ccsla- Service Level Agreement for Cloud Computing
http://cookingbigdata.com/linkeddata/ccsla
Service Level Agreement for Cloud Computing Services. This ontology allows to define model of SLA/SLO used in large cloud computing providers such as Amazon, Azure, etc., including terms, claims, credit, compensations, etc @en
ccp- Vocabulary for prices options in Cloud Computing Services
http://cookingbigdata.com/linkeddata/ccpricing
Simple and direct pricing ontology for Cloud Computing Services. This ontology allows to define model of prices used in large cloud computing providers such as Amazon, Azure, etc., including options for regions, type of instances, prices specification, etc. @en
va- The Visual Analytics Vocabulary
http://code-research.eu/ontology/visual-analytics
This vocabulary allows the semantic description of visual analytics applications. It is based on the RDF Data Cube Vocabulary and the Semanticscience Integrated Ontology. @en
basic- OWL representation of ISO 19103 (Basic types package)
An OWL representation of (some of) the basic types described in ISO 19103:2005, required as primitives in other ontologies based on ISO 19100 series standards @en
r4r- Relations for Reusing (R4R) Ontology
http://guava.iis.sinica.edu.tw/r4r
R4R is a light-weight ontology for representing general relationships of resource for publication and reusing. It asserts that a certain reusing context occurred and determined by its two basic relations, namely, isPackagedWith and isCitedBy. The isPackagedWith relation declares the resource is ready to be reused by incorporating License and Provenance information. The Cites relation is an exceptional to isCitedBy which occurs only two related objects cite each other at the same time. Five resource objects including article, data, code, provenance and license are major class concepts to represent in this ontology.
The namespace for all R4R terms is http://guava.iis.sinica.edu.tw/r4r/ @en
dogont- Ontology Modeling for Intelligent Domotic Environments
http://elite.polito.it/ontologies/dogont.owl
The DogOnt ontology supports device/network independent description of houses, including both controllable and architectural elements. @en
eupont- EUPont: an ontology for End User Programming of the IoT
http://elite.polito.it/ontologies/eupont.owl
EUPont is an ontology to model high level rules for Internet of Things End User Programming (IoT-EUP). @en
op- Observable properties
http://environment.data.gov.au/def/op
A general purpose ontology for observable properties. The ontology supports description of both qualitative and quantitative properties. The allowed scale or units of measure may be specified. A property may be linked to substances-or-taxa and to features or realms, if they play a role in the definition. @en
ldvm- Vocabulary for Linked Data Visualization Model
http://linked.opendata.cz/ontology/ldvm/
Vocabulary for Linked Data Visualization Model (LDVM) serves for description and configuration of components and pipelines according to LDVM @en
lsc- Linked Science Core Vocabulary
http://linkedscience.org/lsc/ns#
LSC, the Linked Science Core Vocabulary, is a lightweight vocabulary providing terms to enable publishers and researchers to relate things in science to time, space, and themes. @en
psh- Probabilistic SHACL Validation
http://ns.inria.fr/probabilistic-shacl/
An OWL vocabulary to include and exploit probabilistic information in SHACL validation reports @en
edupro- EduProgression Ontology
http://ns.inria.fr/semed/eduprogression/
The EduProgression ontology formalizes the educational progressions of the French educational system, making possible to represent the existing progressions in a standard formal model, searchable and understandable by machines (OWL). @en
nrv- Normative Requirements Vocabulary
http://ns.inria.fr/nrv
An OWL vocabulary for describing normative requirements. @en
opmo- Open Provenance Model
http://openprovenance.org/model/opmo
The Open Provenance Model is a model of provenance that is designed to meet the following requirements: (1) To allow provenance information to be exchanged between systems, by means of a compatibility layer based on a shared provenance model. (2) To allow developers to build and share tools that operate on such a provenance model. (3) To define provenance in a precise, technology-agnostic manner. (4) To support a digital representation of provenance for any 'thing', whether produced by computer systems or not. (5) To allow multiple levels of description to coexist. (6) To define a core set of rules that identify the valid inferences that can be made on provenance representation. @en