So even though we’ve had the site open for a few days (testing, tweaking, etc) let this be my offical "welcome" to the new Semantic Universe site. I’m delighted you’ve stopped by to take a look and I hope we can exceed your expectations while you’re here.
Semantic Tech & Business Conference is returning to San Francisco in June! Join us from June 3-7 for complete coverage of Big Data, Linked Data, Extreme Information Management, and Semantic Web. From breakthrough approaches to solving business problems to the big data implications of fast–evolving technologies, SemTechBiz provides you with an unparalleled interactive experience and delivers tangible business value. We're offering a special early rate when you register by February 17. Sign up now!
Jennifer Zaino
SemanticWeb.com Contributor
The semantic web has a clear place in the learning community — so says the new 2009 Horizon Report, the sixth in this collaboration between The New Media Consortium and the EDUCAUSE Learning Initiative. The NMC’s Horizon Project is a long-running qualitative research project that seeks to identify and describe emerging technologies likely to have a large impact on teaching, learning, research, or creative expression within learning-focused organizations.
The annual report includes a focus on new technologies it expects to become mainstream over the next one to five years. It foresees semantic web technologies hitting the learning organization space at the tail end of that curve, on the heels of mobile, cloud computing, geo-location, and personal web technologies. Indeed, it’s the explosion in tagging, aggregating, updating and tracking one’s own and others’ dynamic content that should have a strong hand in driving semantic web applications forward, helping users realize the connections that exist in content within the appropriate contexts.
To date, the report finds that there are not many education-specific examples of semantic-aware applications. But the members of the project who compiled the report have high hopes.
“The capability of semantic-aware applications to aid in searching and finding has implications for research, especially in light of the rate at which web content is being created,” the report notes. “Semantic-aware applications hold the potential to organize and display information embedded in our data in meaningful ways that make it easier to draw connections. Semantic-aware tools to help visualize relationships among concepts and ideas are just beginning to emerge, including mashups that not only plot data on graphs or maps, but also emphasize and illustrate conceptual links.”
Jason Ohler, writing in an article in Educause Quarterly, a journal about managing and using information resources in higher education, says the semantic web’s impact for education are “profound,” affecting knowledge construction, personal learning network maintenance, and personal educational administration. He envisions the typical Google searches done by students — with the “gazillion” hits they deliver, some relevant, many not, and all taxing the patience of the user to read beyond the first couple of dozen–being replaced with a multimedia report that draws from many sources — structured data, video, even gaming scenarios played out in virtual realities — that consists of short sections that coalesce around knowledge areas that emerged naturally from the research.
Semantic Universe and Cerebra today announced the launch of the "Semantic Universe Network", a vibrant educational and networking hub for the global semantic technology marketplace. Semantic Universe Network will be the educational and information resource for the people and companies within the high-growth semantics sector, covering the latest news, opinions, events, announcements, products, solutions, promotions and research in the industry.
Los Angeles, CA (PRWEB) January 27, 2009 — Semantic Universe and Cerebra today announced the launch of the "Semantic Universe Network", a vibrant educational and networking hub for the global semantic technology marketplace. Semantic Universe Network will be the educational and information resource for the people and companies within the high-growth semantics sector, covering the latest news, opinions, events, announcements, products, solutions, promotions and research in the industry.
According to Tony Shaw, Editor of Semantic Universe Network, "The semantic community needs a vehicle to communicate the comprehensive business applications and benefits of semantic technology, as well as a better way to connect developers, customers, entrepreneurs and investors. Semantic Universe Network will be that vehicle."
Says Brian Crook, President of Cerebra, "Today’s launch is an important milestone towards the semanticuniverse.com vision. We now have the technical framework to facilitate the growth and interaction of the community and an online sandbox for all of us to showcase, discuss and advance the enabling benefits of semantic technology."
 The semantic community needs a vehicle to communicate the comprehensive business applications and benefits of semantic technology, as well as a better way to connect developers, customers, entrepreneurs and investors. Semantic Universe Network will be that vehicle.  |
Launch editorial includes extensive new and archived material. Dozens of editorial contributors and industry bloggers are committed to participate in the Semantic Universe Network and over 30 original articles (by 30+ authors) have been published today. Among the contributors are prominent industry analysts and commentators.
