Abstract. 

In the context of the rapid digitalization of the economy, both the volume of digital data and their value are increasing. Distortion of this data is certainly unacceptable and will lead to large material and non-material losses. One of the problems when working with digital data, especially with their long-term storage, is the problem of data interpretation. This article proposes a solution to the problem of interpreting digital distributed long-term keeping data by developing a long-term keeping format, which, along with a mathematical model of long-term keeping digital data, allows solving the problem of interpretability. The article provides an overview of the existing digital data formats. Their advantages and disadvantages are determined. The necessity of creating a custom format has been proved, which would take into account, on the one hand, the heterogeneity of digital data, on the other hand, it would allow organizing access to separate parts of distributed data, on the other hand, it would make it easy to interpret the data in the event of a failure or lack of interpretation software. As a practical result, within the framework of the study, a long-term keeping format based on a subset of the XML language was created. The created format has passed practical testing. In the future, its wider implementation and modernization is planned.

Keywords: 

digital data, long-term keeping, file format, electronic document, digitalization, digital economy

PP. 43-49.

DOI: 10.14357/20790279210206

 

References

1. Solovyev, A.V. 2020. Long-Term Digital Documents Storage Technology. Lecture Notes in Electrical Engineering. 641: 901-911.

2. Solovyev, A.V. 2020. Authentication control algorithm for long-term keeping of digital data. IOP Conference Series: Materials Science and Engineering (MSE). 862(5): 052080.

3. Solovyev, A.V. 2020. Digital media inventory algorithm for long-term digital keeping problem. IOP Conference Series: Materials Science and Engineering (MSE). 919(5): 052003.

4. Open Government Partnership UK National Action Plan. 2013. London. SW1A 2AS. 58 p.

5. Pitman, N., and Shipman, A. 2008. A manager’s guide to the long-term preservation of electronic documents. London. BIP 0089 BSI. 110 p.

6. Universal Electronic Records Management (ERM) Requirements. 2017. U. S. National Archives and Records Administration. 2017. Available at:

https://www.archives.gov/records-mgmt/policy/universalermrequirements (accessed March 25, 2021).

7. Microsoft Office Word 97–2007 Binary File Format (.doc) Specification. 2017. Microsoft Corporation. 210 p.

8. WebP – a new image format for the Web. 2013. Google. Available at: https://developers.google.com/speed/webp/ (accessed March 25, 2021).

9. Nikolayev, D.P., Postnikov, V.V., and Usilin, S.A. 2009. Cognitive PDF/A – tekhnologiya otsifrovki tekstovykh dokumentov dlya publikatsii v Internet i dolgovremennogo arkhivnogo khraneniya [Cognitive PDF / A – technology for digitizing text documents for publication on the Internet and longterm archival storage]. Trudy ISA RAN [Proceedings of the ISA RAS]. 45. P. 159–173.

10. Berestova, V.I. 2014. Sredstva i metody sozdaniya elektronnogo dokumenta, soderzhashchego graficheskiye obrazy [Means and methods for creating an electronic document containing graphic images]. Deloproizvodstvo [J Office work]. 1. P. 45–56.

11. Bakanova N.B., and Solovyev A.V. 2020. Algoritm depersonalizatsii dannykh pri informatsionnom obmene v tsifrovoy ekonomike [Data Depersonalization Algorithm for Information Exchange in the Digital Economy]. Trudy ISA RAN [Proceedings of the ISA RAS]. 70(2). P. 12–20.

12. Akimova G.P., Pashkin M.A., Soloviev A.V., and Tarkhanov I.A. 2020. Modeling the methodology to assess the effectiveness of distributed information systems. Advances in Science, Technology and Engineering Systems. 5(1). P. 86–92.

13. Solovyev A.V. 2017. Elektronnyye arkhivy: razrabotka matematicheskoy modeli elektronnogo dokumenta pri dolgovremennom khranenii [Electronic archives: development of mathematical models of electronic documents for long-term storage]. Informatsionnyye tekhnologii i vychislitel’nyye sistemy [Information Technology and Computing Systems]. 1. P. 46–61. 

14. Devyatkin D.A., Grigoriev O.G., Sokolov I.A., Suvorov R.E., Tikhomirov I.A., Zhebel’ V.V. 2019. On Creating a National System for Identifying Research and Development Priorities. Scientific and Technical Information Processing, Allerton Press, Inc., New York. 46(1). P. 14-19.