Fireside Science: Incredible, Evo-Developmental, and Aestastical Readings!

Here is yet another set of features from my micro-blog Tumbld Thoughts, although this time they will be cross-posted to Fireside Science. Also at Fireside Science is a short feature on my Orthogonal Research initiative. Among these three features are publications, articles, and videos from my reading queue, serving up some Summertime (Summer is Aestas in Latin) inspiration. 

I. Incredible Technologies!

Real phenomena, incredible videos. Here is a reading list on resources on how film and animation are used to advance science and science fiction alike. Here they are in no particular order: 

Gibney, E.   Model Universe Recreates Evolution of the Cosmos. Nature News, May 7 (2014).

A Virtual Universe. Nature Video, May 7 (2014).

Creating Gollum. Nature Video, December 11 (2013).

Letteri, J.   Computer Animation: Digital heroes and computer-generated worlds. Nature, 504, 214-216 (2013).

Laser pulse shooting through a bottle and visualized at a trillion frames per second. Camera Culture Group YouTube Channel, December 11 (2011).

Hardesty, L.   Trillion Frame-per-Second Video. Phys.org, December 13 (2011).

Ramesh Raskar: imaging at a trillion frames per second. Femto-photography TED Talk, July 26 (2012).

Preston, E.   How Animals See the World. Nautil.us, Issue 11, March 20 (2014).

How Animals See the World. BuzzFeed Video YouTube Channel, July 5 (2012).

In June, a Synthetic Daisies post from 2013 was re-published on the science and futurism site Machines Like Us. The post, entitled "Perceptual time and the evolution of informational investment", is a cross-disciplinary foray into comparative animal cognition, the evolution of the brain, and the evolution of technology. 

Evo-Developmental Findings (new)!

Phylogenetic representation of sex-determination mechanism. From Reading [3]

Here are some evolution-related links from my reading queue. Topics: morphological transformations [1], colinearity in gene expression [2], and sex determination [3].

The first two readings [1,2] place pattern formation in development in an evolutionary context, while the third [3] is a brand new paper on the phylogeny, genetic mechanisms, and dispelling of common myths involved with sex determination.

III. Aestastical Readings (on Open Science)!

 

Welcome to the long tail of science. This tour will consist of three readings: two on the sharing of "dark data", and one on measuring "inequality" of citation rates. In [4, 5], the authors introduce us to the concept of dark data. When a paper is published, the finished product typically includes only a small proportion of data generated to create the publication (Supplemental Figures notwithstanding). Thus, dark data is the data that are not used, ranging from superfluous analyses to unreported experiments and even negative results. With the advent of open science, however, all of these data are potentially available to both secondary analysis and presentation as something other than a formal journal paper. The authors of [5] contemplate the potential usefulness of sharing these data.

Dark data and data integration meet yet again. This time, however, the outcome might be maximally informative. From reading [5].

In the third paper [6], John Ioannidis and colleagues contemplate patterns in citation data that reveal a Pareto/Power Law structure. That is, about 1% of all authors in the Scopus database produce a large share of all published scientific papers. This might be related to the social hierarchies of scientific laboratories, as well as publishing consistency and career longetivity. But not to worry -- if you occupy the long-tail, there could be many reasons for this, not all of which are harmful to one's career.

NOTES:

[1] Arthur, W.   D'Arcy Thompson and the Theory of Transformations. Nature Reviews Genetics, 7, 401-406 (2006).

[2] Rodrigues, A.R. and Tabin, C.J.   Deserts and Waves in Gene Expression. Science, 340, 1181-1182 (2013).

[3] Bachtrog et.al and the Tree of Sex Consortium   Sex Determination: Why So Many Ways of Doing It? PLoS Biology, 12(7), e1001899 (2014).

[4] Wallis, J.C., Rolando, E., and Borgman, C.L.   If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology. PLoS One, 8(7), e67332 (2013).

[5] Heidorn, P.B.   Shedding Light on the Dark Data in the Long Tail of Science. Library Trends, 57(2), 280-299 (2008).

[6] Ioannidis, J.P.A., Boyack, K.W., and Klavans, R.   Estimates of the Continuously Publishing Core in the Scientific Workforce. PLoS One, 9(7), e101698 (2014).