An Approach of Syntactic Description of the Annotated Metagraph Model
( Pp. 125-135)
More about authors
Gapanyuk Yuriy E.
Cand. Sci. (Eng.), Associate Professor; associate professor; Bauman Moscow State Technical University
Bauman Moscow State Technical University
Moscow, Russian Federation
Bauman Moscow State Technical University
Moscow, Russian Federation
Abstract:
The annotating metagraph model is a powerful tool for describing complex systems with hierarchy and emergent properties, yet its syntactic representation poses a non-trivial challenge. The purpose of this work is to investigate the problem of representing this model using popular graph description languages: DOT, GraphML, and JSON Graph Format. A comparative analysis of their syntactic capabilities is conducted by encoding metagraphs that contain nested and overlapping metavertices. The research concludes that these languages face fundamental limitations for metagraph description. Their syntax, based on a strict tree-like structure, prevents the accurate representation of key metagraph features, such as an element’s membership in multiple, overlapping metavertices. To address this issue, the paper proposes a new, specialized format called MetagraphYAML. Its id-based referencing system fully supports all capabilities of the annotating metagraph model, thereby overcoming the limitations of existing approaches.
How to Cite:
Gapanyuk Yu.E. An approach of syntactic description of the annotated metagraph model. Computational Nanotechnology. 13, 1 (2026), 125–135. DOI: 10.33693/2313-223X-2026-13-1-125-135. EDN: MHPHOR
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Voloshin V.I. Introduction to graph and hypergraph theory. New York: Nova Science Publishers, 2009. 260 p. ISBN: 978-1-60692-372-6.
Gapanyuk Yu.E. Stages of development of the metagraph data and knowledge model. In: Proceedings of the X International Scientific and Technical Conference “Integrated models and soft computing in artificial intelligence (IMSC-2021)”. In 2 vols. Vol. 1. 2021. Pp. 190–200.
Globa L.S., Ternovoy M.Yu., Shtogrina E.S. Metagraphs as a basis for the representation and use of fuzzy knowledge bases. In: Proceedings of the V International Scientific and Technical Conference “Open Semantic Technologies for Intelligent Systems (OSTIS-2015)”. Minsk: BSUIR, 2015. Pp. 237–240.
Abuoda G., Dell’Aglio D., Keen A., Hose K. Transforming RDF-star to property graphs: A Preliminary analysis of transformation approaches. arXiv: 2210.05781. DOI: 10.48550/arXiv.2210.05781.
Allemang D., Hendler J., Gandon F. Semantic Web for the working ontologist: Effective modeling for linked data, RDFS, and OWL. 3rd ed. Association for Computing Machinery, 2020. 512 p. ISBN: 978-1-4503-7614-3.
Basu A., Blanning R.W. Metagraphs and their applications. New York: Springer, 2007. 224 p. ISBN: 978-0-387-37234-1. DOI: 10.1007/978-0-387-37234-1.
Bergami G. A logical model for joining property graphs. arXiv: 2106.14766. (data of accesses: 04.12.2025).
Chernenkiy V., Gapanyuk Yu., Nardid A. et al. Using the metagraph approach for addressing RDF knowledge representation limitations. In: Internet Technologies and Applications (ITA). Wrexham: IEEE, 2017. Pp. 47–52. DOI: 10.1109/ITECHA.2017.8101909.
Gelling E., Fletcher G., Schmidt M. Bridging graph data models: RDF, RDF-star, and property graphs as directed acyclic graphs. arXiv: 2304.13097 (data of accesses: 04.12.2025).
Holt R.C., Winter A., Schürr A. GXL: Towards a standard exchange format // Fachbericht Informatik. Koblenz: Universität Koblenz–Landau, 2000.
Matsumoto S., Yamanaka R., Chiba H. Mapping RDF Graphs to Property Graphs. arXiv: 1812.01801 (data of accesses: 04.12.2025).
Voloshin V.I. Introduction to graph and hypergraph theory. New York: Nova Science Publishers, 2009. 260 p. ISBN: 978-1-60692-372-6.
Keywords:
DOT, GraphML, YAML, metagraph, metavertex, graph description language, DOT, GraphML, YAML, emergence.
