With genetics and genomics being complicated enough, epigenomics adds even more layers of control and regulation of gene expression, and high-throughput global analyses of epigenetic changes further add to the reams of biological information many people are already referring to as the “data-deluge”.

Now we are awash in challenges! EOL has announced its Computable Data Challenge:Some $US 50,000 is on offer. "Challenge" is perhaps a misnomer, as EOL is offering this money not as a prize at the end, but rather to fund one or more proposals (submitted by 22 May) that are accepted.

There are a number of great datasets available for doing macroecology and community ecology at broad spatial scales. These include data on birds (Breeding Bird Survey, Christmas Bird Count), plants (Forest Inventory &

Is Data Publication the Right Metaphor? is an essay by Mark Parsons and Peter Fox to be published in the Data Science Journal, for which a preprint has been provided for open pre-publication community peer review at http://mp-datamatters.blogspot.com/2011/12/seeking-open-review-of-provocative-data.html.

Our whistlestop summer conference tour circumnavigating the globe has come to a jetlagged end, with the final conference being last weeks HUPO (Human Proteomics Organisation) congress in Geneva.

There is an exciting postdoc opportunity for folks interested in quantitative approaches to studying evolution in Michael Gilchrist’s lab at the University of Tennessee. I knew Mike when we were both in New Mexico. He’s really sharp, a nice guy, and a very patient teacher. He taught me all about likelihood and numerical maximization and opened my mind to a whole new way of modeling biological systems.

In the comments of my post on the Ecological Data Wiki Jarrett Byrnes asked an excellent question: As I started to answer it I realized that my thoughts on the matter were better served by a full post, both because they are a bit lengthy and because I don’t actually know much about DataONE and would love to have some of their folks come by, correct my mistaken impressions, and just chat about this stuff in general.

In biology, the fields of macromolecular structural biology and sequence bioinformatics have, since the 1970s, had established international databases for the deposition of data, and journal policies mandating such deposition prior to acceptance for publication of manuscripts describing the data.  Similar good practices have developed more recently in other disciplines, notably astronomy.

Evidence submitted by David Shotton in response to the Royal Society’s Policy Study “Science as a Public Enterprise” Call for Evidence, addressing the following two topics raised by that call: Getting Researcher buy-in. How do we get researchers to be more willing to share data? What is there to be learned from disciplines such as genomics which have norms which favour wide sharing of data?

We are pretty excited about what modern technology can do for science and in particular the potential for increasingly rapid sharing of, and collaboration on, data and ideas. It’s the big picture that explains why we like to blog, tweet, publish data and code, and we’ve benefited greatly from others who do the same. So, when we saw this great talk by Michael Nielsen about Open Science, we just had to share.