Graphical Notation for Document Database Modeling

Goals and objectives. Graphical models have proven to be a reliable, clear and convenient tool for creating sketch models of databases. Most of the existing notations are designed for the relational data model, the dominant data model for the last thirty years. However, the development of information technologies has led to an increase in the popularity of non-relational data models, primarily the document model. One of the problems of its application in practice is the lack of suitable tools that allow performing graphical modeling of the database, taking into account the features of the document model, at the stage of logical design. The development of appropriate tools is an important and actual task, since their application in practical research makes it possible to identify, classify and analyze typical modeling errors that allow the designer to reduce the risk of their occurrence in the future. The purpose of this article is to develop a graphical notation that, on the one hand, providing convenience for the designer, and on the other hand, taking into account the peculiarities of creating and functioning of the noSQL document storage model.
Materials and methods. The materials for the study were numerous publications devoted to the development of graphical notations in problems and their application to database design for various information systems. The selected materials were analyzed and the main graphical notations used to describe the relational data model were identified. Three notations were selected from them, a set of graphic stereotypes, which were most different from each other, the analysis of which allowed us to identify the main image patterns of the components of the relational model.
The resulting patterns were applied to the main elements of the document database, which were obtained by analyzing the documentation of the popular MongoDB DBMS.
Results. The result of the research was the creation of a new tool for modeling document databases at the logical level, which consists of a set of graphic stereotypes and rules for their application. On the one hand, the development is well known to practitioners who have previously worked with relational data models, since its development took into account many years of experience in using graphical models in the field of relational database design, and on the other hand, it reflects the features of the structure of the document model.
Conclusion. The practical application of the developed model has shown the convenience of its use both in the process of designing document databases and in the process of teaching students within this subject area. The use of graphical models constructed in the proposed graphical notation will allow researchers to create and illustrate typical patterns of document databases, which will undoubtedly have a positive impact on the dynamics of the development of promising data storage technologies.

1. Kuznetsov S.D. Bazy dannykh: yazyki i modeli = Databases: languages and models. Moscow: OOO Binom-Press; 2008. 720 p. (In Russ.)

2. Popov F. A., Maksimov A. V. Approaches to designing databases for automated systems [Internet]. Izvestiya AltGU = News of Altai State University. 2003; 1. Available from: https://cyberleninka.ru/article/n/podhody-k-proektirovaniyu-baz-dannyh-dlya-avtomatizirovannyh-sistem. (cited 20.07.2021). (In Russ.)

3. Codd E. F. A relational model of data for large shared data banks. Comm. ACM. 1970; 113(6).

4. Chen P. The Entity-Relationship Modelñ Toward a Unified View of Data. ACM Transactions on Database Systems. 1976; 1: 11.

5. Moniruzzaman A. B. M., Hossain S. A. Nosql database: New era of databases for big data analytics- classification, characteristics and comparison. arXiv preprint arXiv:1307.0191. 2013.

6. DBMS popularity broken down by database model [Internet]. Available from: https://db-engines.com/en/ranking_categories. (cited 01.08.2021).

7. Mironov V.V., Gusarenko A.S., Yusupova N.I. Situation-oriented databases as a virtual integration layer in web applications. Information Technologies for Intelligent Decision Making Support (ITIDS’2016). 2016: 123-128. (In Russ.)

8. Zimovets A.I., Khomonenko A.D. Substantiation of the choice of data storage model for the space monitoring system. Avtomatika na transporte = Automation on transport. 2019; 5: 2. (In Russ.)

9. Blinkov Yu.A., Pankratov I.A. Document- oriented storage and processing of scientific publications. Matematicheskoye modelirovaniye, komp’yuternyy i naturnyy eksperiment v yestestvennykh naukakh = Mathematical modeling, computer and natural experiment in natural sciences. 2018; 4: 28-36. (In Russ.)

10. Bederdinova O.I. Results of designing a database of a complex of equipment for sawmilling processes using case-technology IDEF1X. Informatsionnyye tekhnologii v proyektirovanii i proizvodstve = Information technologies in design and production. 2007; 3: 33-35. (In Russ.)

11. Glavnaya stranitsa MSUniversity = Main page of MSUniversity [Internet]. MSUniverdity. ru. Available from: http://msuniversity.ru. (cited 20.05.2021). (In Russ.)

12. Alekseyev V.A., Telegina M.V., Yannikov I.M. Creation of a database of biomonitoring of potentially dangerous objects. Vestnik Izhevskogo gosudarstvennogo tekhnicheskogo universiteta = Bulletin of the Izhevsk State Technical University. 2008; 4: 138-143. (In Russ.)

13. Azovtsev A.I. et al. Development of an infological model of a database of preliminary informing of customs authorities for a shipping company. Morskiye intellektual’nyye tekhnologii = Marine intellectual technologies. 2016; 3(1): 327-332. (In Russ.)

14. Gorshkov Ye.A., Kalinina A.V., Kulikova S.A. Application of modeling principles for automation of office activities of sanatorium-resort institutions. BBK 1 N 34 = LBC 1 N 34.. 2019: 1683. (In Russ.)

15. Kusiak A., Letsche T., Zakarian A. Data modelling with IDEF1x. International Journal of Computer Integrated Manufacturing. 1997; 10; 6: 470-486. DOI: 10.1080/095119297131039.

16. Everest G. C. Basic data structure models explained with a common example. Proc. Fifth Texas Conference on Computing Systems. 1976: 18-19.

17. Yusupova D.Zh. Possibilities of the semantic model of ERD at the stage of infological database design. Sovremennyye materialy, tekhnika i tekhnologiya = Modern materials, equipment and technology. 2019: 423-425. (In Russ.)

18. Gorshkov Ye.A., Kalinina A.V., Kulikova S.A. Application of modeling principles for automation of office activities of sanatorium-resort institutions. BBK 1 N 34 = LBC 1 N 34. 2019: 1683. (In Russ.)

19. Hay D.C. A comparison of data modeling techniques. Essential Strategies. 1999: 41: 43.

20. Dokumentatsiya MongoDB [Internet]. Available from: https://docs.mongodb.com (cited 25.05.2021).

21. Stranitsa Veb-prilozheniya JSONDesigner [Internet]. Available from: https://jsondesigner.com/#/. (cited 19.05.2021).