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Data type definition and handling for supporting interoperability across organizational borders

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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.

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Acknowledgments

Work presented in the paper was supported by the EU FP7 under Grant No. 257398, “ADVANCE—advanced predictive-analysis-based decision-support engine for logistics”, http://advance-logistics.eu/.

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Authors and Affiliations

  1. Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI), Kende u. 13–17, 1111 , Budapest, Hungary

    Dávid Karnok, Zsolt Kemény, Elisabeth Ilie-Zudor & László Monostori

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  1. Dávid Karnok
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  2. Zsolt Kemény
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  3. Elisabeth Ilie-Zudor
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  4. László Monostori
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Correspondence to Elisabeth Ilie-Zudor.

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Karnok, D., Kemény, Z., Ilie-Zudor, E. et al. Data type definition and handling for supporting interoperability across organizational borders. J Intell Manuf 27, 167–185 (2016). https://doi.org/10.1007/s10845-014-0884-9

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