Onyx Ontology Specification

V1.2 - 18 July 2013

This version:	RDF/XML, HTML)
Latest version:	http://gsi.upm.es/ontologies/onyx
Previous version:	http://gsi.upm.es/ontologies/onyx/1.1 (RDF/XML, HTML)
Editors:	J. Fernando Sánchez-Rada
Authors:	J. Fernando Sánchez-Rada
Contributors:	See acknowledgements

This work is licensed under a Creative Commons Attribution License. This copyright applies to the Onyx Ontology Specification and accompanying documentation in RDF. This ontology uses W3C's RDF technology, an open Web standard that can be freely used by anyone.

Abstract

Onyx is a standardised data schema (also referred as "ontology" or "vocabulary") designed to annotate and describe the emotions expressed by user-generated content on the web or in particular Information Systems. The following document contains the description of the ontology and instructions on how to connect it with descriptions of other resources.

Introduction
Onyx ontology at a glance
Onyx ontology overview
1. Example
Cross-reference for Onyx classes and properties Classes and Properties

1 Introduction

The following specification is a formal description of metadata schema proposal that can be applied to emotions extracted from user-generated content on the Web. The goal of the following section is to provide the basic knowledge to comprehend the technical part of the specification. As such it shall introduce both Semantic Web and general topic of opinion representation and sentiment analysis.

Onyx aims to complement the Marl Ontology by providing a simple means to describe emotion analysis processes and results using semantic technologies.

1.1 Opinions on the Web and the opinion mining process

With the birth of Web 2.0 users started to provide their input and create content on mass scape about their subjective opinions related to various topics (e.g. opinions about movies). While this kind of content can be very beneficial for many different uses (e.g. market analysis or predictions) it's accurate analysis and interpretation has not been fully harnessed yet. Information left by the users is often very disorganised and many portals that enable user input leave the user added information unmoderated.

Opinion mining (often referred as sentiment analysis) is one of the attempts bring order to those vast amounts of user generated content. The domain focuses to analyse textual content using special language processing tools and as output provides a quantified judgement of the sentiments contained in the text (e.g. if the text expresses a positive or negative opinion).

Due to the complexity of the problem and attempts to provide efficient and fast tools the area can be divided into three main research directions:

document wide sentiment analysis
sentence sentiment analysis
feature-based sentiment analysis

In relation to the World Wide Web, there is a number of common uses of opinion formalisation and analysis. Firstly, it can be applied on top of search engines to find the desired content and next run it through opinion analysis software to obtain desired statistics (e.g. Swotti). Secondly, such algorithms can used within dedicated systems that use the Web to connect to particular communities and gather their opinions on very specific topics (e.g. Internet shops or review websites).

In relation to the dedicated systems (e.g. Enterprise Systems), there the community collaborative models that have proven successful in the open web are often transferred to large enterprise to enhance knowledge exchange and bring the employees together. The same opinion mining techniques can be applied in such cases to extract particular information and use it for internal statistics and to improve knowledge search across the enterprise (e.g. see use of opinion mining in Idea Management [link]).

1.2 The Semantic Web

The Semantic Web is a W3C initiative that aims to introduce rich metadata to the current Web and provide machine readable and processable data as a supplement to human-readable Web.

Semantic Web is a mature domain that has been in research phase for many years and with the increasing amount of commercial interest and emerging products is starting to gain appreciation and popularity as one of the rising trends for the future Internet.

One of the corner stones of the Semantic Web is research on inter-linkable and interoperable data schemas for information published online. Those schemas are often referred to as ontologies or vocabularies. In order to facilitate the concept of ontologies that lead to a truly interoperable Web of Data, W3C has proposed a series of technologies such as RDF and OWL. Onyx uses those technologies and the research that comes within to propose an ontology for the particular goal of describing opinions and linking them with contextual information (such as opinion topic, features described in the opinion etc.).

1.3 What is Onyx for?

The goals of the Onyx ontology to achieve as a data schema are:

enable to publish raw data about emotions in user-generated content
deliver schema that will allow to compare emotions coming from different systems (polarity, topics, features)
interconnect emotions by linking them to contextual information expressed with concepts from other popular ontologies or specialised domain ontologies

2. Onyx ontology at a glance

An alphabetical index of Onyx terms, by class (concepts) and by property (relationships, attributes), are given below. All the terms are hyperlinked to their detailed description for quick reference.

3. Onyx ontology overview

The Onyx class diagram presented below shows connections between classes and properties used for describing opinions.

Class and Properties Diagram for the Onyx Ontology (high resolution version: PNG)

3.1. Example

A very basic example below shows a single opinion annotated with Onyx metadata:

4. Cross-reference for Onyx classes and properties

Below see a comprehensive list of all Onyx classes, properties and their descriptions.

Classes and Properties (full detail)

Classes

Class: onyx:ActionTendency

ActionTendency -

Action Tendency of the emotion: a desire to behave in select communicative or important actions that are connected to a particular feeling.

Status:	unknown
Used with:	hasActionTendency

Status:	unknown
Properties include:	hasEmotionIntensity hasEmotionCategory
Used with:	hasEmotion

Status:	unknown
Domain:	EmotionExpression
Inverse property of	the anonymous defined property with the label 'hasEmotion' (Object Property)
Has inverse property	hasEmotion

Status:	unknown
Range:	xsd:float

Status:	unknown
Domain:	onyx:Emotion or owl:Thing
Range:	ActionTendency

Status:	unknown
Domain:	Emotion
Range:	xsd:float

Onyx Ontology Specification

V1.2 - 18 July 2013

Abstract

Table of Contents

Appendixes

1 Introduction

1.1 Opinions on the Web and the opinion mining process

1.2 The Semantic Web

1.3 What is Onyx for?

2. Onyx ontology at a glance

3. Onyx ontology overview

3.1. Example

4. Cross-reference for Onyx classes and properties

Classes and Properties (full detail)

Classes

Class: onyx:ActionTendency

Class: onyx:Emotion

Class: onyx:EmotionAnalysis

Class: onyx:EmotionCategory

Class: onyx:EmotionExpression

Properties

Property: onyx:algorithm

Property: onyx:algorithmConfidence

Property: onyx:appraisalProperty

Property: onyx:dimensionProperty

Property: onyx:emotionText

Property: onyx:extractedFrom

Property: onyx:hasActionTendency

Property: onyx:hasEmotion

Property: onyx:hasEmotionCategory

Property: onyx:hasEmotionIntensity

Property: onyx:source

Property: onyx:sourceText

A Changelog

2013-07-17

2013-06-27

2013-05-10

B Acknowledgements