OWL 2, the new version of the Web Ontology Language, officially became a W3C standard yesterday. From the W3C press release:

“Today W3C announces a new version of a standard for representing knowledge on the Web. OWL 2, part of W3C’s Semantic Web toolkit, allows people to capture their knowledge about a particular domain (say, energy or medicine) and then use tools to manage information, search through it, and learn more from it. Furthermore, as an open standard based on Web technology, it lowers the cost of merging knowledge from multiple domains.”

Semantics for the Rest of Us: Variants of Semantic Web Languages in the Real World is a workshop that will be held at the on 26 October 2009 in Washington, DC.

We seek two kinds of submissions: full papers up to ten pages long and position papers up to five pages long. Format papers according the ISWC 2009 instructions. Accepted papers will be presented at the workshop and be part of the workshop proceedings.

Organizers:

• Lalana Kagal, Massachusetts Institute of Technology
• Ora Lassila, Nokia
• Tim Finin, University of Maryland, Baltimore County

Tom Briggs defended his PhD dissertation last month on discovering domain and range constraints in OWL and the final copy is now available.

Thomas H. Briggs, Constraint Generation and Reasoning in OWL, 2008.

The majority of OWL ontologies in the emerging SemanticWeb are constructed from properties that lack domain and range constraints. Constraints in OWL are different from the familiar uses in programming languages and databases. They are actually type assertions that are made about the individualswhich are connected by the property. Because they are type assertions these assertions can add vital information to the individuals involved and give information on how the defining property may be used. Three different automated generation techniques are explored in this research: disjunction, least-common named subsumer, and vivification. Each algorithm is compared for the ability to generalize, and the performance impacts with respect to the reasoner. A large sample of ontologies from the Swoogle repository are used to compare real-world performance of these techniques. Using generated facts is a type of default reasoning. This may conflict with future assertions to the knowledge base. While general default reasoning is non-monotonic and undecidable a novel approach is introduced to support efficient contraction of the default knowledge. Constraint generation and default reasoning, together, enable a robust and efficient generation of domain and range constraints which will result in the inference of additional facts and improved performance for a number of Semantic Web applications.

Tom Briggs will defend his dissertation, Constraint Generation and Reasoning in OWL, at Noon on Monday 17 November 2008 in ITE 325b. His work has focused on automatically computing reasonable domain and range constraints for Semantic Web properties. Here’s the abstract:

The majority of OWL ontologies in the emerging Semantic Web are constructed from properties that lack domain and range constraints. Constraints in OWL are different from the familiar uses in programming languages and databases, and are actually type assertions that are made about the individuals which are connected by the property. These assertions can add vital information to the model because they are assertions of type on the individuals involved, and they can also give information on how the defining property may be used.
    Three different automated generation techniques are explored in this research: disjunction, least-common named subsumer, and vivification. Each algorithm is compared for the ability to generalize, and the performance impacts with respect to the reasoner. A large sample of ontologies from the Swoogle repository are used to compare real-world performance of these techniques.
    Finally, using generated facts, a type of default reasoning, may conflict with future assertions to the knowledge base. While general default reasoning is non-monotonic and undecidable a novel approach is introduced to support efficient retraction of the default knowledge. Combined, these techniques enable a robust and efficient generation of domain and range constraints which will result in inference of additional facts and improved performance for a number of Semantic Web applications.

Tom’s dissertation advisor is Professor Yun Peng.

In this week’s ebiquity group meeting, Palani Kodeswaran will talk about his research in developing protocols to govern how network routers implement the Border Gateway Protocol. here’s the aabstract.

“Policies in BGP are implemented as routing configurations that determine how route information is shared among neighbors to control traffic flows across networks. This process is generally template driven, device centric, limited in its expressibility, time consuming and error prone which can lead to configurations where policies are violated or there are unintended consequences that are difficult to detect and resolve. In this work, we propose an alternate mechanism for policy based networking that relies on using additional semantic information associated with routes expressed in an OWL ontology. Policies are expressed using SWRL to provide fine-grained control where by the routers can reason over their routes and determine how they need to be exchanged. In this paper, we focus on security related BGP policies and show how our framework can be used in implementing them. Additional contextual information such as affiliations and route restrictions are incorporated into our policy specifications which can then be reasoned over to infer the correct configurations that need to be applied, resulting in a process which is easy to deploy, manage and verify for consistency.”

Our meetings are open to anyone who wants to come, so drop in if you are interested. (10am Tuesday 29 April 2008, room 325 ITE building)

Reuters has released an API for its Calais Web service. The free service discovers entities, events and relations in text and returns the results in the form of RDF data. The services use information extraction technology from ClearForest, which Reuters acquired in April 2007.

“The Calais web service automatically attaches rich semantic metadata to the content you submit – in well under a second. Using natural language processing, machine learning and other methods, Calais categorizes and links your document with entities (people, places, organizations, etc.), facts (person ‘x’ works for company ‘y’), and events (person ‘z’ was appointed chairman of company ‘y’ on date ‘x’). The metadata results are stored centrally and returned to you as industry-standard RDF constructs accompanied by a Globally Unique Identifier (GUID). Using the Calais GUID, any downstream consumer is able to retrieve this metadata via a simple call to Calais.” (link)

The semantic types it recognizes and uses in its annotations are a basic set typical of information extraction systems and include entities, facts, events and categories. See, for example, the description of the person entity type. The brief API documentation describes how to call the web services and interpret the results. As an example of the semantic metadata types supported by Calais, a preprocessed a sample content set of about 350 Business and Economic news articles from WikiNews for the year 2007 is available.

