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The strong limitations of the expressiveness of the existing well known data modelling languages combined with the lack of a very general universal data modeling language have negative impact to modelling naturalness. As the result of mentioned limits the reality must be transformed to avoid (workaround) the limits introduced by the modelling language. In turn, the transformation process requires extra effort. The problem is strengthened by the lack of mechanisms, which can be used to measure the expressiveness of a particular data modeling language. Some limitations of the existing data modeling languages result from both their metamodel (abstract syntax) and model (metamodel instance) graph-like structure constraints. This kind of limits also has negative impact to a domain-specific modeling naturalness. The paper addresses all problems mentioned above. The problems can be solved with the help of the EGG data modeling language introduced in the paper. First, a universal and customizable EGG data modeling language together with the customization mechanisms (extensions and generalizations) is introduced. According to the first usage scenario the EGG may be applied for domain-specific data modelling tasks in place of other data modeling languages. Second, the paper proposes and applies (for some data modeling languages: RDF, XML, RDBM, UML and AOM) a novel concept of measuring and comparing data modelling languages via mapping their metamodels to the EGG metamodel. So, according to the second usage scenario the EGG metamodel can be used as a reference metamodel for the data modeling language expressiveness comparative studies. It may also support the decision process when a data modeling language must be chosen for a particular domain-specific data modeling task. Third, the EGG introduced in the paper helps to avoid transforming reality to the needs resulting from the data modeling language as the EGG is general enough for the domain data modeling task. Complete abstract syntax of the Extended Generalized Graph is introduced and is expressed through its implementations in terms of the Association-Oriented Metamodel and the Unified Modeling Language. Semantics of each syntactical category of abstract syntax is described. Two complete concrete syntaxes for the Extended Generalized Graph are also introduced in the paper. The case studies related to both social network and knowledge modeling illustrate the applicability and usefulness of the EGG. Abstract syntax is compared to several other metamodels. The comparative study of the case study models created first in different metamodels and then expressed in the Extended Generalized Graph metamodel is summarized quantitatively in the form of a proposed measure.<\/jats:p>","DOI":"10.1007\/s10489-022-04440-0","type":"journal-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T12:04:09Z","timestamp":1678881849000},"page":"8510-8535","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The analysis of data metamodels\u2019 extensional layer via extended generalized graph"],"prefix":"10.1007","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7387-9210","authenticated-orcid":false,"given":"Marcin","family":"Jod\u0142owiec","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marek","family":"Kr\u00f3tkiewicz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Piotr","family":"Zabawa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,3,15]]},"reference":[{"key":"4440_CR1","doi-asserted-by":"publisher","first-page":"103449","DOI":"10.1016\/j.compind.2021.103449","volume":"129","author":"X Li","year":"2021","unstructured":"Li X, Lyu M, Wang Z, Chen C-H, Zheng P (2021) Exploiting knowledge graphs in industrial products and services: a survey of key aspects, challenges, and future perspectives. 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