The First International Workshop on AAMAS Workshops (WORKSAAMAS?) has been proposed* for the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems.

* Not by us. We were out sick that day.

Peter Harsha reports that the Senate Appropriations Committee included language in the Senate version of the FY 06 Defense Appropriations bill that strips $55M from DARPA’s Cognitive Computing program, specifically “Learning, Reasoning, and Integrated Cognitive Systems”. That’s a 50% cut in the program. Peter points out that this runs counter to recent congressional sentiment that the role of computer science, especially university-led fundamental computer science, should be strengthened at DARPA.

The Semantic Web and Policy Workshop will be held at the 4th International Semantic Web Conference on 7 November 2005 in Galway, Ireland. The workshop is focused on two research areas:

• policy-based frameworks for the semantic web for security, privacy, trust, information filtering, accountability, etc.
• applying semantic web technologies in policy frameworks for application domains such as grid computing, networking, storage systems, pervasive computing and specifying agent communities norms.

In addition to presentations of nine submitted papers, Ora Lassila will give an invited talk on “Applying Semantic Web in Mobile and Ubiquitous Computing: Will Policy-Awareness Help?” and a panel of policy researchers will initiate a discussion of “The 2005 Web Policy Zeitgeist”. The proceedings is available and participants can register at the online.

DMOZ in 2005 is a short note from Phil Craven pronouncing dead the once innovative and exciting idea of a community created web directory.

“It was a fine concept, and it looked promising for a while, but the idea of DMOZ becoming the definitive catalog of the Web is gone. Improvements in the search engines eclipsed its value, and the growth rate of the Web meant that it could never achieve its goal. It began with an excellent concept, and they gave it a good shot, but it didn’t work. The continuing growth rate of the Web ensures that it can never work. It continues as a good directory of a large number of web sites, but that is all. And not many people use directories when the search engines produce such good results, and so quickly.”

One supporting fact is that there are only about 3000 active editors and a backlog of over one million submitted links for them to review.

The note caused me to wonder about what’s in store for today’s popular community created, structured knowledge source — Wikipedia. Are it’s days numbered?

Will we will see the development of a machine generated and maintained collection of articles on different topics? Topics that themselves are identified and selected by the machines, as they are in Google News

The development of such a Googlepedia would certainly qualify as a grad challenge — one that might knowledge representation, semantic web technologies, natural language understanding, natural language generation as well as the ability to form a neutral and objective view in the face of conflicting information.

So maybe Wikipedia is safe for a generation.

Brooks, T.A. (2004). “The Nature of Meaning in the Age of Google”, Information Research, 9(3) has an interesting take on things.

“The characteristic tension of the culture of lay indexing is between genuine information and spam. Google’s success requires maintaining the secrecy of its parsing algorithm despite the efforts of Web authors to gain advantage over the Googlebot. Legacy methods of asserting meaning such as the META keywords tag and Dublin Core are inappropriate in the lawless meaning space of the open Web. A writing guide is urged as a necessary aid for Web authors who must balance enhancing expression versus the use of technologies that limit the aggregation of their work.”

Was it ever so? In the world of an earlier generation, of every earlier generation, was there also this tension between those with information to promote and the mediators, publishers and gatekeepers? Does it matter that the mediator is an automaton, as foreshadowed in Metropolis?

UMBC website now publishes RSS for news and Podcasts.
(More )

Good move – subscribed!
Atleast now I will follow what should have been regularly checked by all students at UMBC.

Peter Mikhalenko has a short article on xml.com on SKOS.

“SKOS (Simple Knowledge Organization System), recently introduced by the W3C, is a model for expressing knowledge organization systems in a machine-understandable way, within the framework of the Semantic Web. The SKOS Core Vocabulary is an RDF (Resource Description Framework) application. Using RDF allows data to be linked and merged with other RDF data by Semantic Web applications. SKOS Core provides a model for expressing the basic structure and content of concept schemes, including thesauri, classification schemes, subject heading lists, taxonomies, terminologies, glossaries, and other types of controlled vocabulary.”

The Semantic Web And Policy Workshop (SWPW) will be held on 7 November 2005 in conjunction with the 4th International Semantic Web Conference in Galway, Ireland. The workshop will cover policy-based frameworks for the semantic web as well as the use of semantic web technologies in policy frameworks for other application domains such as multiagent systems, grid computing, networking, and storage systems. Submitted papers should describe original research results or articulate a position, describe an application or demonstrate a working language or system. Papers must be submitted electronically by 25 July 2005; decisions will be announced on 5 September with final camera ready copy due on 30 September.

The W3C’s Semantic Web Best Practices and Deployment Working Group aims to “provide hands-on support for developers of Semantic Web applications.” Their approach is to develop and publish notes explaining good ways to tackle common KR problems in RDF and OWL. For example, given RDF’s underlying binary relations, what are good ways to encode the n-ary relationships needed by many domains? If you are building ontologies or just trying to understand how RDF and OWL should be used, you need to take a look at these.

