Knowledge Amalgamation for Computational Science and Engineering

  • Theresa PollingerEmail author
  • Michael Kohlhase
  • Harald Köstler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11006)


This paper addresses a knowledge gap that is commonly encountered in computational science and engineering: To set up a simulation, we need to combine domain knowledge (usually in terms of physical principles), model knowledge (e.g. about suitable partial differential equations) with simulation (i.e. numerics/computing) knowledge. In current practice, this is resolved by intense collaboration between experts, which incurs non-trivial translation and communication overheads. We propose an alternate solution, based on mathematical knowledge management (MKM) techniques, specifically theory graphs and active documents: Given a theory graph representation of the domain, model, and background mathematics, we can derive a targeted knowledge acquisition dialogue that supports the formalization of domain knowledge, combines it with simulation knowledge and – in the end – drives a simulation run – a process we call MoSIS (“Models-to-Simulations Interface System”). We present the MoSIS prototype that implements this process based on a custom Jupyter kernel for the user interface and the theory-graph-based Mmt knowledge management system as an MKM backend.



The authors acknowledge financial support from the OpenDreamKit Horizon 2020 European Research Infrastructures project (#676541); Project ExaStencils received funding within the DFG priority programme 1648 SPPEXA. We gratefully acknowledge fruitful discussions with the KWARC group, especially Dennis Müller and Florian Rabe for support with the Mmt implementation, to Thomas Koprucki and Karsten Tabelow at WIAS Berlin; and to Sebastian Kuckuk (LSS chair, FAU). Last but not least, Kai Amman and Tom Wiesing have helped with the Jupyter frontend and deployment of MoSIS on JupyterHub.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Theresa Pollinger
    • 1
    Email author
  • Michael Kohlhase
    • 1
  • Harald Köstler
    • 1
  1. 1.Computer ScienceFAU Erlangen-NürnbergErlangenGermany

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