Standard

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. An ontology for representing an indicator's supporting data plus meta information such as provenance, validity and trust can be found in: http://ontology.eil.utoronto.ca/GCI/Foundation/GCI-Foundation.owl Documentation of the ontology can be found in: http://eil.utoronto.ca/smartcities/papers/GCI-Foundation-Ontology.pdf

The Plant Ontology is a structured vocabulary and database resource that links plant anatomy, morphology and growth and development to plant genomics data.

ENVO is an ontology which represents knowledge about environments,environmental processes, ecosystems, habitats, and related entities

The Smart Applications REFerence ontology (SAREF) is intended to enable interoperability between solutions from different providers and among various activity sectors in the Internet of Things (IoT), thus contributing to the development of the global digital market.

Variation Ontology, VariO, is an ontology for standardized, systematic description of effects, consequences and mechanisms of variations. VariO allows unambiguous description of variation effects as well as computerized analyses over databases utilizing the ontology for annotation. VariO is a position specific ontology that can be used to describe effects of variations on DNA, RNA and/or protein level, whatever is appropriate.

The Experimental Factor Ontology (EFO) provides a systematic description of many experimental variables available in EBI databases, and for projects such as the GWAS catalog. It combines parts of several biological ontologies, such as UBERON anatomy, ChEBI chemical compounds, and Cell Ontology. EFO is developed by the EMBL-EBI Samples, Phenotypes and Ontologies Team (SPOT). We also add terms for external users when requested.

FALDO is the Feature Annotation Location Description Ontology. It is a simple ontology to describe sequence feature positions and regions as found in GFF3, DBBJ, EMBL, GenBank files, UniProt, and many other bioinformatics resources. The aim of this ontology is to describe the position of a sequence region or a feature. It does not aim to describe features or regions itself, but instead depends on resources such as the Sequence Ontology or the UniProt core ontolgy.

The Multi-scale Multi-step ontology (MS-O) is an ontology to describe transformation processes., Multi-scale Multi-step ontology (MS-O) est une ontologie permettant de d-crire des processus de transformation.

The Allotrope Foundation- Ontologies (-AFO-) is a curated collection of defined terms prepared by Allotrope Foundation. The AFO is collectively licensed under the Creative Commons Attribution License (CC-BY). However, the collection includes terms that are from or based on third party sources, as identified in the attribution file within the AFO software release package, as updated from time-to-time. Such individual terms may be subject to subject to other licenses specified by the source (e.g., terms from the CHMO or chemical methods ontology are also under the CC-BY, while terms based on Wikipedia entries are subject to CC BY-SA).

This document defines the HBES Information Model and a corresponding data exchange format for the Home and Building HBES Open Communication System.

ISO/IEC 29182-7:2015 provides a general overview and guidelines for achieving interoperability between sensor network services and related entities in a heterogeneous sensor network.

ISO/IEC 30140-1:2018(E) This part of ISO/IEC 30140 provides a general overview of underwater acoustic sensor networks (UWASN). It describes their main characteristics in terms of the effects of propagation variability and analyses the main differences with respect to terrestrial networks. It further identifies the specificities of UWASN and derives some specific and general requirements for these networks.