- An upper ontology of about 35,000 reference concepts, designed to provide a common grounding for relating different ontologies or schema to one another, and
- A vocabulary for aiding ontology and data mapping, including expressions of likelihood relationships distinct from exact identity or equivalence. This vocabulary is also designed for interoperating amongst various domain ontologies.
The Gene Ontology resource provides a computational representation of our current scientific knowledge about the functions of genes (or, more properly, the protein and non-coding RNA molecules produced by genes) from many different organisms, from humans to bacteria. It is widely used to support scientific research, and has been cited in tens of thousands of publications.
Understanding gene function—how individual genes contribute to the biology of an organism at the molecular, cellular and organism levels—is one of the primary aims of biomedical research. Moreover, experimental knowledge obtained in one organism is often applicable to other organisms, particularly if the organisms share the relevant genes because they inherited them from their common ancestor. The Gene Ontology (GO), as a consortium, began in 1998 when researchers studying the genome of three model organisms—Drosophila melanogaster (fruit fly), Mus musculus (mouse), and Saccharomyces cerevisiae (brewer’s or baker’s yeast)—agreed to work collaboratively on a common classification scheme for gene function, and today the number of different organisms represented in GO is in the thousands. GO makes it possible, in a flexible and dynamic way, to provide comparable descriptions of homologous gene and protein sequences across the phylogenetic spectrum.
GO is also at the hub of a major effort to represent the vast amount of biomedical knowledge in a computable form. GO is linked to many other biomedical ontologies, and is a foundation for research applying computer science in biology and medicine.
A lighter OWL axiomatization of DOLCE and the DnS upper ontology. The DOLCE component of this ontology is a simplification of some parts of DOLCE Lite-Plus. Main aspects in which DOLCE+DnS Ultralite departs from DOLCE Lite-Plus are the following:
- The names of classes and relations have been made more intuitive
- The DnS-related part is closer to the newer constructive DnS ontology.
- Temporal and spatial relations are simplified
- Qualities and regions are more relaxed than in DOLCE-Full: they can be used as attributes of any entity; an axiom states that each quality has a region
- Axiomatization makes use of simpler constructs than DOLCE Lite-Plus
- The architecture of the ontology is pattern-based, which means that DOLCE+DnS Ultralite is also available in modules, called ‘content ontology design patterns’, which can be applied independently in the design of domain ontologies. If many modules are needed in a same ontology project, it is anyway useful to use this integrated version.
The final result is a lightweight, easy-to-apply foundational ontology for modeling either physical or social contexts. Several extensions of DOLCE+DnS Ultralite have been designed:
- Information objects
- Legal domain
- Lexical and semiotic domains
- DOLCE-Zero is a commonsense-oriented generalisation of some top-level classes, which allows to use DOLCE with tolerance against ambiguities like abstract vs. concrete information, locations vs. physical artifacts, event occurrences vs. event types, events vs. situations, qualities vs. regions, etc.; etc.
A supplementary ontology used as a generalization of DOLCE+DnS Ultralite (DUL), in order to deal with the systematic polysemy of many lexical items, whose senses create problems when used as OWL classes. For example, it's customary to find lexical items that carry both a sense of physical or abstract location, of event or event type, etc.
The CIDOC Conceptual Reference Model (CRM) provides definitions and a formal structure for describing the implicit and explicit concepts and relationships used in cultural heritage documentation.
The CIDOC CRM is intended to promote a shared understanding of cultural heritage information by providing a common and extensible semantic framework that any cultural heritage information can be mapped to. It is intended to be a common language for domain experts and implementers to formulate requirements for information systems and to serve as a guide for good practice of conceptual modelling. In this way, it can provide the “semantic glue” needed to mediate between different sources of cultural heritage information, such as that published by museums, libraries and archives.
The CIDOC CRM is the culmination of over 10 years work by the CIDOC Documentation Standards Working Group and CIDOC CRM SIG which are working groups of CIDOC. Since 9/12/2006 it is official standard ISO 21127:2006.
Implementation of the CIDOC Conceptual Reference Model, version 5.0.1, in OWL 2.
Chemical Entities of Biological Interest (ChEBI)
Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The term ‘molecular entity’ refers to any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity. The molecular entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms.
ChEBI incorporates an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified.
ChEBI uses nomenclature, symbolism and terminology endorsed by the following international scientific bodies:
- International Union of Pure and Applied Chemistry (IUPAC)
- Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB)
Molecules directly encoded by the genome (e.g. nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI.
The Basic Formal Ontology (BFO) is a small, upper level ontology that is designed for use in supporting information retrieval, analysis and integration in scientific and other domains. BFO is a genuine upper ontology. Thus it does not contain physical, chemical, biological or other terms which would properly fall within the coverage domains of the special sciences. BFO is used by more than 250 ontology-driven endeavors throughout the world.
The BFO project was initiated in 2002 under the auspices of the project Forms of Life sponsored by the Volkswagen Foundation. The theory behind BFO was developed first by Barry Smith and Pierre Grenon and presented in a series of publications listed here.