Samuel's Tech Blog

UPDATE 29/3: See new results here

I reported in a previous blog post (with a bit of surprise) that Jena clearly outperformed SWI-Prolog for a NMR Spectrum similarity search run inside Bioclipse. I have now realized that indeed these previous results were flawed for a number of reasons.

Egon pointed to an interesting blog post about a feature that is available as a an extension to Jena, the semantic web framework available in Bioclipse. It allows to very easily query multiple SPARQL endpoints from a single SPARQL query (using the SERVICE keyword), and use variable bound from one endpoint when querying the next.

This is very useful in general. I was also thinking of the specific scenario (along the lines we have partly already been thinking) to use multiple Semantic MediaWikis as community maintained databanks, for querying back into Bioclipse. Being able to use multiple MediaWiki installs is very useful because it is hard to incorporate a very efficient access restriction system in MediaWiki (due to the nature of how it works, with template calls and all), so then it is better to be able to have separate wikis for content which needs special restrictions.

I wanted to test out some screen casting, so I chose to demo the (still experimental) SWI-Prolog integration into Bioclipse, showing how Prolog code (or a "Prolog knowledge base") can conveniently be stored inside Bioclipse's JavaScript environment (in a JS variable), loaded into the prolog engine, and then queried, all from the JS environment, and finally the results can be returned as well to the Javascript environment for further processing or output.

Note that this is still at the experimental stage, so things are a bit rough around the edges!

During my short stay at EBI, Egon had kindly arranged an opportunity to talk to Janna from the Steinbeck group, about some interesting work she has done on searching for cage structures in molecules, using Prolog, so we met over a coffee, together with Nico who's now at the Steinbeck group (visiting).

Bot Nico and Janna kindly gave a lot of good advice about research in general (as I'm currently looking into possibly doing PhD somewhere), which I highly appreciated. :)

And we talked some about the original topic too :), that is the cage structure problem. The cage structure problem is kind of an extension to the problem of expressing rings, which has previously been reported as a problem for OWL-DL. So because of this, it is interesting that Janna came up with a working solution, using Prolog.

As a highlighting example from the DL-side, Michel Dumontier has done some work on representing molecules, including rings. But they also had to use rules, not plain OWL.

So that seem to be the general conclusion: In order to express ring structures (or extensions of it, such as cage structures), you'll need to use rules in some way.

Unfortunatly my project is now running out of time, so I might not have much time to look more into this topic as part of my project :(. Will see if I can include this as a part of another course I still have to finish ("knowledge based systems in bioinformatics"), but that remains to see.

The problem I've had, to find a working SPARQL query for doing similarity search for spectra, according to a list of peak shift values (documented on this blog: post1, post 2 and on semanticoverflow) is now finally solved, thanks to helpful advice from Brandon Ibach on the [pellet-users] mailing list.

Found a very interesting quote:

"Both OWL-DL and function-free Horn rules are decidable fragments of first-order logic with interesting, yet orthogonal expressive power"Motik B, Sattler U, Studer R. Query Answering for OWL-DL with rules. Web Semantics: Science, Services and Agents on the World Wide Web. 2005;3(1):41-60. Available at: http://linkinghub.elsevier.com/retrieve/pii/S157082680500003X.

"Horn rules", is what prolog builds upon (a prolog statement are horn rules, AFAIS), so maybe Prolog fits into the category of "function-free horn rules"? (Gotta try to figure that out), and OWL-DL is the W3C standard for expressive semantics, that reasoners like pellet (which is available in bioclipse build upon.

What do you think of that title? :) To me it sounds like one of the (many) natural next steps forward for Bioclipse sometime in future¹.

Explicit knowledge is too expensive

There are lots of things that can't be answered by a computer from data alone. Maybe the majority of what we humans perceive as knowledge is inferred from a combination of data (simple fact statements about reality) and rules that tell how facts can be combined together to allow making implicit knowledge (knowledge that is not persisted as facts anywhere, but has to be inferred from other facts and rules) become explicit.

One can easily imagine though, that storing every single piece of knowledge that could be stated, as an explicit fact, would require more storage than can probably ever be made available in this universe.

Simulations can make knowledge explicit, from first princples

It is not too hard to come up with some processes which are just too complex and involves too much variability² that it is unrealistic to try to capture every imaginable state of of that system or process in explicit facts. Instead we must seek the "first principles" that defines the process, and through simulations make explicit any knowledge we are looking for, at the time we need it (one can of course cache often accessed knowledge).