Knowledge Liquidity
Data-information Cycles
Data cycles from information to knowledge (and vice versa) throughout the natural world. High school biology students learn early on that the natural world processes unparsed data into complex information systems. Genetic information is literally synthesized from functional groups in chemistry (amine, amide, etc.). Students are taught that this process, called central dogma, exhibits information directionality (DNA → RNA → protein). In molecular medicine, data seemingly cycles from information to knowledge, when stem cells “decide” on how exactly to differentiate — though this “decision-making process” can be quantified through path analysis.
Indeed, history may very well regard the 2020s as the era in which information theories were widely applied — both in the natural world and technology. From David Sinclair’s information theory of aging to César Hidalgo’s theory on “why information grows,” most cite an intellectual inheritance in Claude Shannon (“A Mathematical Theory of Communication”).[1]
Knowledge Production
Knowledge is grossly denominated in “citations,” the bulk of which is funded for by large government platforms. The genesis of knowledge production can be anchored society’s first written records — broadly, 3000 BCE. Today, the bulk of knowledge and science is generated by large government systems, such as the National Institutes of Health in the United States. In 2006, disparate nations including the United States, China, the EU, Russia, and others contributed more than $12 billion to the International Fusion Experiment. Large government expenditures such as military spending are also significant sources for knowledge production. In science and academia, authors of knowledge in the way of peer-reviewed papers regard “citations” as the currency of knowledge and science. However, the metasciences that study the citations note that large government funding platforms only weakly correlate to “citation impact.”
