This is an example of something I do quite often on my blog Synthetic Daisies. I also run a micro-blog on Tumblr called Tumbld Thoughts. It is a sort of developmental league for features on things from my reading queue. This allows me to combine tangentially- or thematically-connected papers into a graphically-intensive single feature. I then make a meta-connection between these posts and feature it on Synthetic Daisies (to which this content is also cross-posted).

For example, the three features in this post are based on publications, articles, and videos from my reading queue, serving up some Summertime (the Latin word for Summer is Aestas) inspiration. The title is suggestive of the emergent meta-theme (I’ll leave it up to the reader to determine what exactly that is).

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.

II. 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.

BONUS FEATURE: To conclude, I would like to provide a window into what I have been doing for the past six months. If you read Synthetic Daisies with some regularity, you may be aware that I ran out of funding at my former academic home. As a consequence of not being able to find a replacement position, I am doing something called an academic start-up called Orthogonal Research (an open-science initiative that is intensively virtual).

The object is to leverage my collaborations to produce as much work as possible. Under this affiliation, I have worked on several papers, started on a collaborative project called DevoWorm, and advanced a vision of radically open and virtual science. While I have not been able to successfully obtain seed funding (typical of a start-up that deals in tangible goods), the goal is to produce research, a formal affiliation, and associated activities (consulting, content creation) in a structured manner, perhaps leading to future funding and other opportunities.

My vision for open virtual science (with the Orthogonal Science logo at the lower right).

While there are limitations to this model, I have gone through two “quarters” (based on the calendar year, not financial year) of activity. The activity reports for Q1 and Q2 can be downloaded here. As it happens, this has been quite a productive six-month period.

Spread the word about this idea, and perhaps this model of academic productivity can evolve in new and ever more fruitful ways. I will be producing a white paper on the idea of a research start-up, and it should be available sometime in near future. If you are interested in discussing this more with me one-on-one, please contact me.

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).