📑 Data sharing and how it can benefit your scientific career l Nature

Annotated Data sharing and how it can benefit your scientific career (Nature)
Crowther offered everyone who shared at least a certain volume of data with his forest initiative the chance to be a co-author of a study that he and a colleague led. Published in Science in 2016, the paper used more than 770,000 data points from 44 countries to determine that forests with more tree species are more productive.
I suspect a similar hypothesis holds for shared specs, code, and the broader idea of plurality within the IndieWeb. More interoperable systems makes the IndieWeb more productive.

🔖 A First Step Toward Quantifying the Climate’s Information Production over the Last 68,000 Years

Bookmarked A First Step Toward Quantifying the Climate’s Information Production over the Last 68,000 Years (link.springer.com)
Paleoclimate records are extremely rich sources of information about the past history of the Earth system. We take an information-theoretic approach to analyzing data from the WAIS Divide ice core, the longest continuous and highest-resolution water isotope record yet recovered from Antarctica. We use weighted permutation entropy to calculate the Shannon entropy rate from these isotope measurements, which are proxies for a number of different climate variables, including the temperature at the time of deposition of the corresponding layer of the core. We find that the rate of information production in these measurements reveals issues with analysis instruments, even when those issues leave no visible traces in the raw data. These entropy calculations also allow us to identify a number of intervals in the data that may be of direct relevance to paleoclimate interpretation, and to form new conjectures about what is happening in those intervals—including periods of abrupt climate change.
Saw reference in Predicting unpredictability: Information theory offers new way to read ice cores [1]

References

[1]
“Predicting unpredictability: Information theory offers new way to read ice cores,” Phys.org. [Online]. Available: http://phys.org/news/2016-12-unpredictability-theory-ice-cores.html. [Accessed: 12-Dec-2016]

NIMBioS Workshop: Information Theory and Entropy in Biological Systems

Over the next few days, I’ll be maintaining a Storify story covering information related to and coming out of the Information Theory and Entropy Workshop being sponsored by NIMBios at the Unviersity of Tennessee, Knoxville.

For those in attendance or participating by watching the live streaming video (or even watching the video after-the-fact), please feel free to use the official hashtag #entropyWS, and I’ll do my best to include your tweets, posts, and material into the story stream for future reference.

For journal articles and papers mentioned in/at the workshop, I encourage everyone to join the Mendeley.com group ITBio: Information Theory, Microbiology, Evolution, and Complexity and add them to the group’s list of papers. Think of it as a collaborative online journal club of sorts.

Those participating in the workshop are also encouraged to take a look at a growing collection of researchers and materials I maintain here. If you have materials or resources you’d like to contribute to the list, please send me an email or include them via the suggestions/submission form or include them in the comments section below.

Resources for Information Theory and Biology

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