Vocabulary
A86
The Radiomics Ontology aims to cover the radiomics feature domain with a strong focus on first order, shape, textural radiomics features. In addition, in the original version. it includes classes about segmentation algorithms and imaging filters. Due to a recent collaboration with the IBSI (International Biomarkers Standardization Initiative), the ontology has been expanded (v 1.6) and it includes all the entities presented in the IBSI document. Therefore, a broad coverage of not only radiomics features, but also every entity (e.g.
Ontology
A85
The OBO Relation Ontology provides consistent and unambiguous formal definitions of the relational expressions used in biomedical ontologies.
Ontology
B84
COB brings together key terms from a wide range of OBO projects to improve interoperability.
Ontology
B77
An ontology specifies terms that are used to annotate ontology terms for all OBO ontologies. The ontology was developed as part of Information Artifact Ontology (IAO).
Ontology
B76
An ontology of information entities, originally driven by work by the Ontology of Biomedical Investigation (OBI) digital entity and realizable information entity branch.
Ontology
Inactive
D54
The upper level ontology upon which OBO Foundry ontologies are built.
Ontology
D46
An _gentle_ implementation of the Unified Foundational Ontology (UFO), which is an upper level ontology like BFO that is concerned with e.g. expressing temporal relationships between events.
Ontology
D42
A mid-level ontology for representing metadata related to NFDI resources, including individuals, organizations, projects, data portals, and more
Ontology
Inactive
D40
OBO relationship types (legacy): A ontology listed in OBO Foundry.
Ontology
D40
The Sustainable Meat Systems Ontology (SuMSO) is a domain ontology addressing meat systems sustainability. It extends Sustainability Core Ontology (SCO) and Basic Formal Ontology (BFO). Currently, SuMSO provides a representation of the core architectural features of a sustainable meat system, focusing on cow-derived meat as an initial use case. SuMSO deals with meat in a broad sense: it contemplates the liaisons with other cow-derived materials, such as leather and bones., SuMSO is a domain of ontology, representing meat systems sustainability.
Ontology
E38
The Graphic Descriptor Ontology (GDO) is intended for use in describing graphics that represent the form of objects. It uses the language of visual communication, illustration, and technical drawing. The GDO is rooted in the Basic Formal Ontology (BFO) and uses several classes from the Information Entity Ontology of the Common Core Ontologies as a mid-level ontology. [from https://gdo.endlessforms.info/about]
Ontology
E34
This document is an up-to-date specification of all metadata terms maintained by the Dublin Core Metadata Initiative, including properties, vocabulary encoding schemes, syntax encoding schemes, and classes.
Ontology
E32
This Ontology is the representation of semantic model XUnternehmen.Kerndatenmodell based on Basic Formal Ontology (BFO).
Ontology
E29
The Solid Terms vocabulary defines terms referenced in Solid specifications.
Ontology
E28
The midlevel energy ontology (MENO) is a BFO-based midlevel ontology. It comprises the concepts for energy qualities, energy-based dispositions and energy-driven transformation and transfer processes and their interrelations. It has the goal to provide an upper level structure for these concepts for energy-related domain ontologies.
Ontology
E26
This is the stable version of the full-notch creep test ontology (OntoFNCT) that ontologically represents the full-notch creep test. OntoFNCT has been developed in accordance with the corresponding test standard ISO 16770:2019-09 Plastics - Determination of environmental stress cracking (ESC) of polyethylene - Full-notch creep test (FNCT). The OntoFNCT provides conceptualizations that are supposed to be valid for the description of full-notch creep tests and associated data in accordance with the corresponding test standard.
Ontology
E25
SCO is a middle-level ontology, representing the major theoretical challenges to sustainability: 1) The polysemy of the term sustainability. 2) The relationship between sustainability and sustainable development. 3) The complexity underlying sustainability. SCO aims to play a pivotal role in harmonizing and integrating top-level and domain ontologies regarding sustainability.
Ontology
E24
GFO-core contains the core GFO entities and serves as a common basis for both GFO variants (light and full). For some use cases, it may be sufficient to use GFO-core alone as a kind of minimal top-level ontology.
Ontology
E24
GFO-light contains some simplifications compared to the full version of General Formal Ontology (GFO) and is designed as a framework for the efficient development and foundation of domain/application ontologies.
Ontology
E22
The NFDI4DataScience ontology (nfdi4dso) is an ontology describing various resources all resources (datasets, data providers, persons, projects and other entities) within the domain of NFDI4DataScience. nfdi4dso is a module that builds upon the [NFDIcore Ontology](https://ise-fizkarlsruhe.github.io/nfdicore/2.0.0/) and maintains alignment with the Basic Formal Ontology (BFO). [adapted from homepage]
Ontology
E21
BFO/IOF-Core conformant ontology of equipment classes for petroleum production plants.
Ontology
E20
Declarations for the KEE-owned classes, properties, and registered-legacy controlled values retained by the KEE v0.11.0 baseline. This document declares and defines terms; it is not a foundational ontology, and it introduces no semantics beyond the specification and the term registry it is generated from.
Ontology
E18
The Experimental Research Ontology (ERO) is a small ontology that models some fundamental aspects of data creation in experimental research. ERO is aligned with several upper ontologies, including BFO, IAO, OBI, and SOSA. ERO enables the characterization of different types of experiments by specifying different methodologies and collections of parameters. Methodology specifications may include, e.g., research objectives, experiment setups and procedures, success criteria, or saftey regulations.
Ontology
Inactive
E13
The General Formal Ontology is a top-level ontology for conceptual modeling, which is being constantly further developed by Onto-Med. It includes elaborations of categories like objects, processes, time and space, properties, relations, roles, functions, facts, and situations. Moreover, we are working on an integration with the notion of levels of reality in order to more appropriately capture entities in the material, mental, and social areas.
