[u' @inproceedings{pena_resource_2015, address = {Manchester, United Kingdom}, series = {Communications in {Computer} and {Information} {Science}}, title = {Resource {Classification} as the {Basis} for a {Visualization} {Pipeline} in {LOD} {Scenarios}}, copyright = {\xa92015 Springer International Publishing Switzerland}, isbn = {978-3-319-24128-9 978-3-319-24129-6}, url = {http://link.springer.com/chapter/10.1007/978-3-319-24129-6_40}, doi = {10.1007/978-3-319-24129-6_40}, abstract = {After more than a decade since the first steps on the Semantic Web were set, mass adoption of these technologies is still an utopic goal. Machine-readable data should leverage to provide smarter summarisations of any dataset, making them comprehensible for any user, without the need for specific knowledge. The automatic generation of coherent visual representations based on Linked Open Data could stand for mass adoption of the Semantic Web\u2019s vision.', u'Our effort towards this goal is to establish a visualization pipeline, from raw semantically annotated data as input, to insightful visualizations for data analysts as output. The first steps of this pipeline need to extract the nature of the data itself through generic SPARQL queries in order to draft the structure of the data for further stages.}, language = {en}, urldate = {2015-09-21TZ}, booktitle = {Metadata and {Semantics} {Research}}, publisher = {Springer International Publishing}, author = {Pe\xf1a, Oscar and Aguilera, Unai and L\xf3pez-de-Ipi\xf1a, Diego}, editor = {Garoufallou, Emmanouel and Hartley, Richard J. and Gaitanou, Panorea}, year = {2015}, note = {00000}, keywords = {Linked Open Data, semantic web, visualization}, pages = {457--460} }']