History science in Big Data era: unused opportunities and perspectives

Sinitsyn, Maxim Vladislavovich
MSU Institute for Artificial Intelligence, Lomonosov Moscow State University, Moscow, Russia

The subject of history science is to identify the patterns of causes and effects of events. To do this, it is necessary to collect and analyze large amounts of data on the topic under study. In the context of collecting information, significant progress has been made in digitizing archival documents and printed works (newspapers, books, magazines), as a result of which the level of access to documents can already exceed a person's ability to analyze them. Therefore, the unsolved problem of developing data analysis tools for the purpose of automating historical work is coming to the first plan today. Of course, it is not possible to automate the process of identifying causes and effects at this moment, even with the use of artificial intelligence technologies. It is much more important to create a software shell with automated search and analysis functions based on the methodology of historical science. As the result of its use, both the materials that the researcher got acquainted with and his final work will be visible. Thus, the researcher's logic is defined as a "black box" in the cybernetic sense. Development of such software will, on the one hand, significantly facilitate the historical work of processing information and generalizing the experience of the past, on the other hand, open the way for the creation of recommendation systems for both historians and current information and analytical workers.

Keywords: history science, historical computing, Information analysis systems, decision support system, methodology of history science, problems of historical knowledge