Big-Data and Epistemic Change

Big data is an important achievement of the ICT revolution. In this article, big data is considered in terms of its impact on scientific research and the epistemology of knowledge. There are two main trends in this matter: one is that such a phenomenon leads to the abandonment of theory from research processes, and the other considers the role of theories to be still effective.
What we consider regarding the epistemological transformation caused by big data is somewhat different from what is stated in the relevant literature. Of course, it was presented in the critical analysis of researchers' points of view. Now we summarize it as follows:
1- The traditional division of disciplines has lost its importance or at least has been weakened due to the ocean of data. Data is independent of the field, and therefore interdisciplinary cooperation in the “agnostic” situation of science might be irrelevant. Of course, we are not of the agnostic belief that theory has lost its importance in the big-data age, as Chris Anderson claims in his article “The End of Theory: The Data Deluge Makes the Scientific Method Obsolete”. But without this agnostic approach, we can also accept that the role of theories, at least at the level of description, is greatly reduced, and therefore we can accept that data analysis is possible without disciplinary affiliation, and as a result, interdisciplinary collaborations are also shaky.
2- Data-driven science increases the role of correlation compared to causal theories and increases the role of researcher decision-making in the application of knowledge.  Application means that a correlation is functionally important without depending on a specific discipline, and it can be used independently of any discipline; only to solve problems. The problems are not within the disciplines, but are located in the real world and impose themselves on us independently of the theories and disciplines. To solve a problem, numerous disciplines can be considered. These different perspectives mean that “a problem” is not dependent on any of these perspectives (disciplines). The problem of inflation can be seen from the perspective of economics, social psychology, political science, etc.
3- Weakening the role of theory and discipline in scientific development opens another field for scientific activities. New actors enter into scientific activities to the extent possible to play a competitive role with traditional researchers in scientific development. While the methodological changes produced by big data do not seem to be sufficient to invoke an entirely new paradigm in knowledge discovery, the emergence of big data has profoundly shaped the actors involved and their relationships. Moreover, even, the transition of scientific authority is predictable. In the age of big data, the shift of scientific authority from researchers and scientists (the followers and holders of grand theorists) to technicians, digital businessmen, and even ordinary users of big data can be expected. According to Chang et al., categories of mass data have emerged, which are caused by interactions, economies, interactions of societies or nations, and interactions of individuals. Public access to these data and especially facilitating the use of information technology tools can enable a large number of non-professional users in the field of research even with basic knowledge of statistics and data analysis in the field of science production. It is useful to remember that before the appearance of statistical software such as SPSS and SAS, performing a statistical analysis requires familiarity with programming skills. With the development of this software, more researchers were able to perform statistical operations because programming skills were removed from this process. Similarly, increased access to big data and analytical technologies resulting from new tools enable more "people" to analyze data and discover correlations between data for personal or business purposes or socio-cultural interactions. The production of public knowledge by people who are considered unprofessional according to "academic standards" is an important aspect in the evolution of scientific epistemology in the age of big data and analytical tools of information technology. The aggregative and generalized structure of scientific activity (if such a structure is important anymore) which was done by professional researchers and scientists through the structures of knowledge sharing and reproduction, will be performed by the machine. Knowledge activity will be displaced from its traditional institutional context. This is why I say that the implicit structure of authority that has been created over time by scientists and researchers is disrupted by "new revolutionaries" in the world of science. The institution of power in the production of science becomes shaky, scattered, multipolar, and rather rebellious. The problem is that in the previous paradigms, a kind of hierarchical structure of power or authority or scientific authority had emerged. The new paradigm targets exactly this hierarchical structure. Everyone can observe the big data and make inferences from it: No prior expertise; not just without prior theory; in an "agnostic platform" and without dependence on any field or discipline; without aristocracy of epistemological knowledge or any other theory and with a disruption from previous scholars and scientists.
4- Massification of actors raises the question of whether the accumulative, aggregative, and evolutionary characteristics of science, as seen in the history of science, do not undergo a radical transformation. Doesn't it go out of its institutional context, i.e. the field of "academy"? Microsoft, Apple, Facebook, Telegram, WhatsApp and many others have come to the field of innovation by people whose original innovators were often not "scientists" in the conventional sense, and sometimes even dropped out of university. These initiatives and innovations have been the source of the growth of science. The result is that scientific evolution has come from the academic environment to the business environment. Science has become more dependent on the market than before, and the "dynamism" of the market has become the source of the "dynamism" of science. Information technology has provided such a platform by facilitating communication and combining various technologies to provide a context for mutual leap. Science is neither interdisciplinary nor disciplinary but non-disciplinary. This can disrupt the entire structure of science that has dominated since the Renaissance.