Abstract
The recommended interpretation of the “What” facet in the Zachman Framework is that it serves as a data-centric viewpoint on the enterprise, capturing data requirements across several layers of abstraction – from high-level business concepts down to implemented data entities. In enterprise modelling, these have been traditionally approached through well-established practices and modelling techniques – i.e., Entity-Relationship models, UML class models and other types of popular data model types. In the current context of digital transformation and agile enterprise relying on distributed information systems, certain technological specifics are lost when employing traditional methods acting on a high level of abstraction. For example, the Linked Data paradigm advocates specific data distribution, publishing and retrieval techniques that would be useful if assimilated on a modelling level - in what could be characterised as technology-specific modelling methods (mirroring the field of domain-specific languages, but from a technological perspective). This paper proposes an agile modelling language that provides a diagrammatic and, at the same time, machine-readable integration of several of the Zachman Framework facets. In this language, the “What” facet covers concepts met in a Linked Enterprise Data environment – e.g., graph servers, graph databases, RESTful HTTP requests. These have been conceptualised in the proposed language and implemented in a way that allows the generation of a particular kind of code – process-driven orchestration of PHP-based SPARQL client requests.
Keywords
- Zachman Framework
- SPARQL orchestration
- Resource Description Framework
- Agile Modelling Method Engineering
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Acknowledgment
This work is supported by the Romanian National Research Authority through UEFISCDI, under grant agreement PN-III-P2-2.1-PED-2016-1140.
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Harkai, A., Cinpoeru, M., Buchmann, R.A. (2018). The “What” Facet of the Zachman Framework – A Linked Data-Driven Interpretation. In: Matulevičius, R., Dijkman, R. (eds) Advanced Information Systems Engineering Workshops. CAiSE 2018. Lecture Notes in Business Information Processing, vol 316. Springer, Cham. https://doi.org/10.1007/978-3-319-92898-2_17
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