Linked Data

Google Releases Linguistic Data based on NY Times Annotated Corpus

Photo of New York Times Building in New York City

Dan Gillick and Dave Orr recently wrote, “Language understanding systems are largely trained on freely available data, such as the Penn Treebank, perhaps the most widely used linguistic resource ever created. We have previously released lots of linguistic data ourselves, to contribute to the language understanding community as well as encourage further research into these areas. Now, we’re releasing a new dataset, based on another great resource: the New York Times Annotated Corpus, a set of 1.8 million articles spanning 20 years. 600,000 articles in the NYTimes Corpus have hand-written summaries, and more than 1.5 million of them are tagged with people, places, and organizations mentioned in the article. The Times encourages use of the metadata for all kinds of things, and has set up a forum to discuss related research.”

The blog continues with, “We recently used this corpus to study a topic called “entity salience”. To understand salience, consider: how do you know what a news article or a web page is about? Reading comes pretty easily to people — we can quickly identify the places or things or people most central to a piece of text. But how might we teach a machine to perform this same task? This problem is a key step towards being able to read and understand an article. One way to approach the problem is to look for words that appear more often than their ordinary rates.”

Read more here.

Photo credit : Eric Franzon

Getty Releases More Linked Open Data: Thesaurus of Geographic Names

Linked Open Data - Getty VocabulariesLast winter, SemanticWeb reported that the Getty Research Institute had released the first of four Getty vocabularies as Linked Open Data. Recently, the Getty revealed that it had unveiled its second. James Cuno wrote, “We’re delighted to announce that the Getty Research Institute has released the Getty Thesaurus of Geographic Names (TGN)® as Linked Open Data. This represents an important step in the Getty’s ongoing work to make our knowledge resources freely available to all. Following the release of the Art & Architecture Thesaurus (AAT)® in February, TGN is now the second of the four Getty vocabularies to be made entirely free to download, share, and modify. Both data sets are available for download at vocab.getty.edu under an Open Data Commons Attribution License (ODC BY 1.0).”

Read more

Yahoo Labs Hopes to Change the Future of Content Consumption

yahooDerrick Harris of GigaOM reports, “When it comes to the future of web content… Yahoo might just have the inside track on innovation. I spoke recently with Ron Brachman, the head of Yahoo Labs, who’s now managing a team of 250 (and growing) researchers around the world. They’re experts in fields such as computational advertising, personalization and human-computer interaction, and they’re all focused on the company’s driving mission of putting the right content in front of the right people at the right time. However, Yahoo Labs’ biggest focus appears to be on machine learning, a discipline that can easily touch nearly every part of a data-driven company like Yahoo. Labs now has a dedicated machine learning group based in New York; some are working on what Brachman calls ‘hardcore science and some theory,’ while others are building a platform that will open up machine learning capabilities across Yahoo’s employee base.” Read more

New Opps For Libraries And Vendors Open Up In BIBFRAME Transition

semtechbiz-10th-125sqOpportunities are opening up in the library sector, both for the institutions themselves and providers whose solutions and services can expand in that direction.

These vistas will be explored in a session hosted by Kevin Ford, digital project coordinator at the Library of Congress at next week’s Semantic Technology & Business conference in San Jose. The door is being opened by the Bibliographic Framework Initiative (BIBFRAME) that the LOC launched a few years ago. Libraries will be moving from the MARC standards, their lingua franca for representing and communicating bibliographic and related information in machine-readable form, to BIBFRAME, which models bibliographic data in RDF using semantic technologies.

Read more

Symplectic Becomes the First DuraSpace Registered Service Provider for the VIVO Project

vivoResearch Information recently reported, “Symplectic Limited, a software company specialising in developing, implementing, and integrating research information systems, has become the first DuraSpace Registered Service Provider (RSP) for the VIVO Project. VIVO is an open-source, open-ontology, open-process platform for hosting information about the interests, activities and accomplishments of scientists and scholars. VIVO aims to support open development and integration of science and scholarship through simple, standard semantic web technologies.” Read more

A Look At LOD2 Project Accomplishments

lod2pixIf 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?

