From Prototype to Promise: MaRDIFlow Charts the Future of Math Computing

Table of Links

Abstract and 1. Introduction

Existing Solutions

2. MaRDIFlow

Minimum working examples

Spinodal decomposition in a binary A-B alloy

Summary and Outlook, Acknowledgments, Data Availability, and References

Summary and Outlook

The practice to perform data and software intensive tasks has been taken hold by computational workflows. Subsequently, the rapid growth in their uptake and application on computer-based experiments presents a crucial opportunity to advance the development of reproducible scientific softwares. As a part of the MaRDI consortium [MaR21] on research data management in mathematical sciences, in this work, we presented a novel computational workflow framework, namely, MaRDIFlow, a prototype that focuses on the automation of abstracting meta-data embedded in an ontology of mathematical objects while negating the underlying execution and environment dependencies into multi-layered vertical descriptions. Additionally, the different components are characterized by their input and output relation such that they can be used interchangeably and in most cases redundantly.

The design specification as well as the working prototype of our RDM tool was presented through different use cases. In the present version, MaRDIFlow acts a command-line tool such that it enables users to handle the workflow components as abstract objects described by input to output behavior. At its core, MaRDIFlow ensures that the output generated is detailed, and a comprehensive description facilitates the reproduction of computational experiments. At first we illustrated the conversion rates of CO2 using a methanization reactor model, and later, we demonstrated the two-dimensional spinodal decomposition of a virtual A-B alloy using the Cahn-Hilliard model. Our RDM tool adheres to FAIR principles, such that the abstracted workflow components are Findable, Accessible, Interoprable and Reusable. Overall, the ongoing development of MaRDIFlow aims at covering heterogeneous use cases and act as a scientific tool in the field of mathematical sciences.

Apart from this, we are also working towards developing an Electronic Lab Notebook (ELN) in order to visualize as well as execute the MaRDIFlow tool. The ELN will provide researchers with a user-friendly interface to interact with the tool efficiently and seamlessly. Lastly, although the present manuscript introduces our RDM tool as a working proof of concept, we plan to publish a detailed manuscript with technical details and use cases in the near future.

Acknowledgments

The authors are supported by NFDI4Cat and MaRDI, funded by the Deutsche Forschungsgemeinschaft (DFG), project 441926934 “NFDI4Cat – NFDI f¨ur Wissenschaften mit Bezug zur Katalyse” and project 460135501 “MaRDI – Mathematische Forschungsdateninitiative”.

Data Availability

Results presented in this work are apart of an ongoing investigation, however a working prototype with the second use-case is available and documented at https://doi.org/10.5281/zenodo.10608764

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