Data type definition and handling for supporting interoperability across organizational borders

Dávid Karnok (), Zsolt Kemény (), Elisabeth Ilie-Zudor () and László Monostori ()
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Dávid Karnok: Hungarian Academy of Sciences (MTA SZTAKI)
Zsolt Kemény: Hungarian Academy of Sciences (MTA SZTAKI)
Elisabeth Ilie-Zudor: Hungarian Academy of Sciences (MTA SZTAKI)
László Monostori: Hungarian Academy of Sciences (MTA SZTAKI)

Journal of Intelligent Manufacturing, 2016, vol. 27, issue 1, No 11, 167-185

Abstract: Abstract Organisational heterogeneity—especially in networks where new members may join at any time—requires ongoing actions to maintain interoperability. On the level of data interoperability, this highlights the importance of various aspects of data model and dataflow design, as well as handling of data at run-time. The latter is certain to require automated means of data model negotiation, and—while today’s design processes are far from fully automated—such means can leverage productivity and support verification procedures in data modelling and dataflow design as well. The paper presents results in one possible approach to data type definition and manipulation, through the example of the ADVANCE dataflow engine and its type-related features. Aside from an XML-based type system, type inference algorithms are presented which are employed both during design and flow execution.

Keywords: Type inference; XML type system; Dataflow; Enterprise network (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10845-014-0884-9

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