Read more

PredictionIO Raises $2.5M for Open Source Machine Learning Platform

predChristopher Tozzi of The VAR Guy reports, “PredictionIO, the open source machine learning platform, has received a big boost with the announcement of $2.5 million in seed funding, which it plans to use to make its automated data interpretation and prediction platform widely available to open source developers. PredictionIO’s goal is to make it easy for developers and companies of all sizes to integrate machine learning —i.e., software that can interpret data intelligently to make automated decisions and predictions—into their products. ‘PredictionIO aims to be the Machine Learning server behind every application,’ according to the company. ‘Building Machine Learning in software will be as common as search soon with PredictionIO’.” Read more

LODLAM Training Day at Semantic Technology & Business Conference

LODLAM: LinkedOpen Data in Libraries, Archives, and MuseumsAmong the many exciting activities at the 10th Annual Semantic Technology & Business Conference (#SemTechBiz) is the partnership with the Linked Open Data in Libraries Archives, and Museums (LODLAM) Community. On Tuesday, August 19, 2014, LODLAM will hold a full day of trainings at the SemTechBiz Conference in San Jose, California.  Registration information is available here.

We spoke to Jon Voss, Co-Founder of the International LODLAM Summit, about the Training Day:

SemanticWeb.com: What is the LODLAM Training Day?

Photo of Jon VossJon Voss: The LODLAM Training Day is an all-day, hands-on workshop led by practitioners of Linked Open Data in libraries, archives and museums from around the world.

SW: What can people expect to learn?

JV: We’ve broken the day down into two sections, basically: publishing data and reusing data.  The first part of the day we’ll look at ways that libraries, archives and museums are putting massive amounts of structured data online for the public good, and what techniques and tools you can use to do it.  The second part of the day we’ll be looking at using this data in different ways, how to use SPARQL queries, how to build data into other mashups, how to use open datasets to improve your own data, etc.
Read more

Introduction to: Linked Data Platform

Nametag: Hello, my name is Linked Data PlatformIn its ongoing mission to lead the World Wide Web to its full potential, the W3C recently released the first specification for an entirely new kind of system. Linked Data Platform 1.0 defines a read-write Linked Data architecture, based on HTTP access to web resources described in RDF. To put that more simply, it proposes a way to work with pure RDF resources almost as if they were web pages.

Because the Linked Data Platform (LDP) builds upon the classic HTTP request and response model, and because it aligns well with things like REST, Ajax, and JSON-LD, mainstream web developers may soon find it much easier to leverage the power and benefits of Linked Data. It’s too early to know how big of an impact it will actually make, but I’m confident that LDP is going to be an important bridge across the ever-shrinking gap between todays Web of hyperlinked documents and the emerging Semantic Web of Linked Data. In today’s post, I’m going to introduce you to this promising newcomer by covering the most salient points of the LDP specification in simple terms. So, let’s begin with the obvious question…

 

What is a Linked Data Platform?

A Linked Data Platform is any client, server, or client/server combination that conforms in whole or in sufficient part to the LDP specification, which defines techniques for working with Linked Data Platform Resources over HTTP. That is to say, it allows Linked Data Platform Resources to be managed using HTTP methods (GET, POST, PUT, etc.). A resource is either something that can be fully represented in RDF or otherwise something like a binary file that may not have a useful RDF representation. When both are managed by an LDP, each is referred to as a Linked Data Platform Resource (LDPR), but further distinguished as either a Linked Data Platform RDF Source (LDP-RS) or a Linked Data Platform Non-RDF Source (LDP-NR).

Read more

Spiderbook’s SpiderGraph: Linking Datasets To Help You Sell Better

spiderpix1Startup Spiderbook, which is building a linked dataset of companies and their partners, customers, suppliers, and people involved in those deals, has recently closed its seed round for $1 million. The next-generation sales intelligence company was co-founded by CEO Alan Fletcher, who was a vp of product engineering, IT and operations at Oracle, and Aman Naimat, who has been working in the realm of CRM software since he was 19 years old and also has a background in natural language processing. Along with other core members of the team, the company puts natural language processing and machine learning technology to work to help sales people better connect the dots that explain business relationships, extracting information from unstructured text to sell more effectively.

State-of-the-art CRM, says Naimat, by itself doesn’t help salespeople sell. Since the days of Salesforce, which he worked on at IBM and Oracle, it has remained the same thing, he says, “just evolving with better technology. But basically it is an internal-facing administration tool to give management visibility, not to help a salesperson sell or create business relationships.”

Built from billions of data elements extracted from everything from SEC filings to press releases to blogs to Facebook posts, Spiderbook’s SpiderGraph is taking on that challenge, starting with the goal of helping salespeople understand who is the right contact to talk to, how he or she can meet that person (through shared contacts, for instance), and who competitors are, including those providing technology or other products already in use at the company. “We have created a graph of customers, competition, and suppliers for every company that is all interconnected,” he says.

Read more

NEXT PAGE >>