Map4rdf - Faceted Browser for Geospatial Datasets

Recently we have seen a large increase in the amount of geospatial data that is being published using RDF and Linked Data principles. Eorts such as the W3C Geo XG, and most recently the GeoSPARQL initiative are providing the necessary vocabularies to pub- lish this kind of information on the Web of Data. In this context it is necessary to develop applications that consume and take advantage of these geospatial datasets. In this paper we present map4rdf, a faceted browsing tool for exploring and visualizing RDF datasets enhanced with geospatial information

datos.bne.es: A library linked dataset

We describe the datos.bne.es library dataset. The dataset makes available the authority and bibliography catalogue from the Biblioteca Nacional de España (BNE, National Library of Spain) as Linked Data. The catalogue contains around 7 million authority and bibliographic records. The records in MARC 21 format were transformed to RDF and modelled using IFLA (International Federation of Library Associations) ontologies and other well-established vocabularies such as RDA (Resource Description and Access) or the Dublin Core Metadata Element Set. A tool named MARiMbA automatized the RDF generation process and the data linkage to DBpedia and other library linked data resources such as VIAF (Virtual International Authority File) or GND (Gemeinsame Normdatei, the authority dataset from the German National Library)

Translational research combining orthologous genes and human diseases with the OGOLOD dataset

OGOLOD is a Linked Open Data dataset derived from different biomedical resources by an automated pipeline, using a tailored ontology as a scaffold. The key contribution of OGOLOD is that it links, in new RDF triples, genetic human diseases and orthologous genes, paving the way for a more efficient translational biomedical research exploiting the Linked Open Data cloud

Publishing Orthology and Diseases Information in the Linked Open Data Cloud

The Linked Data initiative offers a straight method to publish structured data in the World Wide Web and link it to other data, resulting in a world wide network of semantically codified data known as the Linked Open Data cloud. The size of the Linked Open Data cloud, i.e. the amount of data published using Linked Data principles, is growing exponentially, including life sciences data. However, key information for biological research is still missing in the Linked Open Data cloud. For example, the relation between orthologs genes and genetic diseases is absent, even though such information can be used for hypothesis generation regarding human diseases. The OGOLOD system, an extension of the OGO Knowledge Base, publishes orthologs/diseases information using Linked Data. This gives the scientists the ability to query the structured information in connection with other Linked Data and to discover new information related to orthologs and human diseases in the cloud

Transforming Meteorological Data into Linked Data

We describe the AEMET meteorological dataset, which makes available some data sources from the Agencia Estatal de Meteorología (AEMET, Spanish Meteorological Office) as Linked Data. The data selected for publication are generated every ten minutes by approximately 250 automatic weather stations deployed across Spain and made available as CSV files in the AEMET FTP server. These files are retrieved from the server, processed with Python scripts, transformed to RDF according to an ontology network (which reuses the W3C SSN Ontology), published in a triple store and visualized using Map4RDF.This work has been supported by the Spanish project myBigData (TIN2010-17060)

Integrating geographical information in the Linked Digital Earth

Many progresses have been made since the Digital Earth notion was envisioned thirteen years ago. However, the mechanism for integrating geographic information into the Digital Earth is still quite limited. In this context, we have developed a process to generate, integrate and publish geospatial Linked Data from several Spanish National data-sets. These data-sets are related to four Infrastructure for Spatial Information in the European Community (INSPIRE) themes, specifically with Administrative units, Hydrography, Statistical units, and Meteorology. Our main goal is to combine different sources (heterogeneous, multidisciplinary, multitemporal, multiresolution, and multilingual) using Linked Data principles. This goal allows the overcoming of current problems of information integration and driving geographical information toward the next decade scenario, that is, ?Linked Digital Earth.

Reusing and Re-engineering Non-ontological Resources for Building Ontologies

With the goal of speeding up the ontology development process, ontology developers are reusing as much as possible available ontological and non-ontological resources such as classification schemes, thesauri, lexicons, and folksonomies, that have already reached some consensus. The reuse of such nonontological resources necessarily involves their re-engineering into ontologies. Based on this new trend, this chapter presents a general method for re-engineering non-ontological resources into ontologies, taking into account that non-ontological resources are highly heterogeneous in their data model and contents. The method is based on the so-called re-engineering patterns, which define a procedure that transforms the non-ontological resource components into ontology representational primitives. This chapter also presents the description of a software library that implements the transformations suggested by the patterns. Finally, the chapter depicts an evaluation of the method