I agree with Stephen, if you are into e-Learning, and you listen to one talk this year, listen to this one. He begins his talk with “if you are using a computer or a cell phone right now, please continue.” As he says these words, you initially assume he is about to ask you to turn off your computer and your cell phone. No. Stephen wants you to feel connected. Stephen Downes is no ordinary man.

VLDB 2007 will be held in Vienna.

VLDB 2007 is a premier international forum for database researchers, vendors, practitioners, application developers, and users. We invite submissions reporting original results on all aspects of data management as well as proposals for panels, tutorials, and demonstrations that will present the most critical issues and views on practical leading-edge database technology, applications, and techniques. We also invite proposals for events and workshops that may take place at the conference site between September 23th and 25th before the VLDB 2007 conference.

Larray Seltzer points out that Java lost to Flash and AJAX:

Mostly, in the end, it appears that Java on the client lost out to Flash of all things! (…) It couldn’t even be competitive in the most inessential of tasks.

Let this be a lesson to all of us. You can have the nicest framework in the world, you can have the best arguments in the world, but if you are not providing immediate value to your users, you are dead in the water.

The DOLAP 2006 preliminary technical program is out. Rokia Missaoui and Omar Boussaid have a paper in called “Enhanced Mining of Association Rules from Data Cubes”. There is one paper on wavelets and range sum queries. At this point, we do not even have the abstracts so I will wait before commenting further on the papers.

The European WorkShop on Data Stream Analysis will be held in Italy in March 2007.

A growing number of applications in areas like networking, retail industry or sensor networks are dealing with a challenging type of data: data is produced over time in an unpredictable fashion, representing streams of network traffic, retail transactions or sensor-measured values. A key requirement of such applications is to continuously monitor and react to interesting phenomena occurring in the input streams. Streaming applications are usually characterized by transient relations, continuous queries, approximate answers and one-pass evaluation. These characteristics make them incompatible with several assumptions usually made in traditional databases as well as in statistical techniques. Indeed, simply storing the arriving data into a traditional database management system and manipulating the stored data is impossible. This special European Workshop seeks to bring together researchers working on knowledge discovery problems in data streams. While the primary objective of this Workshop is to provide an avenue for dissemination of research results and works in progress, we also seek to discuss the future development of knowledge discovery in data streams, and how the research will benefit applications. We invite authors to submit their work that demonstrates current research and novel applications in this area.

Fred responded to my recent anti-Semantic Web post by saying that the “Semantic Web landscape is changing.”

I really like Fred’s post. Here is where he agrees with me:

The proof that both RDF and web ontologies are useful is yet to be done.

Here is where we disagree:

Everything is changing, and everything should explode… soon!

I honestly do not see the Semantic Web being about to take off. As Bob DuCharme pointed out, people are doing “ontologies for the sake of ontologies”. This will get old very quickly. If 8 years and millions of dollars was not enough to produce a single remotely useful application, what will it take?

Are semantic web researchers becoming semantic web implementers? I do not see this happening. The papers are every bit as theoretical and as disconnected from real-world problems as they ever were.

Here are some common myths:

• Google is getting worse every day. Only the Semantic Web can save us. (False: Google is not getting worse, it is constantly improving and at an alarming rate at that.)
• Inference engines and ontologies are more sophisticated or somehow more intelligent than current database solutions such as relational databases, data mining algorithms, and so on. (False: Current database technology is highly sophisticated and built on lots and lots of theory.)