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Historical informatics
Reference:

Historical Information Science in the Context of Data Science (Round Table Materials)

Borodkin Leonid

Doctor of History

Professor, Historical Information Science Department, Faculty of History, Lomonosov Moscow State University

aud. 454,  27-4, ul. Lomonosovskii Prospekt, g. Moscow, Russia, 119991

lborodkin@mail.ru
Другие публикации этого автора
 

 
Vladimirov Vladimir

Doctor of History

Professor, the head of document studies, archival studies and historical information science department at Altai State University 

656049, Russia, Altaiskii krai, g. Barnaul, prospekt Lenina, 61, aud. 312

vvladimirov@icloud.com
Другие публикации этого автора
 

 

DOI:

10.7256/2585-7797.2020.2.33549

Review date:

23-07-2020


Publish date:

30-07-2020


Abstract.

The article focused on problems and prospects caused by the rapid development of data science and discusses the opinions and remarks made by the participants of the round table called "Methods and Technologies of Data Science: Its Prospects in Historical Research" held by the editorial board of the "Historical Information Science” journal " and the Association "History and Computer" on July 3, 2020. The round table was attended by over 60 teachers, researchers, as well as students from 5 countries. Online discussions and talks were assisted by Zoom video conferencing service. The participants addressed issues related to the term "data science" itself, artificial intelligence and big data issues. All these were discussed in the light of problems that arise and are solved in the framework of historical research. The speakers addressed the problem of historical sources digitization and text recognition, the opportunities of programming languages (R and Python) use as well as many other issues. The very fact of the round table and its results have demonstrated the undeniable usefulness of the dialogue and the need to develop this form of scientific contacts. It is emphasized that that the development of such a field as "digital historical source studies" is becoming more and more urgent.

Keywords: artificial neural networks, machine learning, artificial intelligence, big data, historical information science, data science, mathematical statistics, programming, digitization, image recognition
This article written in Russian. You can find full text of article in Russian here .

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