Publishing to me is getting the message out. I want to contribute to a better world, via my work. I do this by making methods more precise and by reducing error. You probably spotted that theme in my publications. The impact of my work is reflected by how often people reuse my work (extend, use, ...). A flawed reflection of that is the number of citations of my publications; better would be the number of projects that use my work. For example, tools that use the CDK (which has many more authors!), like Bioclipse, AMBIT,  LICCS (CDK in Excel), KNIME, and many more. Actually, the number of times these projects get cited, indirectly also contribute to the impact of my work.

"We" don't count that. Instead, "we" tend to focus on the Journal Impact Factor (JIF).

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. It is also 15 years too late.

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.

Because if done right, the publishers can even help forward science, despite crippling progress. That sound harsh, and surely they have done a lot of good for science. In fact, we would not be where we are now without the publishers. But things have changed.

Open Science is not just the right thing for science, it is also just fun. It enables collaborations, quick solutions by working together with experts, and actually solving questions you had not planned on solving. Part of Open Science is about making it as easy as possible for others to extend your work.
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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!
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