Rights declaration in Linked Data

Linked Data is not always published with a license. Sometimes a wrong license type is used, like a license for software, or it is not expressed in a standard, machine readable manner. Yet, Linked Data resources may be subject to intellectual property and database laws, may contain personal data subject to privacy restrictions or may even contain important trade secrets. The proper declaration of which rights are held, waived or licensed is a must for the lawful use of Linked Data at its different granularity levels, from the simple RDF statement to a dataset or a mapping. After comparing the current practice with the actual needs, six research questions are posed.

Combinando Linked Data con servicios geoespaciales

La Web de Linked Data supone un nuevo paradigma que pretende explotar la Web como un espacio global de información. La aplicación de los principios de esta nueva Web a la información geoespacial superará la integración de información tradicional, logrando una articulación semántica de los datos que haga desaparecer los silos de datos presentes en las actuales Infraestructuras de Datos Espaciales. Ante esta propuesta, en este artículo se describe el trabajo desarrollado en el marco de un caso de uso utilizando una parte de los datos del SIGNA. En este caso de uso se ha llevado a cabo un proceso de generación y publicación de los mencionados datos conforme a los principios de Linked Data y estos se combinan con diversos servicios de la IDEE y CartoCiudad para explotar el componente geoespacial.

Linguistic linked data for sentiment analysis

In this paper we describe the specification of amodel for the semantically interoperable representation of language resources for sentiment analysis. The model integrates "lemon", an RDF-based model for the specification of ontology-lexica (Buitelaar et al. 2009), which is used increasinglyfor the representation of language resources asLinked Data, with Marl, an RDF-based model for the representation of sentiment annotations (West-erski et al., 2011; Sánchez-Rada et al., 2013)

Licensing patterns for Linked Data

Rights expression languages declare the permitted and prohibited actions to be performed on a resource. Along this work, six rights expression languages are compared, abstracting their commonalities and outlining their underlying pattern. Linked Data, which can be object of protection by the intellectual property laws or its access be restricted by an access control system, can be the asset in rights expressions. The requirements for a pattern for licensing Linked Data resources are listed.

LDP4j: a framework for the development of interoperable read-write linked data applications

Enterprises are increasingly using a wide range of heterogeneous information systems for executing and governing their business activities. Even if the adoption of service orientation has improved loose coupling and reusability, applications are still isolated data silos whose integration requires complex transformations and mediations. However, by leveraging Linked Data principles those data silos can now be seamlessly integrated, and this opens the door to new data-driven approaches for Enterprise Application Integration (EAI). In this paper we present LDP4j, an open souce Java-based framework for the development of interoperable read-write Linked Data applications, based on the W3C Linked Data Platform (LDP) specification.

Language resources and linked data: a practical perspective

Recently, experts and practitioners in language resources have started recognizing the benefits of the linked data (LD) paradigm for the representation and exploitation of linguistic data on the Web. The adoption of the LD principles is leading to an emerging ecosystem of multilingual open resources that conform to the Linguistic Linked Open Data Cloud, in which datasets of linguistic data are interconnected and represented following common vocabularies, which facilitates linguistic information discovery, integration and access. In order to contribute to this initiative, this paper summarizes several key aspects of the representation of linguistic information as linked data from a practical perspective. The main goal of this document is to provide the basic ideas and tools for migrating language resources (lexicons, corpora, etc.) as LD on the Web and to develop some useful NLP tasks with them (e.g., word sense disambiguation). Such material was the basis of a tutorial imparted at the EKAW’14 conference, which is also reported in the paper.

Social tags and linked data for ontology development: a case study in the financial domain

We describe a domain ontology development approach that extracts domain terms from folksonomies and enrich them with data and vocabularies from the Linked Open Data cloud. As a result, we obtain lightweight domain ontologies that combine the emergent knowledge of social tagging systems with formal knowledge from Ontologies. In order to illustrate the feasibility of our approach, we have produced an ontology in the financial domain from tags available in Delicious, using DBpedia, OpenCyc and UMBEL as additional knowledge sources.

Linked-data based domain-specific sentiment lexicons

In this paper we present a dataset componsed of domain-specific sentiment lexicons in six languages for two domains. We used existing collections of reviews from Trip Advisor, Amazon, the Stanford Network Analysis Project and the OpinRank Review Dataset. We use an RDF model based on the lemon and Marl formats to represent the lexicons. We describe the methodology that we applied to generate the domain-specific lexicons and we provide access information to our datasets.

Linked Data for sharing, discovery and re-use of Language Resources at a Web scale

Conferencia por invitación, impartida el 31 d mayo de 2014 en el Workshop on Language Technology Service Platforms: Synergies, Standards, Sharing at LREC2014

Desarrollo de herramienta de generación de Linked Data Educativo

El proyecto nace de un proyecto anterior donde se construyó un modelo para representar la información de los estudios superiores mediante una red de ontologías, proporcionando una definición común de conceptos importantes. Este proyecto consiste en desarrollar una herramienta capaz de generar datos educativos, a partir de la red de ontologías mencionadas anteriormente, siguiendo el paradigma de Linked Data [1]. La herramienta deberá extraer datos de diferentes fuentes educativas y transformará dichos datos educativos a datos enlazados (Linked Data). Para llevar a cabo esta labor se ha utilizado GATE Developer [2], es un entorno de desarrollo que proporciona un completo conjunto de herramientas gráficas interactivas para la creación, medición y mantenimiento de componentes de software para el procesamiento del lenguaje humano.---ABSTRACT---The project arises from a previous project in which a model was constructed to represent information of higher education through a network of ontologies, providing a common definition of important concepts. This project is to develop a tool capable of generating educational data from the ontology network mentioned above, following the paradigm of Linked Data [1]. The tool will extract data from different educational sources and transform said data to linked data (linked data). To carry out this work has been used GATE Developer [2]. It is a development environment that provides a comprehensive set of interactive graphical tools for creating, measuring and maintenance of software components for human language processing.

Using linked data to evaluate medical and financial outcomes of motor vehicle crashes in Connecticut.

Federal Highway Administration, Washington, D.C.

Using linked data to evaluate severity and outcome of injury by type of object struck (first object struck only) for motor vehicle crashes in Connecticut.

Federal Highway Administration, Washington, D.C.

User's guide for the Littoral Environment Observation (LEO) PC Data Retrieval and Analysis System /

"August 1994."

Analysis of head response to torso acceleration. Volume II - description of data retrieval, analysis and display software. Final report.

Transportation Systems Center, Cambridge, Mass.