The use of Web Ontology Language (OWL) to Combine Extant Controlled Vocabularies in Biodiversity Informatics Appears Redundant

Implementation of PESI requires data to be combined from multiple source databases. Some of the shared fields in the source databases used different controlled vocabularies of terms. OWL DL was investigated as a mechanism to build an extensible, shared ontology of species occurrence terms that permitted the source database to continue using and extending their own vocabularies whilst formally mapping to a more generic shared vocabulary. The merits of this approach were explored and it was concluded that the building of such a complex mapping ontology probably wasn't worthwhile. The level of semantic complexity involved outweighed the costs of simply imposing a flat list of well defined terms onto data suppliers. The main problem with exiting vocabularies appear to be the overloading of terms. A candidate list of terms was proposed

The Role of E-Vocabularies in the Description and Retrieval of Digital Educational Resources

Vocabularies are linguistic resources that make it possible to access knowledge through words. They can constitute a mechanism to identify, describe, explore, and access all the digital resources with informational content pertaining to a specific knowledge domain. In this regard, they play a key role as systems for the representation and organization of knowledge in environments in which content is created and used in a collaborative and free manner, as is the case of social wikis and blogs on the Internet or educational content in e-learning environments. In e-learning environments, electronic vocabularies (e-vocabularies) constitute a mechanism for conceptual representation of digital educational resources. They enable human and software agents either to locate and interpret resource content in large digital repositories, including the web, or to use them (vocabularies) as an educational resource by itself to learn a discipline terminology. This review article describes what e-vocabularies are, what they are like, how they are used, how they work, and what they contribute to the retrieval of digital educational resources. The goal is to contribute to a clearer view of the concepts which we regard as crucial to understand e-vocabularies and their use in the field of e-learning to describe and retrieve digital educational resources

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

Definitions in ontologies

Definitions vary according to context of use and target audience. They must be made relevant for each context to fulfill their cognitive and linguistic goals. This involves adapting their logical structure, type of content, and form to each context of use. We examine from these perspectives the case of definitions in ontologies

Bridging End Users' Terms and AGROVOC Concept Server Vocabularies

The AGROVOC is a multilingual structured thesaurus in the agricultural domain. It has already been mapped with several vocabularies, for example AGROVOC-CAT, AGROVOC-NALT , AGROVOC-SWD. Although these vocabularies already contained a good portion of non-preferred terms, the terms are collected under the literary warrant and institutional warrant principles; which means vocabularies were collected based on the documents and publications rather than user‟s queries. It is still very common that end users would use different terms to express the same concept. In light of above discussion, we need to bridge these vocabularies and the users‟ terms Backgroun

Knowledge Organization Systems & Their Applications

This training session introduces Knowledge Organization Systems (KOSs) and their applications especially in the Library and Information Science (LIS) field. It talks about various KOS systems including term lists, subject headings, categorization schemas, classification schemas, taxonomies, thesauri, semantic networks and ontologies. It gives many KOS examples especially those pertain to LIS such as BIBFRAME. It also discusses the process and different methods of creating categories, tag libraries and taxonomies. It was delivered to librarians and staff members in Technical Services at the University Central Florida Libraries and aimed to help catalogers better understand knowledge organization related concepts and systems in and beyond the library field

Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium

Over the last several decades, there has been rapid growth in the number and scope of agricultural genetics, genomics and breeding (GGB) databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as 'databases' throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, conducted a survey to assess the status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data sharing practices by AgBioData databases are in a healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that ontology use has not substantially changed since a similar survey was conducted in 2017. We recommend 1) providing training for database personnel in specific data sharing techniques, as well as in ontology use; 2) further study on what metadata is shared, and how well it is shared among databases; 3) promoting an understanding of data sharing and ontologies in the stakeholder community; 4) improving data sharing and ontologies for specific phenotypic data types and formats; and 5) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.Comment: 17 pages, 8 figure

Technology Integration around the Geographic Information: A State of the Art

One of the elements that have popularized and facilitated the use of geographical information on a variety of computational applications has been the use of Web maps; this has opened new research challenges on different subjects, from locating places and people, the study of social behavior or the analyzing of the hidden structures of the terms used in a natural language query used for locating a place. However, the use of geographic information under technological features is not new, instead it has been part of a development and technological integration process. This paper presents a state of the art review about the application of geographic information under different approaches: its use on location based services, the collaborative user participation on it, its contextual-awareness, its use in the Semantic Web and the challenges of its use in natural languge queries. Finally, a prototype that integrates most of these areas is presented

The Plant Ontology™ Consortium and Plant Ontologies

The goal of the Plant Ontology™ Consortium is to produce structured controlled vocabularies, arranged in ontologies, that can be applied to plant-based database information even as knowledge of the biology of the relevant plant taxa (e.g. development, anatomy, morphology, genomics, proteomics) is accumulating and changing. The collaborators of the Plant Ontology™ Consortium (POC) represent a number of core participant database groups. The Plant Ontology™ Consortium is expanding the paradigm of the Gene Ontology™ Consortium (http://www.geneontology.org). Various trait ontologies (agronomic traits, mutant phenotypes, phenotypes, traits, and QTL) and plant ontologies (plant development, anatomy [incl. morphology]) for several taxa (Arabidopsis, maize/corn/Zea mays and rice/Oryza) are under development. The products of the Plant Ontology™ Consortium will be open-source