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Revisiting the dataflow principle for chemical information processing

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Dataflow systems, such as Pipeline Pilot or KNIME have become important mainstream tools for data processing in chemistry. These established systems are all implemented relying on a data model emphasizing a strict row/column-centric data table view which does not facilitate interaction with individual chemistry objects, or non-uniform data contents.

Resuming our pioneering work which resulted in the implementation of the first dataflow system for chemistry [1], we present in this contribution a different, object-centric approach for the design of re-usable chemical information processing sequences. Our system is based on the metaphor of a factory floor, instead of opaque pipelines. Individual machining stations perform configurable processing steps on objects such as structures, reactions, datasets or tables. Objects are transported between these - or temporarily set on the factory floor for storage or inspection. The combination of this general concept with the extensive scripting functionality of the Cactvs Chemoinformatics toolkit results in a system with capabilities notably different and more flexible than standard pipelining systems.

References

  1. 1.

    Ihlenfeldt , Takahashi , Abe : . Proc. 28th Annual Hawaii International Conference on System Sciences. 1995, 227-236.

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Correspondence to Wolf D Ihlenfeldt.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Ihlenfeldt, W.D. Revisiting the dataflow principle for chemical information processing. J Cheminform 4, P15 (2012) doi:10.1186/1758-2946-4-S1-P15

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Keywords

  • Machine Station
  • Metaphor
  • Processing Sequence
  • Data Content
  • Configurable Processing