Posts Tagged ‘linked open data’
If you’re interested in Linked Data, no doubt you’re planning to listen in on next week’s Semantic Web Blog webinar, Getting Started With The Linked Data Platform (register here), featuring Arnaud Le Hors, Linked Data Standards Lead at IBM and chair of the W3C Linked Data Platform WG and the OASIS OSLC Core TC. It also may be on your agenda to attend this month’s Semantic Web Technology & Business Conference, where speakers including Le Hors, Manu Sporny, Sandro Hawke, and others will be presenting Linked Data-focused sessions.
In the meantime, though, you might enjoy reviewing the results of the LOD2 Project, the European Commission co-funded effort whose four-year run, begun in 2010, aimed at advancing RDF data management; extracting, creating and enriching structured RDF data; interlinking data from different sources; and authoring, exploring and visualizing Linked Data. To that end, why not take a stroll through the recently released Linked Open Data – Creating Knowledge Out of Interlinked Data, edited by LOD2 Project participants Soren Auer of the Institut für Informatik III Rheinische Friedrich-Wilhelms-Universität; Volha Bryl of the University of Mannheim, and Sebastian Tramp of the University of Leipzig?
Earlier this year The Semantic Web Blog reported that the Getty Research Institute has released the Art & Architecture Thesaurus (AAT) as Linked Open Data. One of the external advisors to its work was Vladimir Alexiev, who leads the Data and Ontology Management group at Ontotext and works on many projects related to cultural heritage.
Ontotext’s OWLIM family of semantic repositories supports large-scale knowledge bases of rich semantic information, and powerful reasoning. The company, for example, did the first working implementation of CIDOC CRM search; CIDOC CRM is one of these rich ontologies for cultural heritage.
We caught up with Alexiev recently to gain some insight into semantic technology’s role in representing the cultural heritage sphere. Here are some of his thoughts about why it’s important for cultural institutions to adopt Linked Open Data and semantic technologies to enhance our digital understanding of cultural heritage objects and information:
Ikuya Yamada, co-founder and CTO of Studio Ousia, the company behind Linkify – the technology to automatically extract certain keywords and add intelligent hyperlinks to them to accelerate mobile search – recently sat down with The Semantic Web Blog to discuss the company’s work, including its vision of Semantic AR (augmented reality).
The Semantic Web Blog: You spoke at last year’s SEEDS Conference on the subject of linking things and information and the vision of Semantic AR, which includes the idea of delivering additional information to users before they even launch a search for it. Explain your technology’s relation to that vision of finding and delivering the information users need while they are consuming content – even just looking at a word.
Yamada: The main focus of our technology is extracting accurately only a small amount of interesting keywords from text [around people, places, or things]. …We also develop a content matching system that matches those keywords with other content on the web – like a singer [keyword] with a song or a location [keyword] with a map. By combining keyword extraction and the content matching engine, we can augment text using information on the web.
Ivan Herman Discusses Lead Role At W3C Digital Publishing Activity — And Where The Semantic Web Can Fit In Its Work
There’s a (fairly) new World Wide Web Consortium (W3C) activity, the Digital Publishing Activity, and it’s headed up by Ivan Herman, formerly the Semantic Web Activity Lead there. That activity was subsumed in December by the W3c Data Activity, with Phil Archer taking the role as Lead (see our story here).
Begun last summer, the Digital Publishing Activity has, as Herman describes it, “millions of aspects, some that have nothing to do with the semantic web.” But some, happily, that do – and that are extremely important to the publishing community, as well.
Dandelion, the service from SpazioDati whose goal is to delivering linked and enriched data for apps, has just recently introduced a new suite of products related to semantic text analysis.
Its dataTXT family of semantic text analysis APIs includes dataTXT-NEX, a named entity recognition API that links entities in the input sentence with Wikipedia and DBpedia and, in turn, with the Linked Open Data cloud and dataTXT-SIM, an experimental semantic similarity API that computes the semantic distance between two short sentences. TXT-CL (now in beta) is a categorization service that classifies short sentences into user-defined categories, says SpazioDati.CEO Michele Barbera.
“The advantage of the dataTXT family compared to existing text analysis’ tools is that dataTXT relies neither on machine learning nor NLP techniques,” says Barbera. “Rather it relies entirely on the topology of our underlying knowledge graph to analyze the text.” Dandelion’s knowledge graph merges together several Open Community Data sources (such as DBpedia) and private data collected and curated by SpazioDati. It’s still in private beta and not yet publicly accessible, though plans are to gradually open up portions of the graph in the future via the service’s upcoming Datagem APIs, “so that developers will be able to access the same underlying structured data by linking their own content with dataTXT APIs or by directly querying the graph with the Datagem APIs; both of them will return the same resource identifiers,” Barbera says. (See the Semantic Web Blog’s initial coverage of Dandelion here, including additional discussion of its knowledge graph.)
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