The Scientific Paper Is Obsolete Here’s what’s next.

The Scientific Paper Is Obsolete: Here’s what’s next.

The more sophisticated science becomes, the harder it is to communicate results. Papers today are longer than ever and full of jargon and symbols. They depend on chains of computer programs that generate data, and clean up data, and plot data, and run statistical models on data. These programs tend to be both so sloppily written and so central to the results that it’s contributed to a replication crisis, or put another way, a failure of the paper to perform its most basic task: to report what you’ve actually discovered, clearly enough that someone else can discover it for themselves.

Perhaps the paper itself is to blame. Scientific methods evolve now at the speed of software; the skill most in demand among physicists, biologists, chemists, geologists, even anthropologists and research psychologists, is facility with programming languages and “data science” packages. And yet the basic means of communicating scientific results hasn’t changed for 400 years. Papers may be posted online, but they’re still text and pictures on a page.

What would you get if you designed the scientific paper from scratch today? A little while ago I spoke to Bret Victor, a researcher who worked at Apple on early user-interface prototypes for the iPad and now runs his own lab in Oakland, California, that studies the future of computing. Victor has long been convinced that scientists haven’t yet taken full advantage of the computer. “It’s not that different than looking at the printing press, and the evolution of the book,” he said. After Gutenberg, the printing press was mostly used to mimic the calligraphy in bibles. It took nearly 100 years of technical and conceptual improvements to invent the modern book. “There was this entire period where they had the new technology of printing, but they were just using it to emulate the old media.”

Victor gestured at what might be possible when he redesigned a journal article by Duncan Watts and Steven Strogatz, “Collective dynamics of ‘small-world’ networks.” He chose it both because it’s one of the most highly cited papers in all of science and because it’s a model of clear exposition. (Strogatz is best known for writing the beloved “Elements of Math” column for The New York Times.)

The Watts-Strogatz paper described its key findings the way most papers do, with text, pictures, and mathematical symbols. And like most papers, these findings were still hard to swallow, despite the lucid prose. The hardest parts were the ones that described procedures or algorithms, because these required the reader to “play computer” in their head, as Victor put it, that is, to strain to maintain a fragile mental picture of what was happening with each step of the algorithm.

Victor’s redesign interleaved the explanatory text with little interactive diagrams that illustrated each step. In his version, you could see the algorithm at work on an example. You could even control it yourself.

Just for a moment I thought he was going to suggest that when people use software they need to understand what it's doing.

The Scientific Paper Is Obsolete: Here’s what’s next.

An extremely insightful article and important one for all who love the history of ideas and methods in science!!!!!  This is part of a paradigm change.

from the above article 

 I spoke to Theodore Gray, who has since left Wolfram Research to become a full-time writer. He said that his work on the notebook was in part motivated by the feeling, well formed already by the early 1990s, “that obviously all scientific communication, all technical papers that involve any sort of data or mathematics or modeling or graphs or plots or anything like that, obviously don’t belong on paper. That was just completely obvious in, let’s say, 1990,” he said.

“It’s been a source of ongoing bafflement and consternation for the past 29 years, that with the exception of a few people who get it, the community at large hasn’t really adopted it,” he said. “It’s incalculable, literally ... how much is lost, and how much time is wasted, and how many results are misinterpreted or are misrepresented.”

The idea of empirical science's detecting and recording material and energetic events is the end-all of science -- is fading fast.  Quasi-empirical methods that verify narratives about how reality functions -- can be as solid as an electron microscope's image -- as tools for verification.  Meta-analysis of the computational methods is the future companion of metrology of physical testing.  (personal opinion)

metrology: the scientific study of measurement. 

meta-analysis

 Aim of Course: Meta-Analysis refers to the statistical analyses that are used to synthesize summary data from a series of studies. If the effect size (or treatment effect) is consistent across all the studies in the synthesis, then the meta-analysis yields a combined effect that is more precise than any of the separate estimates, and also allows us to conclude that the effect is robust across the kinds of studies sampled. By contrast, if the effect size (or treatment effect) varies from one study to the next, the meta-analysis may allow us to identify the reason for the variation and report (for example) that the treatment is more effective in a particular kind of patient, or in a particular dose range.

 Quasi-empiricism in this tradition is the view that the logic of mathematical inquiry is based, like the logic of scientific discovery, on the bottom-up retransmission of falsity (by means of counterexamples) rather than the top-down transmission of axiomatic truth. Imre Lakatos, who originally introduced the distinction between Euclidean and quasi-empirical theories, construed mathematics as a quasi-empirical science following in essence Popper’s method of conjectures and refutations. His essay on Proofs and Refutations was an attempt to apply, and thereby to test, Popper’s critical method and fallibilist theory of knowledge in a field – mathematics – to which it had not primarily been intended to apply. While Popper’s proposal stood up gloriously to this test, the new application gave rise also to new insights, in particular the construal of proofs as thought experiments with a role similar to that of testing and corroborating experiments in science.

 
https://link.springer.com/chapter/10.100...-7654-8_23

I am into "truth tables" much more than someone's narrative showing Truth.

 A truth table is a mathematical table used in logic—specifically in connection with Boolean algebra, boolean functions, and propositional calculus—which sets out the functional values of logical expressions on each of their functional arguments, that is, for each combination of values taken by their logical variables (Enderton, 2001). In particular, truth tables can be used to show whether a propositional expression is true for all legitimate input values, that is, logically valid. - Wiki