J. Javier Samper

Visualization of Ontologies to Specify Semantic Descriptions of Services

The present paper describes the main characteristics and components of a tool developed for integrating the definition of profiles for semantic Web services. This tool is based on the languages DAML-S and OWL-S. It includes the ontology visualization and consistency verification which specifies the concepts that a Web service interacts with. Starting from a service description interpreted by a computer and by the means used for accessing the service, it is possible to discover which software agents use the service. The tool can generate information in different formats to represent graphic information based on XML, such as the SVG format proposed by the W3C. The tool was developed in Java language. It is being used for the visualization of ontologies and for the semantic description of services in traffic information systems. The LISITT group (Laboratorio Integrado de Sistemas Inteligentes y Tecnologias de la informacion de Trafico) developed this tool at the Robotics Institute at the University of Valencia.

An ontological infrastructure for traveller information systems

Nowadays there are vocabularies or languages able to describe concepts and data structures related to road traffic. Nevertheless, this description provides only a syntactic approach and it forgot the semantic knowledge. There not exist vocabularies or ontologies with semantic value that add significance to the vocabulary concepts and their relations. The objective to be reached of this paper is to present the research developed to build a representation scheme of a particular domain: the road traffic, with a well defined semantics. The inclusion of this semantic allows to obtain a formalized knowledge model. This model enables the development of an integrated architecture of traffic information from semantic Web services. The ontologies created in this work are used to describe and add semantic value to the current parameters of the traffic services

An approach for recommending personalized contents for homecare users in the context of health 2.0

This paper proposes a content recommendation mechanism as part of a model for implementing ubiquitous learning for supporting people with chronic diseases who are treated at home, so that they can learn more about treatments for their disease. In the proposed approach, the learning takes place based on day-to-day activities and real situations. In this case, the model supports the development of tools that can learn about the users context, based on data obtained via sensors installed on users or in their home, as well as data supplied directly by the user interface of their mobile devices, and data provided by the healthcare team, and, after that, recommend contents about their diseases.

Smart cities technologies applied to sustainable transport. Open data management

One of the objectives of the Smart Cities is the efficient and sustainable use of transport infrastructures. Sustainability is understood as the application of new technologies to minimize the loss of time and energy, and at the same time, to improve the satisfaction of citizens. Achieving this objective calls for making use of the mobility data collected from the existing transport infrastructure and services, as well as from the citizens themselves. After the data collection process, information must be stored (use of open data bases) and made accessible (available) to specialized applications and users. This paper highlights the opportunity to take advantage of emerging technologies, like the open source data platform CKAN, or to use services for data linked queries (SPARQL endpoint). As an example of application of these technologies to the transport domain, two use cases are presented: the proposed implementation of an information access point and a national project called “CONECTA”.

Proposal of an Architecture to Retrieve Information from Multiple Devices Using Matchmaking Algorithms

Semantic Web services (SWS) propose to extend the traditional Web services technologies on the way to consolidate ontologies and semantics. This makes possible the selection, the integration and the dynamic invocation of services. In this way, services are able to dynamically adapt themselves to changes without human intervention. The main purpose of this paper is to present an algorithm for matching SWS. The algorithm uses the description of the services capabilities to match the semantic values. The traditional matching has been improving using ontologies witch constitutes a step further in the matching algorithms. To implement the algorithm an agent FIPA compliant architecture has been designed and implemented. The results obtained are positives. The semantic Web services framework developed in combination with the use of the matchmaking algorithm allows to find services based on their similarities

Radio Environment Map Estimation Based on Communication Cost Modeling for Heterogeneous Networks

Radio environment maps can be a powerful tool for achieving efficient context-aware resource allocation in 5G heterogeneous networks. In this paper, we consider an heterogeneous network formed by a traditional cellular network and a wireless sensor network. The role of the wireless sensor network is to estimate the radio environment map of the cell using a geostatistical interpolation technique named Kriging. A distributed clustering algorithm was proposed in a previous work in order to decrease the complexity of the estimation. In our contribution, the clustering formation process is modified to include the communication cost as a metric to determine which nodes are included in each cluster. Simulation results show that the proposed algorithm improves the estimation quality for sparse wireless sensor networks, and preserves the network lifetime by forming clusters with an average of 5 nodes.

A low complexity distributed cluster based algorithm for spatial prediction

Radio Environment Maps (REM) can be an essential tool for numerous applications in future 5G wireless networks. In this paper, we employ a popular geo-statistical method called ordinary kriging to estimate the REM of an area covered by a eNodeB equipped with multiple antennas. Wireless sensors are distributed over the area of interest and adaptive clusters of sensors are arranged in order to improve the quality of the estimation. In this paper, we modify the distributed clustering algorithm proposed in a previous work to reduce the complexity of kriging prediction. Simulations are performed to detail the cluster formation technique and to analyze the performance in comparison with centralized and classical interpolation methods. The computational complexity is verified in terms of the number of message exchanges among the sensor nodes. Simulation results demonstrate that clusters are formed by an average of 5 sensor nodes.

Semantic traffic applications based on DatexII

In this work we demonstrate a particular use of ontologies based on the European specifications DATEXII. These specifications are designed and developed as a traffic and travel data exchange mechanism by a European task force to set up and standardise the interface between traffic control and information centres. It is the reference for applications that are developed and implemented in Europe. This language describes concepts and structures of data related to traffic, but the description is just syntactic, not semantic. Therefore the objective to be reached in this part of the research has been to develop a semantic description in order to carry out some applications like syndication and a Maps representation of DatexII data.

An ontological infrastructure for the automatic control of freight transport

Currently, freight transport carried through a country or through different countries undergoes many delays due to merchandise controls. Merchandise control is only carried out at some border posts or when the authorities demand it. Such control can be an important problem since there are different laws for the same merchandise, according to the legislation of the country and even within the same country. Nowadays there are vocabularies or languages that describe concepts and structures of data related to transport, but the description is just syntactic, not semantic. Therefore the objective to be reached in this part of the research has been to develop a representation scheme of a particular domain, freight transport, with a well defined semantics based on laws. The use of this semantic will allow us to obtain a formalized knowledge that will enable the development of a conceptual infrastructure, to exchange and control goods information between trucks and external entities.