The most exciting news in our scientific quest to understand the nature of culture is not a single result, but a fundamental change in the metabolism of research: With increasing availability of cultural data, more and more robust quantification nurtures further qualitative insight; taken together, the results inspire novel conceptual and mathematical models, which in turn put into question and allow for accelerated modification of existing data models; Closing the loop, better models lead to more efficient collection of even more cultural data. In short, the hermeneutic circle is replaced by a hermeneutic hypercycle. Driven by the quantification of non-intuitive dynamics, cultural science is accelerated in an auto-catalytic manner.
The original "hermeneutic circle" characterizes the iterative research process of the individual humanist to understand a text or an artwork. The circle of hermeneutic interpretation arises as understanding specific observations presupposes an understanding of the underlying worldview, while understanding the worldview presupposes an understanding of specific observations. As such, the hermeneutic circle is a philosophical concept that functions as a core principle of individual research in the arts and humanities. Friedrich Ast explained it implicitly in 1808, while Heidegger and Gadamer further clarified it in the mid-20th century.
Unfortunately the advent of large database projects in the arts and humanities has almost disconnected the hermeneutic circle in practice. Over decades, database models, to embody the underlying worldview, were mostly established using formal logic and a priori expert intuition. Database curators were subsequently used to collect vast numbers of specific observations, enabling further traditional research, while failing to feed back systematic updates into the underlying database models.
As a consequence, "conceptual reference models" are frozen, sometimes as ISO standards, and out of sync with the non-intuitive complex patterns that would emerge from large numbers of specific observations by quantitative measurement. A systematic data science of art and culture is now closing the loop using quantification, computation, and visualization in addition.
The "hermeneutic hypercycle" is a term that returned no result in search engines before this contribution went online. A product of horizontal meme-transfer, it combines the hermeneutic circle with the concept of the catalytic hypercycle, as introduced by Eigen and Schuster. Like the carbon-cycle that keeps our sun shining and the citric acid cycle that generates energy in our cells, the hermeneutic circle in data-driven cultural analysis can be understood as a cycle of "reactions", here to nurture our understanding of art and culture.
The cycle of reactions is a catalytic hypercycle, as data collection, quantification, interpretation, and data modeling all feed back to catalyze themselves. Their cyclical connection provides a mutual corrective of bias (avoiding an error catastrophe) and leads to a vigorous growth of the field (as we learn what to learn next). In simple words, data collection leads to more data collection, quantification leads to more quantification, interpretation leads to more interpretation, and modeling leads to more modeling. Altogether, data collection nurtures quantification and interpretation, which in turn nurtures modeling, which again nurtures data collection, etc.
It is fascinating to observe the resulting vigorous growth of cultural research. While the naming game of competing terms such as digital humanities, culture analytics, culturomics, or cultural data science is still going on, it becomes ever more clear that we are on our way to a sort of systems biology of cultural interaction, cultural pathways, and cultural dynamics, "Broadly" defined. The resulting "systematic science of the nature of culture" is exciting news as most issues from religious fundamentalism to climate change require cultural solutions and "nature cannot be fooled".