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.”

This is a good overview paper with the perspective of someone in library and information science.

Folksonomies – Cooperative Classification and Communication Through Shared Metadata, Adam Mathes, UIUC,December 2004. “This paper examines user-generated metadata as implemented and applied in two web services designed to share and organize digital media to better understand grassroots classification. … Conclusion. A folksonomy represents simultaneously some of the best and worst in the organization of information. Its uncontrolled nature is fundamentally chaotic, suffers from problems of imprecision and ambiguity that well developed controlled vocabularies and name authorities effectively ameliorate. Conversely, systems employing free-form tagging that are encouraging users to organize information in their own ways are supremely responsive to user needs and vocabularies, and involve the users of information actively in the organizational system. Overall, transforming the creation of explicit metadata for resources from an isolated, professional activity into a shared, communicative activity by users is an important development that should be explored and considered for future systems development.”

Interest in ontologies has gone down and up over the past 20 years and its been very strong in the last five years. Designing a good ontology for a complex real world topic is hard and made especially so by the usual goal that it be relatively independent of any small set of driving tasks. There are so many ways you can go wrong — too simple, too complex, too philosophical, to pragmatic, non-extensible, too big, too small, too brittle, too loose. And how do you evaluate the one you come up with? Sometimes it seems that ontological engineering requires graduate level training in way too many advanced topics — knowledge representation, logic, databases, philosophy.

While the semantic web movement hasn’t changed any of these problems, it has opened up new avenues by making this a problem by and for the web — an open, distributed, heterogeneous environment in which people and software agents create, publish, search for, combine, exchange and use information.

One interesting phenomenon is a number of sites which are using what some call folksonomies — informal tagging systems developed bottom up by their users. Examples of sites that use folksonomies include flickr, furl, del.icio.us and Google’s gmail. As a way to build an ontology, you can’t get much simpler that this — the tags form a flat one-level taxonomy of classes. You can attach a set of tags to an object (URL, picture or email message) and find objects indexed by a set of tags. What you can’t do are things like (i) define relations between tags (e.g., declare that rdf is a subtag of semanticWeb or that NYC and newYork are equivalent); (ii) form combinations of tags other than intersection (e.g., find pictures tagged as domesticatedAnimals OR pets but NOT cats); and (iii) define and use properties (e.g., this picture depicts an animal whose owner is a person with lastname=”finin”).

This is not a great leap forward for classification theory and the basic approach is quite common (e.g., see the use of faceted classifications in library science or polyclave classification systems in Biology), but what is interesting is letting a community of people develop and share folksonomies in a natural way with the hope that consensus vocabularies will naturally emerge.

Flickr, furl and del.icio.us allow you to make public your tags and tagged objects and to search over those of others, introducing an interesting social dimension. In the natural course of things, users will tend to converge around a set of tags to denote a common shared concept. This is accelerated by the fact that, for del.icio.us and furl, users are tagging objects from a common universe of URLs. Simple statistical techniques can reveal tags that are related or similar in that they’ve been used by different people to classify a common object. If shared consensus sets of tags do emerge in these communities as they grow, it will be significant.

Can we extend the expressive power of these systems, say by using RDF and introducing some of the features of RDFS and (even) OWL, resulting in folksologies. It’s a good question. We can do it, of course, but will the result be as easy for people to learn and use? That’s an even better question.

IBM and Massachusetts General Hospital Announce Effort to Improve Information Sharing Among Cancer Researchers “Effective tools for information management, integrated tightly with underlying computing and data infrastructures, are key to life sciences researchers gaining new insights into complex problems,” said David Grossman, Distinguished Engineer, IBM Internet Technology Group. “In addition, the use of semantic web technologies to integrate many sources and formats of data with advanced modeling algorithms is particularly helpful for this type of large-scale collaborative project.”

“There is an urgent need to develop a common, unifying infrastructure that enables the integration and sharing of knowledge about cancer — both in terms of disparate data and distinct computational tools — with the goal of modeling cancer as a complex dynamic system,” said Dr. Deisboeck. “While advances in cancer research and new technologies have generated a wealth of new data and insight, all too often the lack of shared systems and standards makes integration of this crucial knowledge difficult or impossible.”

Cwm 1.0 has been released. Cwm is a general-purpose data processor for the semantic web, implemented as a forward chaining reasoner which can be used for querying, checking, transforming and filtering information. Its core language is RDF, extended to include rules, and it uses RDF/XML or RDF/N3 serializations.