Evaluación del nivel de confianza de los recursos LOD en instancias CKAN

Linked Open Data has been an initiative aimed at offering principles for the interconnection of data through machine-readable structures and knowledge representation schemes. At present, there are platforms that allow consuming LOD resources, being CKAN one of the most relevant on a large community made up of governmental organizations, NGOs, among others. However, the resources consumption lacks minimum criteria to determine their validity such as level of trust, quality, linkage and usability of the data; aspects that require a previous systematic analysis on the set of published data. To support this process of analysis and determination of the mentioned criteria, this paper has as purpose to present a method that allows analyzing the dataset current state obtained from the different instances published in CKAN, with the aim of evaluating the levels of trust that can offer from their sources. Finally, it presents results, conclusions and future work from the use of the tool for the dataset consumption belonging to certain instances ascribed to the CKAN platform.Linked Open Data ha sido una iniciativa orientada a ofrecer una serie de principios para la interconexión de datos mediante estructuras legibles por máquinas y esquemas de representación de conocimiento. En la actualidad existen plataformas que permiten consumir este tipo de recursos LOD, siendo CKAN una de las más relevantes sobre una gran comunidad conformada por organizaciones gubernamentales, ONGs, entre otras. Sin embargo, el consumo de estos recursos carece de criterios mínimos para determinar la validez de los mismos tales como: nivel de confianza, calidad, vinculación y usabilidad de los datos; aspectos que requieren de un análisis sistemático previo sobre el conjunto de datos publicados. Para apoyar este proceso de análisis y determinación de los criterios mencionados, el presente artículo tiene como propósito presentar un método que permita analizar el estado actual de los dataset obtenidos desde las distintas instancias publicadas en CKAN, con el propósito de evaluar los niveles de confianza que pueden ofrecer desde sus fuentes de origen. Finalmente, presenta resultados, conclusiones y trabajo futuro a partir del uso de la herramienta para el consumo de conjuntos de datos pertenecientes a ciertas instancias adscritas a la plataforma CKAN

Machine Learning on Linked Data, a Position Paper

The combination of linked data and machine learning is emerging as an interesting area of research. However, while both fields have seen an exponential growth in popularity in the past decade, their union has received relatively little attention. We suggest that the field is currently too complex and divergent to allow collaboration and to attract new researchers. What is needed is a simple perspective, based on unifying principles. Focusing solely on RDF, with all other semantic web technology as optional additions is an important first step. We hope that this view will provide a low-complexity outline of the field to entice new contributions, and to unify existing ones