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
ctag- Common Tag Vocabulary
http://commontag.org/ns#
Common Tags are references to unique, well-defined concepts, complete with metadata and their own URLs. @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
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
ntag- Nice Tag Ontology
http://ns.inria.fr/nicetag/2010/09/09/voc
NiceTag Ontology is an ontology which describes as generally as possible tags or rather tag actions understood as a speech acts occurring on the Web @en
nrv- Normative Requirements Vocabulary
http://ns.inria.fr/nrv
An OWL vocabulary for describing normative requirements. @en
pmofn- Predicate Model for Ontologies (PreMOn) - FrameNet ontology module
http://premon.fbk.eu/ontology/fn
The FrameNet module of the PreMOn ontology extends the core module for representing concepts specific to FrameNet. The modeling is based on the [FrameNet II: Extended Theory and Practice](https://framenet2.icsi.berkeley.edu/docs/r1.5/book.pdf) book. @en
pmonb- Predicate Model for Ontologies (PreMOn) - NomBank ontology module
http://premon.fbk.eu/ontology/nb
The NomBank module of the PreMOn ontology extends the core module for representing concepts specific to NomBank. The modelling is based on the NomBank Specifications. @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