Abstract
Enterprise data is typically located in disparate legacy systems and heterogeneous sources. Researchers and business analysts identified the importance of integrating such data sources through a semantic data fabric to support the generation of valuable insights and consolidated views. Still, this objective is hard to attain as information is dispersed in ever-growing enterprise data lakes and silos. Some solutions are very abstract, taking the form of prescriptive enterprise frameworks, and therefore they do not provide operational mappings between data from real systems. In other cases the integration requires technical expertise that may be format-specific and, because of this, it is hard to cover heterogeneous technologies. It would be useful if those working on the enterprise architecture level could express on a high abstraction level the involved data sources and interlinking rules. This paper proposes a solution that enables integration management in a diagrammatic view that does not require expertise with data transformations. In support of this idea, we engineer a modelling method that provides (i) a front-end interface to enable the combination of relevant data with the help of an agile modelling language and (ii) the use of RDF as a common representation that captures the output of the modelled integrations in an Enterprise Knowledge Graph.
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Acknowledgements
This work was supported by a mobility grant of the Romanian Ministery of Research and Innovation, CNCS - UEFISCDI, project number PN-III-P1-1.1-MC-2019-0465, within PNCDI III.
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Ghiran, AM., Buchmann, R.A. (2019). The Model-Driven Enterprise Data Fabric: A Proposal Based on Conceptual Modelling and Knowledge Graphs. In: Douligeris, C., Karagiannis, D., Apostolou, D. (eds) Knowledge Science, Engineering and Management. KSEM 2019. Lecture Notes in Computer Science(), vol 11775. Springer, Cham. https://doi.org/10.1007/978-3-030-29551-6_51
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