ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 2. Vol. 29. 2023

DOI: 10.17587/it.29.72-83

A. N. Rodionov, Dr. of Tech. Sc.,
Computer Centre of Far-Eastern Branch of RAS, Khabarovsk, 680035, Russian Federation

Typology and Modeling Profiles of Moving-Class Process-Entity Interactions: Core Types, Relationships, Constraints and Subschemas

Most of scientific research that are immediately concerned with the development of domain digital models, to one degree or another, is aimed at the derivation of reference conceptual and logical constructions covering all pertinent classes of interactions in which real-world objects with concomitant constraints can be involved. This work is directed to forming the core of a structural template that models facts — instances of associates that arise during the movement (transportation) of freights. The multiple alternatives and high variability of any processes logic, including moving-class processes, make their complete unification problematic. Nevertheless, one can come down to process modeling from a system-wide perspective, focusing on the capture of universal permanent processes components, such as source and output sets of objects, associations and constraints. The reality exhibits examples of hierarchical coherence of any classes of generalized processes, which in their sequential development break up into several self-sufficient processes distributed between organizational, calendar and implementation phases. The main focus of the work is on the sequential (from simple to complex) configuration of the structural core of process-entity interactions in the organizational phase, covering route segments, transport and freights, as well as the study of constraints on permissible instances of links incoming into the corresponding associative complex. Conceptual diagrams are presented in simplified and thorough formats. In a simplified format, multi-valued dependencies are modeled by means of weak entities and relators. In a thorough format, weak entities and relators have been replaced with documentary types, the structures of which contain an eXhaustive set of information about all objects, including auXiliary ones that are involved in interactions. The paper also considers the influence of the environment that is represented by classifying sets on the content of bounded relationships operating between the entity and process types. We have ascertained, formalized and described all constraints appearing in the organizational phase of generalized transport process including new constraint kind — split dependent link, resulting from the formation of cycles in conceptual constructions. Similar cycles contain and link together split, entity and (or) process types.
Keywords: assembling-class, process-entity interactions, levels and phases of the generalized process, prototype- sample/ individual kinds, bounded and targeted associations, split dependent link constraint

P. 72–83

References

1. Ruy F. B., Guizzardi G., Falbo R. A., Reginato C. C., Santos V. A. From reference ontologies to ontology patterns and back, Data and knowledge engineering, 2017, vol. 109, pp. 41—69.
2. Mecca G., Rull G., Santoro D., Teniente E. Ontology-based mappings, Data and knowledge engineering, 2015, no. 98, pp. 8—29.
3. Keet C. Maria, Fillottrani P. R. An ontology-driven unifying metamodel of UML Class Diagrams, EER, and ORM2, Data and knowledge engineering, 2015, no. 98, pp. 30—53.
4. Yang L., Cormican K., Yu M. Ontology-based systems engineering: A state-of-the-art review, Computer in industry, 2019, no. 111, pp. 148—171.
5. Verdonc M., Gailly F., Pergl R. et al. Comparing tra­ditional conceptual modeling with ontology-driven conceptual modeling: An empirical study, Information systems, 2019, no. 81, pp. 92—103.
6. Ghorbel F., Hamdi F., Metais E, Ellouze N., Gargoiri F. Ontology-based representation and reasoning about precise and imprecise temporal data: A fuzzy-based view, Data and knowledge engineering, 2019, no. 124, pp. 1—26.
7. Kogalovsky M. R., Kalinichenko L. A. Conceptual and logical modeling in information systems, Programmirovanie, 2009, no. 5, pp. 3—25 (in Russian).
8. Guizzardi G., Fonseca C. M. et al. Types and taxonomic structures in conceptual modeling: a novel ontological theory and engineering support, Data and knowledge engineering, 2021, vol. 134.
9. Guizzardi G. Ontological foundations for structural conceptual models. Center for Telematics and Information Techno­logy, University of Twente, The Nethelands, 2005, 441 p.
10. Elmasri R., Weeldreyer J., Hevner A. The category con­cept: An extension to the entity-relationship model, Data and knowledge engineering, 1985, vol. 1, pp. 75—116.
11. Hartmann. S., Link S. Collection type constructors in entity-relationship modeling, Conceptual modeling, ER 2007, 2007, pp. 307—322.
12. Halpin T., Morgan T. Information modeling and relational databases, Morgan Kaufmann Publishers, 2008, 970 p.
13. Patridge C., Sergio de Cesare, Mitchell A., Odell J. Formalization of the classification pattern: survey of classification modeling in information system engineering, Software and system modeling, 2018, vol. 17, no. 1, pp. 167—203.
14. Cabot J., Raventos R. Conceptual modeling patterns for roles, Journal on data semantics V LNCS 3870, 2006, pp. 158—184.
15. Guizzardi G., Fonseca C. M. et al. Endurant types in ontology-driven conceptual modeling: towards OntoUML 2.0, Conceptual modeling, ER 2018, 2018, pp. 136—150.
16. Sales T. P., Guizzardi G. Ontological anti-patterns: empirically uncovered error-prone structures in ontology-driven conceptual models, Data and knowledge engineering, 2015, vol. 99, pp. 72—104.
17. Guizzardi G. Ontological patterns, anti-patterns and pattern languages for next-generation conceptual modeling, Concep­tual modeling, ER 2014, 2014, pp. 13—27.
18. Santos P. S., Almeida J. P., Guizzardi G. An ontology-based analysis and semantics for organizational structure in the ARIS method, Information systems, 2013, no. 38, pp. 690—708.
19. Romanenko E. et al. Abstracting ontology-driven conceptual models: objects, aspects events, ant their parts, Conference: International Conference on Research Challenges in Information Science, 2022, pp. 372—388.
20. Silverstone L. The data model resource book. A library of universal data models for all enterprises, 2001, vol. 1, Wiley, New York.
21. Silverstone L. The data model resource book. A library of universal data models by industry types, 2001, Wiley, vol. 2, New York.
22. Silverstone L., Agnew P. The data model resource book. Universal patterns for data modeling 2009, vol. 3, Wiley, New York.
23. Leopold H., Pittke F., Mendling J. Ensuring the can-onicity of process models, Data and knowledge engineering, 2017, no. 111, pp. 22—38.
24. Rodionov À. N. Typology and modeling profiles of AS-class process-entity interactions: structures, constraints, phases and evolution of process phases, Information technologies, 2022, no. 4, vol. 28, pp. 191—201 (in Russian).
25. Rodionov À. N., Rezak E. V. Typology and modeling profiles of AS-class process-entity interactions: object actualization and base schema adaptation, Information technologies, 2022, no. 64, vol. 28, pp. 309—318 (in Russian).
26. Rodionov A. N. "Migrating" objects of data models: "weak entities" and documents, Vestnik KSAEL, 2011, no. 1. pp. 40—65 (in Russian).
    

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