II. Pedia Sapiens: A Planetary Progeny Comes to Her/His Own Twintelligent Gaiable Knowledge

B. The Spiral of Science: Manican to American to Earthicana Phases

Fortunato, Santo, et al. Science of Science. Science. 359/1007, 2018. A 14 member team including Katy Borner, Dirk Helbing, Filippo Radicchi and Albert-Laszlo Barabasi provide a strong statement to date about how this international collaborative endeavor can be well characterized by the same dynamic, self-organizing complex network system theories as everywhere else. Akin to cerebral cognition on a group and global scale (while not overtly said), this approach and identity can help identify better methods and techniques, aid project design, and hasten discovery. And here is an affirmation of our website premise, whence an emergent humankinder is to be appreciated as coming to her/his own revolutionary knowledge.

The increasing availability of digital data on scholarly inputs and outputs—from research funding, productivity, and collaboration to paper citations and scientist mobility—offers unprecedented opportunities to explore the structure and evolution of science. The science of science (SciSci) offers a quantitative understanding of the interactions among scientific agents across diverse geographic and temporal scales. The value proposition of SciSci is that with a deeper understanding of the factors that drive successful science, we can more effectively address environmental, societal, and technological problems.

Science can be described as a complex, self-organizing, and evolving network of scholars, projects, papers, and ideas. This representation has unveiled patterns characterizing the emergence of new scientific fields through the study of collaboration networks and the path of impactful discoveries through the study of citation networks. (First Page)

Franceschet, Massimo. The Large-Scale Structure of Journal Citation Networks. Journal of the American Society for Information Science and Technology. Online February, 2012. Within the burst of such noosphere studies reported herein, in another example, a University of Udine, Italy, mathematician proceeds to reconceive the field of bibliometrics by way of integral network dynamics. Three levels of interest are then node, group, and network. And in all these contributions, beyond abstract terms, the formation of an enveloping worldwide brain by the same stratified neural network geometries seems undeniable, waiting to be realized, and availed.

Frangsmyr, Tore, et al, eds. The Quantifying Spirit in the 18th Century. Berkeley: University of California Press, 1990. On the proliferation of instrumentation that served to identify and measure everything from chemicals to clouds.

Gates, Alexander, et al. Nature’s Reach: Narrow Work has Broad Impact. Nature. 575/32, 2019. As a contribution to this premier scientific journal’s 150th anniversary, Northeastern University network theorists including Albert-Laszlo Barabasi quantify and explain the long course from individual rudiments to today’s global, multiple coauthor, research teams. See the Science of Science article by Santo Fortunato, et al (search) from this group as a 2018 technical document. As we near 2020, how might it dawn (as time runs out) that this dynamic, instant, worldwide, emergent endeavor is presently gaining knowledge on her/his own.

Gau, Remi, et al. Brainhack: Developing a Culture of Open, Inclusive, Community-driven Neuroscience. Neuron. 109/11, 2021. As an example of how real and responsive the nascent global knowledge repository actually is, just three words – brainhack, Gau and Neuron – could instantly access the full article. Herein some fifty researchers across Europe, Australia and the USA describe an active medium for on-going discussions with regard to our collective project to retrospectively quantify and learn all about the homo sapiens cerebral faculty from which it all arose. At what point, by what vista, as this site tries to broach, could we altogether witness, and achieve an ecosmic self-discovery, as if a second singularity, so as for EarthKinder to begin a new self-cocreation?

Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress.

Geiger, R. Stuart. Investigating the Role of Algorithmic Systems in Wikipedian Organizational Culture. Big Data & Society. Online September, 2017. In this new SAGE journal, a UC Berkeley Institute for Data Science researcher (Google for RSG and IDS) considers the presence and quality of these programs as they may be running through and affecting this huge, busy public encyclopedia.

Scholars and practitioners across domains are increasingly concerned with algorithmic transparency and opacity, interrogating the values and assumptions embedded in automated, black-boxed systems, particularly in user-generated content platforms. Today, the organizational culture of Wikipedia is deeply intertwined with various data-driven algorithmic systems, which Wikipedians rely on to help manage and govern the “anyone can edit” encyclopedia at a massive scale. I illustrate how cultural and organizational expertise is enacted around algorithmic agents by discussing two autoethnographic vignettes, which relate my personal experience as a veteran in Wikipedia. I use these cases of Wikipedia’s bot-supported bureaucracy to discuss several issues in the fields of critical algorithms studies; critical data studies; and fairness, accountability, and transparency in machine learning. (Abstract excerpts)

George, Daniel and Eliu Antonio Huerta. Deep Neural Networks to Enable Real-Time Multimessenger Astrophysics. arXiv:1701.00008. University of Illinois astronomers describe how artificial neural nets as a generic self-organizing complex system of universal application can facilitate space studies. See also in this cosmic realm Deep Learning for Studies of Galaxy Morphology (1701.05917), and Star-Galaxy Classification using Deep Convolutional Neural Networks (1608.04369).

The application of DNNs in GW astrophysics, astronomy, and astroparticle physics has the potential to accelerate scientific research and unlock new opportunities by enhancing the way we use existing High Performance Computing (HPC) resources while allowing us to exploit emerging hardware architectures such as deep-learning optimized Graphics Processing Units (GPUs) and Field-Programmable Gate Arrays (FPGAs). Working in tandem with computer scientists and industries to develop Artificial Intelligence (AI) tools that extend our prototype, and further exploring applications of deep learning for multimessenger astrophysics and fundamental sciences, may provide the means to e ectively consolidate different windows of observation into the Universe. (2)

Goerner, Sally. Integral Science: Rethinking Civilization Using the Learning Universe Lens. Systems Research and Behavioral Science. 20/4, 2003. Humanity is perceived as a collaborative learning society revising its comprehension of the universe from a mechanistic view where life is an accident to an Integral Ecological vision. This inchoate paradigm shift finds life, intelligence and evolutionary cooperation to be innate properties, which can then serve as to inspire a global, fractal-like network of symbiotic communities.