The service is free for both commercial and non-commercial purposes with a limit, but a generous one, on the number of service calls a registered developer can make in a day. A sample Java application is available that reads input from STDIN, writes output to STDOUT and takes processing parameters from a configuration file.

updates: The sample application requires Java 6 to run! Here’s an example of input and the RDF output.

Making such a service freely available on the Web has the potential to be a disruptive move. Reuters will sponsor “a number of contests and bounties for applications developed using the Calais API.” An initial “bounty” of $5,000 is offered for “A highly configurable plugin for WordPress that enriches a blog with several capabilities” based on OpenCalais.

The kind of content extraction that Calias does falls considerably short of full language understanding. However, it does represent the state of the art in scalable, domain-independent information extraction, is immediately useful, and an important step toward the ultimate goal of full NLP.

ReadWriteWeb reports that Project10X has released a 400 page report entitled Semantic Wave 2008 Report: Industry Roadmap to Web 3.0 and Multibillion Dollar Market Opportunities. The full report will set you back $3,495, but you can get a free 27 page executive summary, a $235 value. Project10X describes their Semantic Wave report as follows.

“It is the first comprehensive industry study of the next stage of internet evolution — Web 3.0. This landmark 400-page report is written for executives, developers, designers, entrepreneurs, investors, and others who want to better understand semantic technologies, the business opportunities they present, and the ways Web 3.0 will change how we use and experience the internet. The semantic wave is a “long wave” of innovation and investment that will bring fundamental shifts in paradigm, technology, and economics. Over the next decade semantic technologies will drive trillion dollar global economic expansions, transforming industries as well as our experience of the internet. ”

The report also includes a supplier directory with more than 270 companies that are researching and developing semantic technology products and services and an annotated bibliography.

Peter Patel-Schneider gave a talk on the Semantic Web at Google several weeks ago and you can see the video here. The abstract:

“The Semantic Web has been attracting considerable attention the last few years. From the point of view of Knowledge Representation, the Semantic Web affords opportunities for both research and application. However, several aspects of the Semantic Web, as it has been envisioned, cause problems from the Knowledge Representation viewpoint. Overcoming some of these problems has resulted in a more formal basis for the Semantic Web and an increase in expressive power in Semantic Web languages. Other of these problems still remain and need a new vision of the Semantic Web from a Knowledge Representation viewpoint.”

Spotted on the SWIG Scratchpad.

Sometime today the UMBC Swoogle Semantic Web search engine discovered and indexed its millionth document. Of these, about 77% are valid RDF documents, 15% HTML documents with embedded RDF and 8% appear to be RDF documents but can not be parsed.

We’ve set up a Google group, Swooglers, for users of the Swoogle Semantic Web search engine. Anyone can browse the archived and join, but only members can post messages. Replies are sent to the whole group. We’re not exactly sure what Swooglers will have to talk about, but it might be a place to share your experiences in using Swoogle, ask other users for advice, etc.

If you go to Swoogle on this Groundhog’s Day you will see a change. We’ve released a new version, Swoogle 2006, that is a nearly complete rewrite of Swoogle Classic, which now answers to Swoogle 2005. While Swoogle is currently missing some of Swoogle 2005’s features, it enjoys a cleaner and simpler model and foundation. We will be adding in some of these features as well as new ones over the next few months. Here are some of Swoogle 2006’s highlights:

• New hardware. Swoogle 2006 is running on a set of three machines: EB2 is a two processor Sun v20z with 4G of memory and runs the crawler, DBMS and development web interfaces; LOGOS is an IBM eserver runs the production web interfaces, and NATRAJ is the file server for the SW cache and archive.
• More data. Swoogle 2006 has over 850K documents in its index compared to Swoogle 2005’s 340K. The documents include about 700K RDF documents and 140K HTML documents with embedded RDF.
• Better ranking. Swoogle 2006 uses the improved ranking algorithms reported on in our ISWC 2005 paper.
• Better crawling. Swoogle 2006 now does a better job of crawling new URLs, including those submitted by people.
• Web services. Swoogle 2006 exposes a set of 17 web services, currently with simple GCI interfaces that return their results as RDF graph. Using the web services requires the use of a key, so we can track usage and possible abuses.
• RDF output. All query results, whether via a web service call or through the browser interface, are available in RDF. For browser-based queries, look for the RDF VERSION link in the upper left corner of the page.
• Simpler interface. The human web interface is simpler and cleaner.
• Cache and archive. Swoogle 2006 maintains a cache of the SW documents it finds and also keeps copies of older versions in it’s Semantic Web Archive .
• Registered user services. Swoogle 2006 has a better system for user accounts that includes a CAPCHA to keep out spambots. Anonymous users only see a limited number of query results where as registered users can see them all.
• Development wiki. We have a wiki for swoogle development ideas and discussion.

Some of the Swoogle 2005 features currently missing from Swoogle 2006 are the shopping cart and triple shop; the ontology dictionary; swoogle statistics and swoogle’s top ten. We plan to add these back into Swoogle 2006 over the next few months. Send any comments to swoogle-developers at ebiquity.umbc.edu.

Recently Cláudio Fernandes asked on several semantic web mailing lists

“Can someone point me to some huge owl/rdf files? I’m writing a owl parser with different tools, and I’d like to benchmark them all with some really really big files.”

I just ran some queries over Swoogle’s collection of 850K RDF documents collected from the web. Here are the 100 largest RDF documents and OWL documents, respectively. Document size was measured in terms of the number of triples. For this query, a document was considered to be an OWL document if it used a namespace that contained the string OWL.

Curently, the version of Swoogle you get by going to http://swoogle.umbc.edu/ is Swoogle 2. Its database has been trapped in amber since last summer, when it was corrupted, preventing us from adding new data. We put our efforts into a reimplementation, Swoogle 3, which will be released early next week. The data reported here is from Swoogle 3’s database.