The South-East Asia Earthquake and Tsunami

The catastrophic actuality pushes me back to post on this page which had been silent for a while. A number of Web communities have quickly dedicated resources to inform and bring as much support as possible. Wikipedia has dedicated very rapidly a page to the event, which is updated regularly. WorldChanging has also focused on the event and community resources, and the specific SEA-EAT blog provides news and information about resources, aid, donations and volunteer efforts.

RDF/Topic Maps Interoperability Task Force

In his today's deviant chronicle, Edd Dumbill is wondering if the Semantic Web dreamers could not turn out to be right after all:

The topics of XML-oriented programming languages and the Semantic Web have been targets of mockery in their time, so this week I'm asking whether the true believers might be right.

And further on:

The unthinkable rapprochement between topic maps and RDF has occurred, signified by the formation of the W3C RDF/Topic Maps Interoperability Task Force. The task force is part of the Semantic Web Best Practices and Deployment Working Group. The last time I was with the majority of the people listed as members of the task force, it was in a very pleasant drinking establishment in Amsterdam. It's nice to think that the bonhomie of that evening has persisted into forming the basis of the task force.

They Ain’t Nothin’ ‘til I Call ‘em!

In today's article in EContentMag, Bob Doyle writes :

There is nothing wrong with creating new words for branding and marketing purposes, but it makes a company look foolish if they don't know the basic technical vocabulary of their own industry. The problem is that technical jargon is notoriously slippery and it is often difficult to determine whether a true meaning for a word even exists.

Semantic Association Identification and Knowledge Discovery...

Picked this one up at PlanetRDF and here.

Our goal is to research new techniques and improving effectiveness of techniques to identify semantic associations and knowledge discovery by exploiting a large knowledge base. Specific objectives include (a) ontology driven lazy semantic metadata extraction (i.e., annotation) to complement traditional active metadata extraction techniques, and (c) formal modeling and high-performance computation of semantic association discovery including ontology-based contextual processing and relevancy ranking of interesting relationships.

Contextually relevant links include InfoQuilt, and SCORE.