Golosovsky, Michael and Sorin Solomon. Growing Complex Network of Citations of Scientific Papers. arXiv:1607.08370. Hebrew University of Jerusalem physicists continue their project of elucidating how global research endeavors via our instant Internet are structured by the same, neural-net, scale-free interconnectivity as everywhere else. See also a cited paper Anatomy of Scientific Evolution by Jinhyuk Yun, et al in PLoS One (February 2015).

To quantify the mechanism of a complex network growth we focus on the network of citations of scientific papers and use a combination of the theoretical and experimental tools to uncover microscopic details of this network growth. Namely, we develop a stochastic model of citation dynamics based on copying/redirection/triadic closure mechanism. In a complementary and coherent way, the model accounts both for statistics of references of scientific papers and for their citation dynamics. Originating in empirical measurements, the model is cast in such a way that it can be verified quantitatively in every aspect. Such verification is performed by measuring citation dynamics of Physics papers. The measurements revealed nonlinear citation dynamics, the nonlinearity being intricately related to network topology. The nonlinearity has far-reaching consequences including non-stationary citation distributions, diverging citation trajectory of similar papers, runaways or "immortal papers" with infinite citation lifetime etc. Thus, our most important finding is nonlinearity in complex network growth. In a more specific context, our results can be a basis for quantitative probabilistic prediction of citation dynamics of individual papers and of the journal impact factor.

Gontier, Nathalie, et al. Evolutionary Epistemology, Language and Culture: A Non-Adaptationist, Systems Theoretical Approach. Dordrecht: Springer, 2006. This academic endeavor was active in the 1980s, see Franz Wuketits herein, in search of a proper Darwinian basis for psyche and society. But the project has languished for some years until its revival at a 2004 conference held at the Vrije Universiteit Brussel, with a salient difference that this volume reflects. Rather than external selection alone, the prior bent, a novel realm of internal, nonlinear dynamics such as self-organization, symbiogenesis, and a pervasive modularity are now seen at work. So one more example of an epic shift, a genesis evolutionary synthesis, due to our worldwide “Mary and Charles Earthwin,” that remains held back by a still life-unfriendly physical universe, and a need to translate such abstractions into a cosmic embryogeny. Notable papers by Wuketits, Gontier, Diederik Aerts, Tim Ingold, Bart de Boer, and others make a credible case.

The dynamic approach we take has not only permeated the natural sciences, but the social, behavioral and neurosciences as well. The common link is the idea that seemingly unrelated systems behave in essentially the same way and that the creation and evolution of patterned behaviour at all levels is governed by the processes of self-organization. (Annemarie Peltzer-Karpf 228)

Goodman, Alyssa, et al. New Thinking on and with Data Visualization. arXiv:1805.11300. AG, Harvard University, Michelle Borkin, Northeastern University and Thomas Robitaille, Aperio Software, UK discuss how to better use and enhance graphic Internet presentations of scientific findings by small and large research teams that collaboratively use masses of big data to study where and who we are from cosmic to cardiac phases. We add author bios to sample these worldwide exploratory frontiers.

As the complexity and volume of datasets have increased along with the capabilities of modular, open-source, easy-to-implement, visualization tools, scientists' need for, and appreciation of, data visualization has risen too. Our aim in this paper is to spark conversation amongst scientists, computer scientists, outreach professionals, educators, and graphics and perception experts about how to foster flexible data visualization practices that can facilitate discovery and communication at the same time. We present an example using the glue visualization environment to demonstrate how the border between explanatory and exploratory visualization is easily traversed. The linked-view principles as well as the actual code in glue are easily adapted to astronomy, medicine, and geographical information science - all fields where combining, visualizing, and analyzing several high-dimensional datasets yields insight. (Abstract excerpt)

In my Astronomy research, I am interested in how the gas in galaxies constantly re-arranges itself over huge time spans to form new stars. I have also had a long-standing interest in data visualization, and in improving the use of computers in all aspects of scientific research. I teach a course at Harvard called "The Art of Numbers," and I am very involved in the WorldWide Telescope Project, which brings astronomical data to everyone through an interface that demonstrates data delivery for the 21st Century of "e-Science." (A. Goodman website)

Michelle Borkin works on the development of novel visualization techniques and tools to enable new insights and discoveries in data. She works across disciplines to bring together computer scientists, doctors, and astronomers to collaborate on new analysis and visualization techniques, and cross-fertilize techniques across disciplines. Her research resulted in the development of novel computer assisted diagnostics in cardiology, scalable visualization solutions for large network data sets, and novel astrophysical visualization tools and discoveries. (M. Borkin website)

Tom Robitaille is a director and founder of Aperio Software. Following a PhD in Astrophysics from the University of St Andrews, he took a postdoctoral fellowship at the Harvard-Smithsonian Center for Astrophysics, and led a research group at the Max Planck Institute for Astronomy. He then moved to the UK to become a freelance developer for scientific open source projects, and co-founded Aperio Software. Tom is an active member of the scientific open-source community - he is one of the coordinators and lead developers of the Astropy project, as well as the lead developer of the glue package for multi-dimensional linked data exploration. (A. Software website)

Goonatilake, Susantha. Towards a Global Science. Bloomington: Indiana University Press, 1998. A Sri Lankan policy advisor to the United Nations seeks to leaven a Western dominance and enrich science by including holistic, mindful contributions from Asian, Arabic and Indigenous cultures in mathematics, psychology, evolution and physics.

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