Formal Rules to Produce Object Notation for EXPRESS Schema-Driven Data
https://doi.org/10.15514/ISPRAS-2021-33(5)-1
Abstract
Recently, product data management systems (PDM) are widely used to conduct complex multidisciplinary projects in various industrial domains. The PDM systems enable teams of designers, engineers, and managers to remotely communicate on a network, exchange and share common product information. To integrate CAD/CAM/CAE applications with the PDM systems and ensure their interoperability, a dedicated family of standards STEP (ISO 10303) has been developed and employed. The STEP defines an object-oriented language EXPRESS to formally specify information schemas as well as file formats to store and transfer product data driven by these schemas. These are clear text encoding format SPF and STEP-XML. Nowadays, with the development and widespread adoption of Web technologies, the JSON language is getting increasingly popular due to it being apropos for the tasks of object-oriented data exchange and storage, as well as its simple, easy to parse syntax. The paper explores the topic of the suitability of the JSON language for the unambiguous representation, storage and interpretation of product data. Under the assumption that the product data can be described by arbitrary information schemas in EXPRESS, formal rules for the producing JSON notation are proposed and presented. Explanatory examples are provided to illustrate the proposed rules. The results of computational experiments conducted confirm the advantages of the JSON format compared to SPF and STEP-XML, and motivate its widespread adoption when integrating software applications.
About the Authors
Vitaly Adolfovich SEMENOVRussian Federation
Doctor of Physical-Mathematical Sciences, Professor, Head of the Department of System Integration and Multi-disciplinary Applied Systems
Semen Vasilyevich ARISHIN
Russian Federation
Postgraduate student
Georgii Vitalyevich SEMENOV
Russian Federation
Student
References
1. ISO 10303. Industrial automation systems and integration — Product data representation and exchange.
2. ISO 10303-11:2004. Industrial automation systems and integration — Product data representation and exchange — Part 11: Description methods: The EXPRESS language reference manual.
3. ISO 10303-11:1994. Industrial automation systems and integration — Product data representation and exchange — Part 11: Description methods: The EXPRESS language reference manual.
4. ISO 10303-21:2016. Industrial automation systems and integration — Product data representation and exchange — Part 21: Implementation methods: Clear text encoding of the exchange structure.
5. ISO 10303-28:2007. Industrial automation systems and integration — Product data representation and exchange — Part 28: Implementation methods: XML representations of EXPRESS schema and data.
6. T. Bray. The JavaScript Object Notation (JSON) data interchange format. Internet Engineering Task Force (IETF), Request for Comments: 8259, 2014.
7. D. Peng, L. Cao, W. Xu. Using JSON for data exchanging in web service applications. Journal of Computational Information Systems, 2011, vol. 7, no. 16, pp. 7552-7569.
8. N. Nurseitov, M. Paulson et al. Comparison of JSON and XML Data Interchange Formats.
9. Base64. https://en.wikipedia.org/wiki/Base64
10. ISO 16739-1:2018. Industry Foundation Classes (IFC) for data sharing in the construction and facility management industries.
11. K. Afsari, Charles M. Eastman, Daniel Castro-Lacouture. JavaScript Object Notation (JSON) data serialization for IFC schema in web-based BIM data exchange. Automation in Construction, 2017, vol. 77, pp. 24-51.
12. V. Semenov, D. Ilyin, S. Morozov, O. Tarlapan. Effective consistency management for large-scale product data. // Journal of Industrial Information Integration, 2019, vol. 13, pp. 13-21.
Review
For citations:
SEMENOV V.A., ARISHIN S.V., SEMENOV G.V. Formal Rules to Produce Object Notation for EXPRESS Schema-Driven Data. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2021;33(5):7-24. (In Russ.) https://doi.org/10.15514/ISPRAS-2021-33(5)-1