The working group has published three new working drafts:

• SKOS Core Guide. “SKOS Core provides a model for expressing the basic structure and content of concept schemes (thesauri, classification schemes, subject heading lists, taxonomies, terminologies, glossaries and other types of controlled vocabulary).”
• SKOS Core Vocabulary Specification. This document gives a reference-style overview of the SKOS Core Vocabulary as it stands at the time of publication. It also describes the policies for ownership, naming, persistence and change by which the SKOS Core Vocabulary is managed.
• QuickGuide to Publishing a Thesaurus on the Semantic Web. “This document describes in brief how to express the content and structure of a thesaurus, and metadata about a thesaurus, in RDF.”

These join some very useful previous working group notes and working drafts, including the following:

• Representing Classes As Property Values on the Semantic Web. “This document addresses the issue of using classes as property values in OWL and RDF Schema. It is often convenient to put a class (e.g., Animal) as a property value (e.g., topic or book subject) when building an ontology. While OWL Full and RDF Schema do not put any restriction on using classes as property values, in OWL DL and OWL Lite most properties cannot have classes as their values. We illustrate the direct approach for representing classes as property values in OWL-Full and RDF Schema. We present various alternative mechanisms for representing the required information in OWL DL and OWL Lite.”
• Defining N-ary Relations on the Semantic Web: Use With Individuals. ” In Semantic Web languages, such as RDF and OWL, a property is a binary relation; that is, it links two individuals or an individual and a value. How do we represent relations among more than two individuals? How do we represent properties of a relation, such as our certainty about it, severity or strength of a relation, relevance of a relation, and so on? The document presents ontology patterns for representing n-ary relations and discusses what users must consider when choosing these patterns.”
• Representing Specified Values in OWL: “value partitions” and “value sets”. “Modelling various descriptive “features” (also known variously as “qualities”, “attributes” or “modifiers”) is a frequent requirement when creating ontologies. For example: “size” may describe persons or other physical objects and be constrained to take the values “small”, “medium” or “large”; rank may describe military officers and restricted to a specific list of values depending on the military organisation. In OWL such descriptive features are modelled as properties whose range specifies the constraints on the values that the property can take on. This document describes two methods to represent such features and their specified values: 1) as partitions of classes; and 2) as enumerations of individuals.”

The standard view of the semantic web assumes that we will not have a single consensus ontology for a given domain, but many, each with its own base of users and applications. Thus it’s essential that we have good techniques and tools to translate information expressed in one collection of ontologies into another. One of the issues that we have not yet faced head on is that most of these mappings will probably be approximations. Here’s a good overview of the Bayesian approach to OWL ontology mapping being developed by Yun Peng and his students.

A Bayesian Methodology towards Automatic Ontology Mapping, Zhongli Ding, Yun Peng, Rong Pan, and Yang Yu, AAAI Workshop on Contexts and Ontologies, July 09, 2005.

This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. The proposed method includes four components: 1) learning probabilities (priors about concepts, conditionals between subconcepts and superconcepts, and raw semantic similarities between concepts in two different ontologies) using Naive Bayes text classification technique, by explicitly associating a concept with a group of sample documents retrieved and selected automatically from World Wide Web (WWW); 2) representing in OWL the learned probability information concerning the entities and relations in given ontologies; 3) using the BayesOWL framework to automatically translate given ontologies into the Bayesian network (BN) structures and to construct the conditional probability tables (CPTs) of a BN from those learned priors or conditionals, with reasoning services within a single ontology supported by Bayesian inference; and 4) taking a set of learned initial raw similarities as input and finding new mappings between concepts from two different ontologies as an application of our for-malized BN mapping theory that is based on evidential reasoning across two BNs.

mSpace is an interaction model to help explore relationships in information. It is a research project developed by the School of Electronics & Computer Science (ECS) at the University of Southampton.

mSpace combinds the use of information semantics and a flexible UI interface. It allows users to explore new information that they only have limited knowledge about. One problem that the mSpace project tries to address is the following:

What if you want to find something from an domain where you have a general interest but not specific knowledge? How would you find classical music you might enjoy if you don’t know what Beethoven or Berlioz sounds like? What a Sonata is? The difference between Baroque or Romantic? What do you type into Google?

You can find mSpace technical reports and demo apps here.

Getting people to agree on a single ontology has always a problem in the Semantic Web research. There are two schools of thinking. Some people believe that in the future all ontologies will be defined by some kind of standard bodies or special interest groups. Some others believe that there will be many different ontologies flowing around, and standard ontologies will emerge as the result of an “evolution” process — i.e., good ontologies will get used and bad ontologies will be forgotten.

I think the latter is more likely to happen than the former. The new tag service of the Technorati website is a good example. Here is a short description of the service from a Slashdot post:

Technorati (a search engine for blogs) has a new ‘tag’ service. If your blog tool of choice uses Categories, has a RSS/Atom feed, and pings technorati, then you’re done. If not, you can add tags via a new tag markup. The twist is that Technorati is working with Del.icio.us (a social/sharing bookmark manager website) and Flickr (a social/sharing photo web site) to read their tagged content! So Flickr pictures, Del.Ico.us bookmarks, and blog posts all on one page! Here’s an example result for the tag Toronto. There is some documentation as well. One current limitation is that there is no way to do tag intersection as with del.icio.us (i.e. http://del.icio.us/tag/toronto+food ) like http://www.technorati.com/tag/toronto+Food. Tagging (also know as Folksonomies) was the topic recently on Slashdot: Folksonomies In Del.icio.us and Flickr.”