Technical articles, case studies and research have been contributed by organizations including: Microsoft, SAP, Oracle, Metatomix, Zemanta, Expert System, Ontos, Collibra, NetBase, IQser, General Electric, and two dozen more. Archived content draws upon a rich media library generated from the Semantic Technology Conferences and the Semantic Report including blogs, webcasts, slide decks, video recordings, executive interviews, audio recordings, profiles, photos, press releases, product information and vendor announcements.
Charter sponsorships are now being offered to product and tool developers within the semantic sector, as well as industry participants such as venture capitalists, consulting firms, educational institutions and other services organizations.
For information about advertising and site sponsorships contact Steve Bastasini +1-415-740-5528 (steve (at) semanticuniverse (dot) com). For information about editorial participation contact Tony Shaw +1-310-337-2616 x102 (tony (at) semanticuniverse (dot) com).
About Semantic Universe:
Semantic Universe is the creator of the Semantic Technology Conference (SemTech), the world’s foremost symposium on the business of semantic technology now in its fifth year. Semantic Universe is also the creator of the Semantic Report and the Semantic Universe Webcast Series. Semantic Universe is a joint venture of Wilshire Conferences and Semantic Arts.
About Cerebra, Inc. – Cerebra is the developer of the Cerebra Server, a content matching and discovery platform combining the respective strengths of natural language processing and semantic reasoning techniques. Cerebra products augment publisher sites with relevant content and advertising delivered as small widget applications to embed maps, reviews, videos, images, products and domain content contextually into publisher web pages.
Jennifer Zaino
SemanticWeb.com Contributor
Want to understand how the semantic web applies to the enterprise arena? To get some new insight into this, Semanticweb.com recently caught up via email with Prof. Adrian Paschke, who heads up the Corporate Semantic Web project at the Free University of Berlin. The project, already started and will continue over the next few years, seeks to demonstrate how semantic web technologies will be realized in the context of corporate requirements.
The project has already published its first milestone report, available here, and plans to disclose additional information in the next few months about the projects it already has in the works.
Semanticweb.com: What was the reason for the initiation of this project last February?
Paschke: There has been intense research and development in Semantic Web technologies in the last years. Since 2004 there exists a relatively stable core of W3C standards with RDF, RDFS and OWL. Recently, the Semantic Web stack was extended by the RDF query language SPARQL and the W3C Rule Interchange Format (W3C RIF). A large number of tools, software and applications already exist in the public (Semantic) Web and first commercial services are available. Nevertheless, it is still an early technology. There are still gaps in the standards and implementations and the vision of a global machine-understandable Semantic Web will not be fulfilled in the near future due to the high requirements with respect to scalability, security, critical mass of adopters, users, and semantic data on the public Web. While the vision of a global Semantic Web remains unfulfilled in the next years, the Corporate Semantic Web approach focuses on controlled environments where these issues do not arise. Current Semantic Web tools and standards are already adequate to implement components of such Corporate Semantic Webs.
The high potential in many industrial application scenarios and the short-term practicability in closed enterprise settings was the reason to initiate the funded Corporate Semantic Web project and start a new chair addressing this topic at the Free University Berlin. Furthermore, one important long-term goal of Corporate Semantic Web research of the new working group is to widen this focus in the course of time, to develop solutions that scale to a global range, and thereby contribute to the development of the global Semantic Web.
Semanticweb.com: Why is it important to, as the web site about this project notes, establish economically beneficial adoption of Semantic Web technologies in corporate environments?
Paschke: The transition from manufacturing to information economies and the progressive globalization of markets pose new challenges to enterprises. The amount of information that companies have to produce, acquire, maintain, propagate, and use has increased dramatically over the last decades.
