I have promised my Twitter followers the SPARQL query you have all been waiting for. Sadly, you had to wait for it for more than two months. I’m sorry about that.

December saw the end of this year’s PRA3006 course (aka #mcspils). Time to blog some screenshots of the student projects. Like last year, the aim is to use the Open PHACTS API to collect data with ops.js and which should then be visualized in a HTML page, preferably with d3.js. This year, all projects reached that goal.

The Royal Society of Chemistry and Wikipedia just released an interesting press release:

Debugging is the process find removing a fault in your code (the etymology goes further back than the moth story, I learned today). Being able to debug is an essential programming skill, and being able to program flawlessly is not enough; the bug can be outside your own code.

I previously wrote about the JavaScript Object Notation (JSON) which has become a de facto standard for sharing data by web services. I personally still prefer something using the Resource Description Framework (RDF) because of its clear link to ontologies, but perhaps JSON-LD combines the best of both worlds.

I think the authors of the Open PHACTS proposal made a right choice in defining a small set of questions that the solution to be developed could be tested against. The questions being specific, it is much easier to understand the needs. In fact, I suspect it may even be a very useful form of requirement analysis, and makes it hard to keep using vague terms.

Yesterday, I received a letter from the Association of Universities The Netherlands (VSNU, @deVSNU) about Open Access. The Netherlands is for research a very interesting country: it’s small, meaning we have few resources to establish and maintain high profile centers, we also believe strong education benefits from distribution, so we we have many good universities, rather than a few excelling universities.

Chemistry in Second Life. DOI:10.1186/1752-153X-3-14 There are nowadays a lot of people talking about Open, about open access, open data, open source. In fact, some discussion on Twitter resulted in the realization that it is highly unlikely that any scholar has not taken advantage of Open in some way in their research in the last few years. However, this is mostly due to people whom actually do, not by those who talk about it or use it.

Elsevier is not the only publisher with a large innovation inertia. In fact, I think many large organizations do, particularly if there are too many interdependencies, causing too long lines. Greg Laundrum made me aware that one American Chemical Society journal is now going to encourage (not require) machine readable forms of chemical structures to be included in their flagship. The reasoning by Gilson et al. is balanced.

Elsevier’s new ideas on text mining are getting a lot attention now. Sadly, they get it wrong, again. On the bright side, all other publishers, which are expected to follow this year, can learn from this mistake.

I got a one more source code zip file from the Maastricht Science Programme students (see also the first two screenshots). Vincent and Błażej extended the d3.js tree view, showing classification information from ChEBI (they also submitted three patches to the Open PHACTS ops.js):