Институт развития информационного общества

IIS leaders and employees participated in the meeting of the Data Subcommittee as part of the Artificial Intelligence Technical Committee for Standardization

On December 1, 2021, the II annual meeting of the Data Subcommittee (PC 02), which is part of the Artificial Intelligence Technical Committee for Standardization (TC 164), took place online. The experts discussed the achieved results and future plans in the field of national and international big data standardization.

Let us recall that TC 164 is a national mirror image of the specialized international subcommittee ISO / IEC JTC 1 SC 42 “Artificial Intelligence”. PC 02 operates as part of TC 164, the functions of its secretariat are performed by the National Center for Digital Economy of Lomonosov Moscow State University. The activities of PC 02 are supported within the project of the NTI Competence Center for Big Data of MSU (NTI Center of MSU).

Bridging the gap between national and international standardization

“From the very beginning of its activities, our working group, and then the Data Subcommittee, we set a course for overcoming the lag of the Russian Federation from the international standardization of big data. Our subcommittee, together with experts, is successfully coping with this task,” noted Sergei Afanasyev, executive secretary of PC 02, leading specialist of the NTI Center of MSU.

Thus, the fundamental national terminological standard in the field of big data, harmonized with the international one, has already been approved and entered into force. A day after the meeting of the subcommittee, Rosstandart approved another national standard – GOST R 59926-2021 / ISO / IEC TR 20547-2: 2018 “Information technology. Big Data Reference Architecture. Part 2. Use Cases and Derived Requirements”. The aforementioned standards are identical to international ones and were prepared by the NTI Center of MSU together with the Institute of the Information Society (IIS). In addition, these organizations have developed an original national standard on the requirements for terms of reference in the field of operating with big data, which is also approved by Rosstandart on December 2, 2021 and will enter into force on March 1, 2022.

Two more developed draft standards in the area of ​​the big data reference architecture are awaiting approval, as well as a draft standard on a framework for managing big data analytics processes.

Parallel national and international standardization

Today, PC 02 is launching the development of a series of GOSTs dedicated to data quality for analytics and machine learning. This series of national standards is planned to be approved almost simultaneously with the corresponding international series.

“At the international level, a series of data quality standards is also still at the design stage, that is, they have not been approved. Therefore, work at the national and international levels is now being carried out in parallel. Thus, we can influence the content of the international series, representing Russia at the international level, and also not allow a lag – if it even occurs, it will be minimum,” said Sergei Afanasyev.

During the meeting, the subcommittee experts supported the idea of ​​actively participating in the development of a series of international data quality standards for analytics and machine learning.

“Issues of data quality are very important for the Russian Federation: for example, government data sets are massively created in the country. They are processed with the use of machine learning technologies. Participation in the development and adoption of data quality standards will serve the interests of Russia, will make it possible to use the advanced knowledge recorded in the standards being developed,” says Yuri Hohlov, head of PC 02, chairman of the IIS board of directors, project leader of the NTI Center of MSU.

The experts of the subcommittee also decided to recommend Rosstandart to vote for the international subcommittee of ISO / IEC JTC 1 SC 42 “Artificial Intelligence” to start working on international standardization of the life cycle structure for artificial intelligence data.

“It is imperative to conduct fundamental research on data quality and data lifecycle, especially in relation to big data analytics and machine learning. Such a study would help Russia to make a significant contribution to the development of international standards on a similar topic,” added Yuri Hohlov.

Presentations on the development of draft international standards on data quality for analytics and machine learning were also presented by Alexander Bogdanov, head of the IIS Directorate of digital technologies development, Professor of SPbSU, and Nadezhda Shchegoleva, head of IIS Department of big data technologies development, professor of SPbSU.

Source: NTI Center of MSU