Wikidata celebrates their 5th birthday with a great WikidataCon in Berlin. Sadly, I could not join in person, so I assuming it is a great meeting, following the #WikidataCon hash tag and occasionally the live stream.

Happy Birthday, Wikidata!

My first encounter was soon after they started, and was particularly impressed by the presentation by Lydia Pintscher at the Dutch Wikimedia Conferentie 2012. I had played with DBPedia occasionally but always disappointed by the number of issues with extracting chemistry from the ChemBox infobox, but that's of course the general problem with data that has been mangled into something that looks nice. We know that problem from text mining from PDFs too.

It takes effort to move scholarly publishing forward. And the traditional publishers have not all shown to be good at that: we're still basically stuck with machine-broken channels like PDFs and ReadCubes. They seem to all love text mining, but only if they can do it themselves.

Fortunately, there are plenty of people who do like to make a difference and like to innovate. I find this important, because if we do not do it, who will.

It has been ages I blogged about work I heard about and think should receive more attention. So, I'll try to pick up that habit again.

After my PhD research (about machine learning (chemometrics, mostly), crystallography, QSAR) I first went into the field metabolomics. Because is combines core chemistry with the complexity biology. My first position was with Chris Steinbeck, in Cologne, within the bioinformatics institute led by Prof. Schomburg (of the BRENDA database).

This spring I attended a meeting organized by researchers from the European metabolomics community, including from PhenoMeNal to talk about proposing a use case to ELIXIR. Doing research in metabolomics and being part of ELIXIR, I was happy that meeting happened. During the meeting I presented the work from our BiGCaT group (e.g. WikiPathways, see doi:10.1093/nar/gkv1024).
Text
Text
This blog deals with chemblaics in the broader sense. Chemblaics (pronounced chem-bla-ics) is the science that uses computers to solve problems in chemistry, biochemistry and related fields. The big difference between chemblaics and areas such as chem(o)?informatics, chemometrics, computational chemistry, etc, is that chemblaics only uses open source software, open data, and open standards, making experimental results reproducible and validatable. And this is a big difference!
About Me
About Me
Popular Posts
Popular Posts
Pageviews past week
Pageviews past week
1831
Blog Archive
Blog Archive
Labels
Labels
Loading
Dynamic Views theme. Powered by Blogger. Report Abuse.