Adolfo Lozano-Tello

Reference Ontology and (ONTO)2 Agent: The Ontology Yellow Pages

Abstract. Knowledge reuse by means of ontologies faces three important problems at present: (1) there are no standardized identifying features that characterize ontologies from the user point of view; (2) there are no web sites using the same logical organization, presenting relevant information about ontologies; and (3) the search for appropriate ontologies is hard, time-consuming and usually fruitless. To solve the above problems, we present: (1) a living set of features that allow us to characterize ontologies from the user point of view and have the same logical organization; (2) a living domain ontology about ontologies (called Reference Ontology) that gathers, describes and has links to existing ontologies; and (3) (ONTO)2 Agent, the ontology-based WWW broker about ontologies that uses Reference Ontology as a source of its knowledge and retrieves descriptions of ontologies that satisfy a given set of constraints.

BAREMO: how to choose the appropriate software component using the analytic hierarchy process

To select a software component from several similar candidates is a complex task, since each project pursues different objectives. We intend to use the Analytic Hierarchy Process in the taking of multicriteria decisions for software component reuse. This method is called BAREMO. It will help the software engineer to make estimations which will enable him/her to choose the appropriate component. The article presents a case study of the application of the method, where a project manager assesses a certain software component in order to consider its reuse in the domain of image processing.

Ontology and SWRL-Based Learning Model for Home Automation Controlling

In the present paper we describe IntelliDomo’s learning model, an ontology-based expert system able to control a home automation system and to learn user’s behaviour. This system obtains its own data from the user’s daily activities. From these data, IntelliDomo can detect behaviour periodic patterns and it can be able to generate SWRL rules that anticipate the user’s day-to-day activities. One of the main objectives IntelliDomo seeks is to be as transparent as possible for the user. The user has nothing to configure, the system learns his/her habits and anticipates his/her actions.

Ontology-based expert system for home automation controlling

In the present paper we describe the model process of an ontologybased expert system for the control of domotic installations and SWRL rules management. From the domotic system database where the attribute values of each device are stored, a background process converts these values into ontologys instances representing the system physic devices. From these instances, a software application -known as DomoRules- allows creating production rules in SWRL language that will be useful to regulate the system behaviour. IntelliDomo draws inferences from the ontology and the SWRL rules by using parameters previously indicated by the user, so the state of the physic devices in the domotic system can be modified in real time.

Selection of ontologies for the semantic web

The development of the Semantic Web has encouraged the creation of ontologies in a great variety of domains. Web users currently looking for ontologies in order to incorporate them into their systems, just use their experience and intuition. This makes it difficult for them to justify their choices. Mainly, this is due to the lack of methods that help the user to measure that the most appropriate ontologies for the new system are. To solve this deficiency, this work proposes a method which allows the users to measure the suitability of the existent ontologies, regarding the requirements of their systems.

Use of Ontologies as Representation Support of Workflows Oriented to Administrative Management

One of the applications of workflow systems is the management of administrative processes characterized by the transmission of information elements among users of an organization. Tasks contained in these processes are carried out by users responsible for confirming, modifying or adding information throughout. These processes need to be defined in workflow management systems in which all the elements are perfectly identified and are easily adaptable to changes that may arise in the sequences of tasks, in the users involved or in the data transmitted from one task to another. For this kind of processes is easier to reuse those represented in ontologies. On one hand, existing ontologies for representing some domain elements can be reused. At the same time, ontologies have an excellent expressive capacity to define tasks, their relationships and the flow control among them with precision. This paper proposes a complete model, together with the necessary software tools, for tackling this issue.

Providing RIA user interfaces with accessibility properties

Rich Internet Applications (RIAs) technologies are challenging the way in which the Web is being developed. However, from the UI accessibility point of view, these technologies pose new challenges that the Web Accessibility Initiative of the W3C is trying to solve through the use of a standard specification for Accessible Rich Internet Applications (WAI-ARIA). Currently, the introduction of properties defined in WAI-ARIA is being done in an ad-hoc manner due to the lack of models, methodologies and tools to support the design of accessible RIA UIs. In this paper we propose a semantic approach to deal with this modeling issue by extending the RUX-Method, a model-based method to build RIA UIs. The approach includes the validation process of the accessibility issues at two different levels: the UI structure and the interactions behavior.

Semantic Comparison of Ontologies Based on WordNet

The increasing use of ontologies in recent years has led to much of the information represented in them appear in differently expressed ways. When integration processes of ontologies are required within the same domain, problems arise in the correspondence between the terms that appear in ontologies involved in the process. To solve this problem, this article presents a method, which provides the user with a value of similarity between the terms of two ontologies to assist in the integration process. The method is based on the use of the lexical database defined by WordNet and the application of semantic similarity algorithms. It also introduces a software tool that carries out the implementation of this method.

Linked Data methodologies for managing information about television content: Applying Linked Data principles in the OntoTV system, in order to improve the collection processes and the way television information is accessed

OntoTV is a television information management system designed for improving the quality and quantity of the formation available in the current television platforms. In order to achieve this objective, OntoTV (1) collects the information offered by the broadcasters, (2) integrates it into a ontology-based data structure, (3) extracts extra data from alternative television sources, and (4) makes possible for the user to perform queries over the stored information. This document shows the way Linked Data methodologies have been applied in OntoTV system, and the improvements in the data consumption and publication processes that have been obtained as result. By the one hand, the possibility of accessing to information available in the Web of Data has made possible to offer more complete descriptions about the programs, as well as more detailed guides than those obtained by using classic collection methods. On the other hand, as the information of the television programs and channels are published according to the Linked Data philosophy, it becomes available not only for OntoTV clients, but also for other agents able to access Linked Data resources, who could offer the viewer more fresh and innovative features.

Analysis of Sequential Events for the Recognition of Human Behavior Patterns in Home Automation Systems

Learning users’ frequent patterns is very useful to develop real human-centered environments. By analyzing the occurrences of events over time in a home automation system, it’s possible to find periodic patterns based on action-time relationships. However, the human behavior could be better defined if it’s related to chained actions, creating action-action relationships. This work presents IntelliDomo’s learning layer, a data mining approach based on ontologies and production rules that aims to achieve those objectives. This module is able to acquire users’ habits and automatically generate production rules for behavior patterns to anticipate the user’s periodic actions. The learning layer includes new features looking for the adaptability and personification of the environment.