Epistemic Metadata for Computational Engineering Information Systems

Author:

Horsch Martin Thomas12,Chiacchiera Silvia2,Guevara Carrión Gabriela3,Kohns Maximilian4,Müller Erich A.5,Šarić Denis3,Stephan Simon4,Todorov Ilian T.2,Vrabec Jadran3,Schembera Björn6

Affiliation:

1. Norwegian University of Life Sciences, Faculty of Science and Technology, Department of Data Science, Drøbakveien 31, 1430 Ås, Norway

2. UK Research and Innovation, STFC Daresbury Laboratory, Scientific Computing Department, Keckwick Ln, Daresbury WA4 4AD, UK

3. Technische Universität Berlin, Thermodynamics, Ernst-Reuter-Platz 1, 10587 Berlin, Germany

4. Rheinland-Pfälzische Technische Universität, Laboratory of Engineering Thermodynamics, Erwin-Schrödinger-Str. 44, 67663 Kaiserslautern, Germany

5. Imperial College London, Department of Chemical Engineering, South Kensington Campus, London SW7 2AZ, UK

6. University of Stuttgart, Institute of Applied Analysis and Numerical Simulation, Pfaffenwaldring 57, 70569 Stuttgart, Germany

Abstract

Digitalization is a priority for innovation in the engineering sciences. The digital transformation requires making the knowledge claims from scientific research data machine-actionable, so that they can be integrated and analysed with minimal human intervention. Up until now, the depth of digitalization is often too shallow, with annotations that are only of use to a human reader. In addition, digital infrastructures and their metadata standards are tedious to use: They demand too much effort from researchers, much of which goes into metadata that contribute nothing to an improved reuse of knowledge. These shortcomings are related. Data documentation and annotation are complicated and of little use whenever the metadata that make knowledge reusable are not prioritized. Addressing this gap, we discuss metadata standardization efforts targeted at documenting the knowledge status of data; we refer to such an annotation as epistemic metadata. We propose a schema for epistemic metadata, with a focus on knowledge and reproducibility claims, that is designed to be user-friendly and flexible enough to apply to a spectrum of circumstances and validity assessments. These developments are implemented as part of the PIMS-II ontology. They were conducted in line with requirements procured through a case study on papers and claims from molecular modelling and simulation.

Publisher

IOS Press

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