Nowadays, companies seek more capable approaches for gaining, managing, and utilizing knowledge, and the Semantic Web offers promising solutions. While the global Semantic Web remains an unfulfilled vision for the present, the Corporate Semantic Web idea aims at bringing semantic technologies to enterprises. The expected results are an advantage in competition for enterprises using semantic technologies. However, the Semantic Web technology has not arrived in the corporate world, yet. Incentives need to be provided to encourage in-house adoption and integration of these new Corporate Semantic Web technologies into the existing IT infrastructures, services and business processes. Decision makers on the operation, tactical and strategic IT management level need to understand the impact of this new technological approach and its adoption costs and return on investment.
Therefore, companies will have in mind the economical justifiability of the deployment of new technologies. One of the next steps in the Corporate Semantic Web project will be to develop methods for cost estimation of ontology development processes, ontology use, and ontology maintenance that are adaptable to different corporate environments.
Furthermore, methods for evaluating existing ontologies with regard to enterprise relevant usage criteria are needed. Early adopters deploying application-oriented solutions for improving their competitive advantages through enhanced knowledge management of semantically rich data will demonstrate incentives for further corporations to follow and thereby accelerate the realization of a global Semantic Web.
Semanticweb.com: Where do you foresee semantic web technologies having their greatest impact in the corporate world?
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Thanks to everyone who attended the SPARQL By Example Web cast or who has watched the archived recording of it. There was a tremendous level of enthusiasm during the one hour presentation, and as a result we did not have the chance to answer all of the excellent questions that participants submitted. Below, I’ve tried to summarize most of the unanswered (and some of the answered) questioons and provided some explanations and pointers to further information. Also, please note that due to the popularity of the first session, we’ll be holding a continuation Web cast on Thursday, January 22, at 1:00 PM EST / 10:00AM PST. During that Web cast, we’ll continue our example-driven look at some of the more advanced features of SPARQL. I hope you can join us then!
We had several questions about SPARQL endpoints. A SPARQL endpoint is any URL on the Web that implements the SPARQL protocol. Generally speaking, this means that if the URL http://example.com/sparql is a SPARQL endpoint, then we can send queries to it by issuing requests to a URL that looks like: http://example.com/sparql?query=SELECT+%3Fname+WHERE.... Note that the query itself is passed to the endpoint as a URL-encoded string.
The SPARQL protocol is defined as an abstract interface that can be implemented over HTTP GET, HTTP POST, or SOAP. (The above example would work for a SPARQL endpoint that implements the protocol over HTTP GET.) An endpoint will normally return the results of a SPARQL query using the SPARQL Query Results XML Format, a simple XML format for returning a table of variables and their values that satisfy a query. Many SPARQL endpoints also support other return formats via content negotiation, such as a JSON result format or various RDF serializations.
In the tutorial, we ran our queries by going to a Web page and pasting the queries into a form. Those Web forms are not themselves SPARQL endpoints, but when we submit the forms the queries are being submitted to SPARQL endpoints. Many public SPARQL endpoints provide this type of human-friendly form for designing, developing, and debugging SPARQL queries.
In the tutorial, we also saw two types of SPARQL endpoints in action. When we ran queries against Tim Berners-Lee’s FOAF file, we used a generic SPARQL endpoint. This type of endpoint sits somewhere on the Web and goes out to retrieve RDF data from elsewhere on the Web to run a query. Because a generic SPARQL endpoint will query against arbitrary RDF data, we must specify the URL of the graph (or graphs) to run the query against. We do this either using the input boxe provided on the human-friendly forms, or using the SPARQL FROM clause. We also saw specific SPARQL endpoints such as DBPedia and DBTune. These endpoints are hardwired to query against a fixed dataset. Because a specific SPARQL endpoint will always query against the same data, we do not need to use the FROM clause when writing queries for these endpoints.
A few participants asked questions about the interaction between SPARQL and reasoning. In other words, for example, when I write a SPARQL query to search for all mammals, will I receive results for human beings that are not also explicitly typed as mammals? The short answer is that while some SPARQL implementations do inform their results via RDFS or OWL reasoning, many do not. The SPARQL standard does not require that query results take any reasoning into account.
For a more detailed answer, please see these two answers in the SPARQL FAQ.
An insightful question cropped up a few times during the Web cast: How do we know what type of data lurks behind a SPARQL endpoint? How do we know what predicates (relationships) exist to be queried for? How do we know what types (classes, the objects of an rdf:type predicate) exist?
