Ontologies

Research Area NLP and sentiment analysis
Authors Adam Westerski, J. Fernando Sánchez-Rada
Version https://www.gsi.upm.es/ontologies/marl/
Description Marl is a standardized data schema (also known as an ontology or vocabulary) designed to annotate and describe subjective opinions expressed on the web or in Information Systems. This document contains the description of the ontology and instructions for connecting it to descriptions of other resources.

Research Area NLP and sentiment analysis
Authors J. Fernando Sánchez-Rada
Version https://www.gsi.upm.es/ontologies/onyx/
Description Onyx is a statalized data schema (also known as an ontology or vocabulary) designed to annotate and describe the emotions expressed in user-generated content on the web or in information systems. This document describes the ontology and instructions for linking it to other resources.

Research Area NLP and sentiment analysis
Authors J. Fernando Sánchez-Rada
Version https://www.gsi.upm.es/ontologies/wnaffect/
Description WordNet-Affect is an extension of WordNet Domains. It includes a subset of synsets suitable for representing affect concepts related to a word. The SKOS taxonomy provides the WordNet-Affect categories in a semantic representation following the SKOS standard.

Research Area Big Data and Machine Learning
Authors Miguel Coronado
Version https://www.gsi.upm.es/ontologies/ewe/
Description The Evented WEb Ontology (EWE) is a standardized data schema (also known as an ontology or vocabulary) designed to describe the elements within Task Automation Services to enable interoperability of automation services. This document contains the ontology description and instructions on how to connect to descriptions of other resources.

Research Area Agents and Social Simulation
Authors Adam Westerski
Version http://purl.org/gi2mo/ns
Description The Generic Ideology and Innovation Management Ontology (Gi2MO) is a standardized data schema (also called ontology or vocabulary) designed to annotate and describe the resources gathered within Idea Management facilities. The following document contains the ontology description and instructions on how to connect it to descriptions of other resources.

Research Area Web data and semantic technologies
Authors José I. Fernández-Villamor, Carlos A. Iglesias, Mercedes Garijo
Version https://gsi.upm.es/ontologies/scraping/
Description Semantic scraping is the process in which a correspondence between web data and semantic web resources is established. An RDF model is defined to formalize this correspondence called the Scraping Ontology. The proposed vocabulary serves as a link between the HTML document and the RDF data. With this RDF model, it is possible to construct an RDF network from the HTML DOM tree of an HTML document, and to provide semantics to syntactic extractors.

Research Area NLP and sentiment analysis
Authors J. Fernando Sánchez-Rada
Version https://www.gsi.upm.es/ontologies/pearl/
Description Pearl is an ontology defined for the purpose of modeling the attributes and characteristics of a user in an intelligent environment, and relating them to contextual information. This document describes the ontology and instructions for linking it to other resources.

Research Area Web data and semantic technologies
Authors José I. Fernández-Villamor
Version https://www.gsi.upm.es/ontologies/limon/
Description The Linked Mashup ontology integrates properties and comapos that are available in component repositories on the web. Its name comes from the approach of bringing the Web of Data movement to mashup-oriented development. It allows describing mashups and their components to integrate and share mashup information, such as their classification or dependencies. This document contains the ontology description.