedical data being generated by high-throughput analysis methods, controlled vocabularies and ontologies are becoming increasingly important to annotate units of information for ease of search and retrieval. Each scientific community tends to create its own locally available ontology. The interfaces to query these ontologies tend to vary from group to group. We saw the need for a centralized location to perform controlled vocabulary queries that would offer both a lightweight web-accessible user interface as well as a consistent, unified SOAP interface for automated queries. RESULTS: The Ontology Lookup Service (OLS) was created to integrate publicly available biomedical ontologies into a single database. All modified ontologies are updated daily. A list of currently loaded ontologies is available online. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A programmatic interface is available to query the webservice using SOAP. The service is described by a WSDL descriptor file available online. A sample Java client to connect to the webservice using SOAP is available for download from SourceForge. All OLS source code is publicly available under the open source Apache Licence. CONCLUSION: The OLS provides a user-friendly single entry point for publicly available ontologies in the Open Biomedical Ontology (OBO) format. It can be accessed interactively or programmatically at http://www.ebi.ac.uk/ontology-lookup/.

Database Management Systems↗

Development of a controlled vocabulary and software application to analyze fruit shape variation in tomato and other plant species.

The domestication and improvement of fruit-bearing crops resulted in a large diversity of fruit form. To facilitate consistent terminology pertaining to shape, a controlled vocabulary focusing specifically on fruit shape traits was developed. Mathematical equations were established for the attributes so that objective, quantitative measurements of fruit shape could be conducted. The controlled vocabulary and equations were integrated into a newly developed software application, Tomato Analyzer, which conducts semiautomatic phenotypic measurements. To demonstrate the utility of Tomato Analyzer in the detection of shape variation, fruit from two F2 populations of tomato (Solanum spp.) were analyzed. Principal components analysis was used to identify the traits that best described shape variation within as well as between the two populations. The three principal components were analyzed as traits, and several significant quantitative trait loci (QTL) were identified in both populations. The usefulness and flexibility of the software was further demonstrated by analyzing the distal fruit end angle of fruit at various user-defined settings. Results of the QTL analyses indicated that significance levels of detected QTL were greatly improved by selecting the setting that maximized phenotypic variation in a given population. Tomato Analyzer was also applied to conduct phenotypic analyses of fruit from several other species, demonstrating that many of the algorithms developed for tomato could be readily applied to other plants. The controlled vocabulary, algorithms, and software application presented herein will provide plant scientists with novel tools to consistently, accurately, and efficiently describe two-dimensional fruit shapes.

Algorithms↗

Application of eVOC: controlled vocabularies for unifying gene expression data.

To provide standardised description of gene expression and cross platform querying of databases, we have developed eVOC (http://www.sanbi.ac.za/evoc/), consisting of four orthogonal ontologies which describe Anatomical System, Cell Type, Pathology and Developmental Stage. We have annotated 47 microarray expression data sets and all publicly available human cDNA and SAGE tag libraries. eVOC has been integrated with the public resource EnsMart, which provides linking of transcripts and libraries with expression terms and the human genome sequence (http://www.ensembl.org/Homo_sapiens/martview).

Databases, Genetic↗

Controlled vocabularies for consumer health.

There is often a disconnect between the language that consumers use to express health concerns and the language that is used by health care professionals. At the same time, health care consumerism and the availability of vast health-related resources on the Internet have resulted in millions of persons using the Internet for health-related matters daily. The mismatch in language, however, poses a barrier to access to relevant information. It also prevents full participation in shared health records, and sometimes interferes in communication between patients and their health care providers. Nurse informaticians, with their deep expertise in vocabulary development, could play an important role in solving this dilemma. Structured vocabularies comprised of lay terms, with definitions, variant spellings, and regional dialects, along with mappings to equivalent or related professional terms, could make health literature much more accessible to consumers, and provide the basis for bi-directional translation of health terms in a shared medical record. In addition, the presence of terms for which no representation currently exists in nursing terminologies could serve as a stimulus for developing new knowledge about patient phenomena not previously recognized.

Community Participation↗

Do existing controlled vocabularies contain terminology needed for patient records?

A 1996-97 study conducted by the National Library of Medicine and the Agency for Health Care Policy and Research aimed to determine how well existing vocabularies cover the concepts and terms needed in health information systems. The author describes the hypothesis underlying the study, how the process worked, its findings, and implications for future vocabulary development.

Abstracting and Indexing↗

Utilizing weakly controlled vocabulary for sentence segmentation in biomedical literature.

Since biomedical texts contain a wide variety of domain specific terms, building a large dictionary to perform term matching is of great relevance. However, due to the existence of null boundary between adjacent terms, this matching is not a trivial problem. Moreover, it is known that generative words cannot be comprehensively included in a dictionary because their possible variations are infinite. In this study, we report our approach to dictionary building and term matching in biomedical texts. Large amount of terms with/without part-of-speech (POS) and/or category information were gathered, and a completion program generated approximately 1.36 million term variants to avoid stemming problems when matching terms. The dictionary was stored in a relational database management system (RDBMS) for quick lookup, and used by a matching program. Since the matching operation is not restricted to a substring surrounded by space characters, we can avoid the problem of null boundaries. This feature is also useful for generative words. Experimental results on GENIA corpus are promising: nearly half of the possible terms were correctly recognized as a meaningful segment, and most of the remaining half could be correctly recognized by some post-processing process, like chunking and further decomposition. It should be remarked that although we have not used term cost, connectivity cost, or syntactic information, reasonable segmentation and dictionary lookup were performed in most cases.

Abstracting and Indexing↗

The Australian Medicines Handbook and its controlling vocabularies.

The Australian Medicines Handbook is intended to serve as an independent peer-reviewed knowledge resource for health care providers. A printed handbook is planned first, followed by electronic products. Information about medication will be dissected and entered into a detailed database, whose elemental nature should make it "computer understandable." The terms used in the database will be cross-referenced to preferred terms. Thus, the vocabulary will be controlled. The handbook will be printed directly from the database with use of database publishing techniques.

Australia↗