In many cases, we know via an out-of-band source. Perhaps a SPARQL endpoint also publishes documentation of their dataset, along the lines of the music ontology used by the DBTnue.org dataset we looked at. Other datasets build on well-known vocabularies, such as the core RDF and RDFS terms, or the common FOAF and Dublin Core vocabularies. And still other times we find ourselves writing SPARQL queries to access datasets that we (or our software applications) have created ourselves, and therefore we simply know what we want to query for with SPARQL. These out-of-band scenarios are really no different from how we know what databases, tables, and columns to query for when constructing an SQL query.
On the other hand, a significant part of the appeal of the Semantic Web in general, and of SPARQL in particular, is the ability to start with nothing but a SPARQL endpoint and to dive in and learn about the data lurking behind the endpoint. The basic mechanism by which we can do this is by writing queries that use variables to find all of the predicates and all of the types that exist in a dataset, and then to pick out interesting predicates and types and use open-ended queries to explore the structure of the data. Dean Allemang has written a blog post on this exact subject, so I’ll gladly reference his writing on using SPARQL to explore an unknown dataset.
A few quick hits here to address some lingering questions:
I’m sure there are other questions that I have not managed to address here. Please drop me a line with any other questions. You can also check out the SPARQL FAQ that I maintain. Thanks!
The evolution of the semantic web brings new possibilities to handle the information overload. This paper focuses on the motivation to integrate two applications and the usage of semantic content for information managers. Analysts and executives need to understand today the value of semantic technologies in relation to business intelligence and decision making support. There are a number of mature semantic technology categories including automatic annotation, information extraction techniques, text mining and semantic navigation and search within the content.
Jennifer Zaino
SemanticWeb.com Contributor
EveryZing — whose search-engine-optimization expertise lies in its ability to understand the semantic aspects of publishers’ content through the consistent marking up of multimedia assets — said last week that Internet TV company Revision3 is using its solutions to provide enhanced search and discovery of the site’s broadcast-quality programming.
Founded by Digg.com founders Kevin Rose and Jay Adelson, Revision3 focuses on the technology space, with video programming aimed at consumer electronic products, video games, social bookmark hot topics, and hackers (in the good sense of the word), as well as comedy, music and movies.
The Internet TV channel, just a few years old, has about 11 shows in its programming schedule, and has accumulated about 2,000 episodes in its video library to date.
“As we sat down to look at the web site and functionality for users, it was clear there was no easy way to find an episode you saw that mentioned the Nokia phone that you’re now thinking about buying, for instance,” says Ron Richards, senior director of marketing and product management at Revision3. “We can tag our video posts with metadata, and keywords, and so on, but a 45-minute episode of a TV show is not well-represented by metadata.”
In search of more state-of-the-art search technology, Richards chose EveryZing’s ezSEO and ezSearch shared-hosting solution because of its ability to convert speech to text, making it possible for users to search not just on metadata but on exact words spoken to find the episode they’re looking for. Richards says the solution will make it easier both to search on Revision3′s site for episodes that feature specific content and via search engines like Google, as well, which can crawl the tagged and indexed text output derived from the video content to make information easier to find by the public at large.
So far Revision3 has completed the first phase of the project, which encompassed making all 2000 episodes to date indexed and searchable.
“Now we are further deepening this to integrate search on every part on the site, as well as make the transcripts of text searchable so you can jump right to it in the video once you find the word you’re looking for,” says Richards.
We have used a sophisticated array of AI/Machine Learning systems in combination with statistical methods, background knowledge and expert defined rules engines, to create, entirely automatically, a structured database with high quality information. The example we have produced contains structured company records and fields for over 2 million IT and telecoms companies using data taken from their websites.
A common challenge facing today’s enterprise, its employees, and customers, is the ability to easily and effectively access corporate data and product/services-related information. To obtain the accurate and specific information needed from a vast corporate network is a daunting task, especially as data grows more complex and the workforce becomes increasingly mobile. What if we had pervasive access to it all– enabling us to make timely business decisions while continuing on with our busy days?
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