Archives: May 2013

The Human Brain Project & the Future of Tech

Medical Xpress reports, “One of the major frontiers of modern science is a comprehensive understanding of the human brain and its functions to guide the development of new technologies in information and communication. In a major announcement for the globalization of science, two Japanese research organizations, the Okinawa Institute of Science and Technology Graduate University (OIST) and RIKEN, will join forces with a large European consortium on the Human Brain Project (HBP) which the European Commission has officially announced as one of two Future and Emerging Technology (FET) Flagship projects. The new project will federate international efforts to understand and simulate the human brain for the creation of new technological advances for society.” Read more

Google’s Next Steps To Build Structured Data Buy-In

Google’s Data Highlighter, its take at making it easier to let the search engine know about the structured data behind web pages, is adding more highlights. Data Highlighter (which The Semantic Web Blog originally covered here) now can teach Google the pattern of structured data about products, local businesses, articles, software applications, movies, restaurants, and TV episodes in addition to events.

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Semantic Video’s Banner Year

The BBC made use of semantic video annotation in its coverage of the 2012 Olympics

It’s fair to say that an good idea has finally “arrived” when it has left the realm of the theoretical and has become the foundation of a lot of popular tools, services, and applications.

That is surely the case with Semantic Video.

Gone are the days when internet video could best be described as a meaningless blob of content invisible to search and impossible to annotate and reuse in meaningful ways.

The past year has seen an explosion of practical (and popular) services and applications that are based upon the extraction of meaningful metadata– and often linked data– from video content.

For those of us lucky enough to view it, the BBC wowed us last July with its Olympic Coverage, broadcasting live every event of the Olympics on 24 HD streams, all accessible over the internet, with live, dynamic data and statistics on athletes.  To pull off this feat, the BBC used a custom-designed Dynamic Semantic Publishing platform which included fluid Operations’ Information Workbench to help author, curate and publish  ontology and instance data.

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New Semantic Service Aims At Diggng Out The Dollars

Digging out money. That’s the mission of VitalFlux’s ShriGB, which aims to extract meaningful insights from financial Big Data published from various financial portals and make it consumable to users with different needs, from financial brokers to job seekers.

Courtesy: Flickr/aivas14

The app right now is focusing on portals in the Indian marketplace, putting its artificial intelligence to work in its learning phase to create appropriate ontologies, taxonomies and relationships, according to founder and CEO Ajitesh Shukla. The plan is to migrate it to other markets in future. “Once the system starts getting mature, this shall be moved to the global arena,” says Shukla. “It is also understood that different countries financial portals have different ontologies and system may need to get appropriate learning to work appropriately for these countries.”

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The Rise of ‘Big Content’

Virginia Backaitis of CMS Wire recently discussed the rise of Big Content and how semantic technologies are taking a role in mining value from said content. She writes, “The first time I heard the term Big Content, I thought ‘Oh brother.’ At the time, the people who used the term “Big Content” either talked about it in terms of content that went beyond their control (i.e. viral) and said that this was a highly desirable thing OR they argued that ‘content’ was growing at a rapid clip, and that Big Data technologies, such as Hadoop, were incapable of dealing with voluminous unstructured data — that you needed something called ‘Big Content’ to do that.” Read more

Twitter, TV, and Semantic Technology

Michael Learmonth of Ad Age reports, “Twitter is attempting to deepen its links to TV — as well as skim TV ad budgets — with a series of new media deals and technology to target ads at TV viewers. Twitter’s ad pitch has been consistent over the past year: advertising on Twitter in conjunction with TV makes TV ads more effective. ‘Our perspective is everybody in digital has it wrong; they have ben going to market with an either-or proposition,” said Twitter global head of revenue Adam Bain. Twitter is a bridge to these different screens and experiences.’ Today, at an Internet Week event, the company unveiled a series of media deals and a targeting tool designed to bring TV advertisers on to Twitter.” Read more

Semantic Hack – Hackathon Update

Semantic Hack logoSemantic Hack is three days away. We’re looking forward to seeing what emerges from creative minds unearthing the hidden data of the web.

If you’re interested and have not yet registered for this free-to-attend new event, there are a few spots left, but they are going fast! Sign up today here!

Semantic Hack is attracting a great list of people interested in creating some cool hacks with Semantic Technology, and although there are some veteran thought leaders signed up, this is also an opportunity for developers and designers who have little or no experience working with Semantic Technologies to explore and learn something new. You can see who has already signed up at the Semantic Hack site.

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Introduction to: Reasoners

Name Tag: Hello, we are ReasonersReasoning is the task of deriving implicit facts from a set of given explicit facts. These facts can be expressed in OWL 2 ontologies and stored RDF triplestores. For example, the following fact: “a Student is a Person,” can be expressed in an ontology, while the fact: “Bob is a Student,” can be stored in a triplestore. A reasoner is a software application that is able to reason. For example, a reasoner is able to infer the following implicit fact: “Bob is a Person.”

Reasoning Tasks

Reasoning tasks considered in OWL 2 are: ontology consistency, class satisfiability, classification, instance checking, and conjunctive query answering.

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Big Data Trends Impacting Business

Bob Zurek of Smart Data Collective recently shared seven trends that are impacting business. One trend is added data mining and analytic functions: “Industry leaders in the big data space understand the requirements to expand the underlying analytics and statistical capabilities in their platform. This goes beyond typical analytic functions into the world of very sophisticated data mining functionality. Teradata Aster Data includes a wide variety of analytic capabilities including support for statistical, text analytics, graph, sentiment analysis and in-database PMML execution through the support of Zementis. Other companies including IBM Netezza have embedded support for the popular R statistical language as well as Matrix engine, a parallelized linear algebra package. Over time, we will see a significant expansion of these capabilities across a broad range of big data solutions. ” Read more

Late-Breaking Program Additions for Semantic Technology & Business Conference

The Semantic Technology & Business Conference begins in a few short days. If you haven’t registered yet, it’s not too late, and if you haven’t looked at the program recently, be sure to check out some of these exciting late-breaking additions…

Photo of Jason DouglasKEYNOTE:
What Google is Doing with Structured Data
Jason Douglas, Group Product Manager, Knowledge Graph, Google

Photos of Dan Brickley, R.V. Guha, Sandro HawkeHOT TOPIC PANEL:
WebSchemas: and Vocabulary Collaboration

Dan Brickley, Developer Advocate, Google
R.V. Guha, Google Fellow, Google
Sandro Hawke, W3C Technical Staff, W3C/MIT

(More panelists TBA)


Building Your SmartData Accelerator
Robert Kruse, Managing Partner, SmartDataAccelerator
Gene Mishchenko, Lead Information Architect, Standard & Poor’s Ratings Services

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