Chemistry publication - making the revolution

Steven Bachrach has just published a very interesting commentary "Chemistry publication - making the revolution" on March 17, 2009 in the new Journal of Cheminformatics (I am on the editorial board).

The article does a great job of highlighting the current state of affairs in chemistry which is creating a chasm between researchers and the data they could be using. There are suggestions of steps that can be taken by researchers, reviewers and editors. Although Open Notebook Science is mentioned, there are several less intensive steps that can be taken to still benefit the community. Steven mentions the submission of JCAMP-DX files instead of PDFs when submitting spectra as supplementary materials for publications. I agree that this is a very low barrier step that chemists can take to gain immediate benefit - whether they share their spectra or not. At that point it also becomes trivial to contribute spectra to databases like ChemSpider that supports the open JCAMP-DX format - hopefully as Open Data (so that it can be used in applications such as our SpectralGame)

The ChemSpider Journal and ChemMantis

The ChemSpider Journal of Chemistry is about to go live. This is not just another chemistry journal. Not only does it boast the option of an open peer-review in addition to Open Access, but it takes us tantalizing closer to the promise of Web3.0: the semantic web. This is achieved by a sophisticated mark-up system generated by ChemMantis. The automatic identification of molecules is impressive enough. But it also marks up functional groups, reactions, spectral data and even biological entities.

For an example consider this article, which was actually a proposal that I wrote with Rajarshi Guha and Tony Williams. Simply by hovering over the marked-up text "Ugi reaction", it pulls up a brief summary from Wikipedia. What makes this semantic is that it already knows that this is a chemical reaction and not a molecule or a virus.

When you hover over the name of a molecule it knows to render it accordingly and provide appropriate links. Consider this example:
This makes the experience of reading a chemistry article a lot richer. But another payoff is coming in what machines will do when they are able to associate concepts instead of just text. Most importantly it does not require authors to do any extra work.

Tony has more information on his blog - and new submissions are welcome.