The third example in this series is not too hard to explain.

03. Posting a blog post to social media

Because many of you are familiar with blogging and many of you blog yourself, you know what this one is about.

OK, after moving to the second example, I realized the subtle difference with the first: I got example 01 and 02 mixed up, and while the previous post was really discussing Julia's second example. Example 01 is really about snippets of publications, like quotes.

OK, let me first say that I hope Julia Reda does not consider herself a publisher. If you did not get the above joke, then continue reading.

This post is an attempt to translate the proposed copyright laws to, well, research. The choice of words is critical here. I deliberately did not say: academic, university, scholarly. I hope my hesitation will become more clear after reading this post too.

I was recently asked my experiences around data sharing, and in particularly the legal aspects of it. Because whether we like it or not (I think "we" generally do not like it and I see many scholars ignore it), society has an impact on scholarly research. Particularly, copyright and intellectual property (IP) laws make research increasingly expensive. I wrote up the following aspects related to that discussion.

SWAT4LS was once again a great meeting. I doubt I will find time soon enough to write up notes, but at least I can post the eNanoMapper poster I presented, which is available from F1000Research:

Willighagen E, Rautenberg M, Gebele D et al. Answering scientific questions with linked European nanosafety data [v1; not peer reviewed].

The current list of databases in Wikidata with an Open API using this query:
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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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