Vocabulary
E12
This ontology was designed to conceptualize symbolic meanings following Baudrillard's Simulacra and Simulation theory. Symbols, their meaning, the context in which the symbolic meaning (or simulation) exists and the source of the simulation are linked to a N-ary Simulation Class.
Vocabulary
E9
The DBpedia ontology provides the classes and properties used in the DBpedia data set.
Vocabulary
E8
Erlangen CRM / OWL - An OWL DL 1.0 implementation of the CIDOC Conceptual Reference Model, based on: Nick Crofts, Martin Doerr, Tony Gill, Stephen Stead, Matthew Stiff (eds.): Definition of the CIDOC Conceptual Reference Model (http://cidoc-crm.org/).
Vocabulary
E8
The goal of this ontology design pattern is to characterise a subject or group of subjects of interest by assigning qualifiable or quantifiable attributes or characteristics.
Vocabulary
E6
The generic BBC ontology for people, places,events, organisations, themes which represent things that make sense across the BBC. This model is meant to be generic enough, and allow clients (domain experts) link their own concepts
Vocabulary
E6
This ontology offers OWL-Lite definition for object list. It is a restricted version of OWL-S ObjectList
Vocabulary
E6
The DOLCE+DnS Ultralite ontology. It is a simplification of some parts of the DOLCE Lite-Plus library (cf. http://www.ontologydesignpatterns.org/ont/dul/DLP397.owl)
Vocabulary
E6
An ontology of information objects, encodings and realizations, as a plugin to DOLCE-Ultralite
Vocabulary
E6
The PROTON Top module represents the most general classes
Vocabulary
E6
Upper-level ontology with extensions to handle Linked Open Data (LOD)
Vocabulary
E4
OpenVocab is a community maintained vocabulary intended for use on the Semantic Web, ideal for properties and classes that don't warrant the effort of creating or maintaining a full schema. OpenVocab allows anyone to create and modify vocabulary terms using their web browser.
Vocabulary
E3
The Common European Research Information Format (CERIF) Ontology Specification provides basic concepts and properties for describing research information as semantic data.
Vocabulary
E3
An ontology to tie classes and properties to SKOS concepts
Vocabulary
E3
Data Reference Model: A metamodel for government data. A vocabulary listed in Linked Open Vocabularies (LOV).
Vocabulary
E3
UMBEL provides a general vocabulary of classes and predicates for describing domain ontologies, with the specific aim of promoting interoperability with external datasets and domains.
Ontology
B76
The Ontology for General Medical Science (OGMS) is an ontology of entities involved in a clinical encounter. OGMS includes very general terms that are used across medical disciplines, including: 'disease', 'disorder', 'disease course', 'diagnosis', 'patient', and 'healthcare provider'. OGMS uses the Basic Formal Ontology (BFO) as an upper-level ontology. The scope of OGMS is restricted to humans, but many terms can be applied to a variety of organisms.
Vocabulary
D42
gist is a minimalist upper ontology created by Semantic Arts.
Vocabulary
E31
Unified Code for Units of Measure (UCUM) is a code system intended to include all units of measures being contemporarily used in international science, engineering, and business.
Vocabulary
E12
A metadata model for Dublin Core metadata
Vocabulary
E11
Specification of the metadata used to describe models in the OntoUML/UFO Catalog.
Vocabulary
E7
A content ontology pattern that encodes a basic semiotic theory, by reusing the situation pattern. The basic classes are: Expression, Meaning, Reference (the semiotic triangle), LinguisticAct (for the pragmatics), and Agent. A linguistic act is said to be context for expressions, with their meanings and references, and agents involved. Based on this pattern, several specific linguistic acts, such as 'tagging', 'translating', 'defining', 'formalizing', etc. can be defined, so constituting a formal vocabulary for a pragmatic web.
Vocabulary
E6
The Context Description module includes models for the context of a cultural property, in a broad sense: agents (e.g.: author, collector, copyright holder), objects (e.g.: inventories, bibliography, protective measures, other cultural properties, collections etc.), activities (e.g.: surveys, conservation interventions), situations (e.g.: commission, coin issuance, estimate, legal situation) related, involved or involving the cultural property.
Vocabulary
E6
The Denotative Description module encodes the characteristics of a cultural property, as detectable and/or detected during the cataloguing process and measurable according to a reference system. Examples include measurements e.g. length, constituting materials e.g. clay, employed techniques e.g. melting, conservation status e.g. good, decent, bad.
Vocabulary
E6
ISO 37120 – Sustainable Development and Resilience of Communities – Indicators for City Services and Quality of Life (under TC268) http://ontology.eil.utoronto.ca/ISO37120.html This OWL file defines a class for each indicator defined in the ISO 37120 standard. Names for each indicator are provided. Text definitions are provided only for Economy, Education and Energy indicators, due to copyright restrictions imposed by ISO. This file is meant to provide a single URI for each indicator.
Vocabulary
E6
MSO-EM is a system of ontologies for documenting the knowledge status of models and data; the aim is to make models and data explainable-AI-ready (XAIR).
Vocabulary
E4
This ontology defines the most abstract concepts and properties that are needed to semantically manage resource within federated infrastructures
Vocabulary
E3
The Data Value Vocabulary (DaVe) is an extensible core vocabulary that allows user to use custom data value dimensions and metrics to characterise data value in a specific context. This flexibility allows for the comprehensive modelling of data value. As a data value model, DaVe allows users to monitor data value as it occurs within a data exploitation or value creation process (data value chain)
Vocabulary
Inactive
E2
LIME (LInguistic MEtadata) is a vocabulary for expressing linguistic metadata about linguistic resources and linguistically grounded datasets.
