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2020 | OriginalPaper | Chapter

A Layered Approach to Lightweight Toolchaining in Visual Analytics

Authors : Hans-Jörg Schulz, Martin Röhlig, Lars Nonnemann, Marius Hogräfer, Mario Aehnelt, Bodo Urban, Heidrun Schumann

Published in: Computer Vision, Imaging and Computer Graphics Theory and Applications

Publisher: Springer International Publishing

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Abstract

The ongoing proliferation and differentiation of Visual Analytics to various application domains and usage scenarios has also resulted in a fragmentation of the software landscape for data analysis. Highly specialized tools are available that focus on one particular analysis task in one particular application domain. The interoperability of these tools, which are often research prototypes without support or proper documentation, is hardly ever considered outside of the toolset they were originally intended to work with. To nevertheless use and reuse them in other settings and together with other tools, so as to realize novel analysis procedures by using them in concert, we propose an approach for loosely coupling individual visual analytics tools together into toolchains. Our approach differs from existing such mechanisms by being lightweight in realizing a pairwise coupling between tools without a central broker, and by being layered into different aspects of such a coupling: the usage flow, the data flow, and the control flow. We present a model of this approach and showcase its usefulness with three different usage examples, each focusing on one of the layers.

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Title: A Layered Approach to Lightweight Toolchaining in Visual Analytics
Authors: Hans-Jörg Schulz
Martin Röhlig
Lars Nonnemann
Marius Hogräfer
Mario Aehnelt
Bodo Urban
Heidrun Schumann
Publisher: Springer International Publishing
Book: Computer Vision, Imaging and Computer Graphics Theory and Applications
Print ISBN: 978-3-030-41589-1

Electronic ISBN: 978-3-030-41590-7

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-41590-7_13

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