Victor Saquicela

GeoLinked data and INSPIRE through an application case

In this paper we present the process that has been followed for the development of an application that makes use of several heterogeneous Spanish public datasets that are related to three themes of INSPIRE Directive, specifically Administrative Units, Hydrography, and Statistical Units. Our application aims at analysing existing relations between the Spanish coastal area and different statistical variables such as population, unemployment, dwelling, industry, and building trade. Besides providing methodological guidelines for the generation, publishing and exploitation of Linked Data from such datasets, we provide an important innovation with respect to other similar processes followed in other initiatives by dealing with the geometrical information of features.

Geographical linked data: a Spanish use case

We present the process that has been followed for the development of an application that makes use of several heterogeneous Spanish public datasets that are related to administrative, hydrographic, and statistical domains. Our application aims at analysing existing relations between the Spanish coastal area and different statistical variables such as unemployment, population, dwelling, industry, and building trade. Moreover, we provide an important innovation with respect to other similar processes followed in other initiatives by dealing with the geometrical information of features.

Lightweight semantic annotation of geospatial REST ful services

RESTful services are increasingly gaining traction over WS-* ones. As with WS-* services, their semantic annotation can provide benefits in tasks related to their discovery, composition and mediation. In this paper we present an approach to automate the semantic annotation of RESTful services using a cross-domain ontology like DBpedia, domain ontologies like GeoNames, and additional external resources (suggestion and synonym services). We also present a preliminary evaluation in the geospatial domain that proves the feasibility of our approach in a domain where RESTful services are increasingly appearing and highlights that it is possible to carry out this semantic annotation with satisfactory results.

Enriching Electronic Program Guides using semantic technologies and external resources

Electronic Program Guides (EPGs) describe broadcast programming information provided by TV stations. However, users may obtain more information when these guides have been enriched. The main contribution of this work is to present an automation process for EPGs information enrichment through the use of semantic technologies and external resources. Among the several resources involved in the enrichment process, the following can be mentioned : ontologies, web services, semantic repositories and natural language processing techniques.

An automatic method for the enrichment of DICOM metadata using biomedical ontologies

This work is a novel contribution for enriching medical images using semantic annotations with a strategy for unifying different ontologies and instances of DICOM medical files. We present the L-MOM library (Library for Mapping of Ontological Metadata) as a tool for making an automatic mapping between instances of DICOM medical files and different medical ontologies (e.g., FMA, RadLex, MeSH). The main contributions are: i) the domain independent L-MOM library which is able to integrate DICOM metadata with ontologies from different domains; ii) a strategy to automatically annotate DICOM data with universally accepted medical ontologies, and provide values of similarity between ontologies and DICOM metadata; and iii) a framework to traverse ontological concepts that characterized clinical studies of patients registered in the framework catalog.

Interlinking Geospatial Information in the Web of Data

There is an increasing presence of geospatial datasets in the Linked Open Data cloud. However, these datasets are published like data silos and the value of the Web of Data depends, among other properties, on the amount and quality of links between data sources. One of the most overlooked problems to date in the linking process is to ensure that two different resources (identified with URIs) are actually referring to the same physical thing, that is, the co-reference problem. In this paper we present a co-reference resolution approach that is composed of a set of heuristics for interlinking geospatial Linked Data. We have used these heuristics to connect resources from GeoLinkedData.es and DBpedia.

Semantic annotation of RESTful services using external resources

Since the advent of Web 2.0, RESTful services have become an increasing phenomenon. Currently, Semantic Web technologies are being integrated into Web 2.0 services for both to leverage each other strengths. The need to take advantage of data available in RESTful services in the scope of Semantic Web evidences the difficulties to cope with syntactic and semantic description of the services. In this paper we present an approach to tackle the problem of automatic the semantic annotation of RESTful services using a cross-domain ontology, a semantic resource (DBpedia) and additional external resources (suggestion and synonyms services) to annotate the parameters of the RESTful services. We also present a preliminary evaluation that proves the feasibility of our approach and highlights that it is possible to carry out this semantic annotation with satisfactory results.

RDF-ization of DICOM medical images towards linked health data cloud

This paper proposes a novel strategy for semantifying DICOM medical images (RDF-ization) automatically. We define an architecture that involves processes for extracting, anonymizing, and serializing metadata comprised in DICOM medical images into RDF/XML. These processes allow for semantically enriching and sharing the metadata of DICOM medical files through the Linked Health Data cloud. Thereby providing enhanced query capabilities with respect to the ones offered by current PACS environments, while exploiting all advantages of the Linking Open Data (LOD) cloud and SemanticWeb technologies.

Semantic Recommender Systems for Digital TV: From Demographic Stereotyping to Personalized Recommendations

Compared to analog transmissions, Digital Television (DTV) standards allows a higher number of available TV stations and consequently, a larger entertainment offer. In this context, Recommender Systems (RS) support users in choosing entertainment content by narrowing their options to a reduced set based on their preferences an interests. However, new users or those having incomplete profiles prevent the system to produce accurate recommendations, which is more noticeable in early stages of the RS. This paper proposes the use of a demographic stereotyping approach based on minimal user attributes acquired during user registration. Furthermore, we propose an experimental procedure that can be used to compare the system accuracy for the created stereotypes and for users making extensive use of the system.

Detecting Similar Areas of Knowledge Using Semantic and Data Mining Technologies

Searching for scientific publications online is an essential task for researchers working on a certain topic. However, the extremely large amount of scientific publications found in the web turns the process of finding a publication into a very difficult task whereas, locating peers interested in collaborating on a specific topic or reviewing literature is even more challenging. In this paper, we propose a novel architecture to join multiple bibliographic sources, with the aim of identifying common research areas and potential collaboration networks, through a combination of ontologies, vocabularies, and Linked Data technologies for enriching a base data model. Furthermore, we implement a prototype to provide a centralized repository with bibliographic sources and to find similar knowledge areas using data mining techniques in the domain of Ecuadorian researchers community.