Linked Open Data
| Linked Open Data|
(Alternative names for this keyword)
|Related keyword(s)||web of data|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of keywords|
Linked Open Data is included as keyword or extra keyword in 1 datasets, 1 tools and 3 publications.
|DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link other data sets on the web to Wikipedia data.|
|Tool||Operating System(s)||Language(s)||Programming language(s)||License||Description||Image|
|Wikidata||Wikidata aims to create a free knowledge base about the world that can be read and edited by humans and machines alike. It will provide data in all the languages of the Wikimedia projects, and allow for the central access to data in a similar vein as Wikimedia Commons does for multimedia files. Wikidata is proposed as a new Wikimedia hosted and maintained project.|
|Title||Author(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Acronym-expansion recognition based on knowledge map system||Jeong D.-H.
|Information (Japan)||English||2013||In this paper, we present a method for instance mapping and URI resolving to merge two heterogeneous resources and construct a new semantic network from the viewpoint of acronym-expansion. Acronym-expansion information extracted from two unstructured large datasets can be remapped by using linkage information between instances and measuring string similarity. Finally we evaluate the acronym discrimination performance based on the proposed knowledge map system. The result showed that noun phrase based feature selection method gained 89.6% micro averaged precision, which outperformed single noun based one by 20.1%. We found a possibility of interoperability between heterogeneous databases through the experiment of acronym-expansion recognition.||0||0|
|Bioqueries: A social community sharing experiences while querying Biological Linked Data||Garcia-Godoy M.J.
|ACM International Conference Proceeding Series||English||2012||Life Sciences have emerged as a key domain in the Linked Data community because of the diversity of data semantics and formats available by means of a great variety of databases and web technologies. Thus, it has been used as the perfect domain for applications in the Web of Data. Unfortunately, on the one hand, bioinformaticians are not exploiting the full potential of this already available technology and, on the other hand, the experts in Life Sciences have real problems to discover, understand and devise how to take advantage of these interlinked (integrated) data. In this paper, we present Bioqueries, a wiki-based portal that is aimed at community building around Biological Linked Data. This public space offers several services and a collaborative infrastructure with the objective of stimulating the generation of activity in the consumption of Biological Linked Data and therefore contributing to the deployment of the benefits of the Web of Data in this domain. This tool is not only designed to aid bioinformaticians when designing SPARQL queries to access biological databases exposed as Linked Data but also aid biologists to gain a deeper insight into the potential use of this technology. These queries published in the portal are also described and commented on natural language, to enable their use by experts in the domain but with less expertise in semantic technologies. Copyright||0||0|