Digital Transformation in Materials Science: A User Journey...

Abstract

A robust digital infrastructure, built upon overarching frameworks and software tools, is essential for the ongoing digital transformation in materials science and engineering. This user journey demonstrates the seamless integration of distinct technical solutions for data handling and analysis, enabling (a) the pursuit of a specific scientific question and (b) adherence to FAIR principles. The scientific study selected for this user journey focuses on comparing different measures of the elastic modulus of a typical engineering material. The user journey involves three research groups replicating real-world collaborative research scenarios. Specifically, it integrates existing digital solutions for experimental data management (PASTA-ELN), simulation workflow execution (pyiron), and image processing workflow execution (Chaldene). Within the auxiliary data management workflow, generated data and metadata are systematically stored in repositories, with metadata aligned to the MatWerk Ontology. Key insights from this user journey include lessons learned from scientists’ perspectives and recommendations for improvement, such as machine-readable experimental protocols, standardized workflow representation, and automated metadata extraction.

References

Apache CouchDB (2024) Apache CouchDB. Available at: https://couchdb.apache.org/ (Accessed: 29 May 2024).
Search in Google Scholar Back to article
Baker, M. (2016) ‘1,500 scientists lift the lid on reproducibility’, Nature, 533, pp. 452–454. Available at: 10.1038/533452a
Open DOI Search in Google Scholar Back to article
Barker, M., Chue Hong, N., Katz, D., Lamprecht, A.L., Martinez-Ortiz, C., Psomopoulos, F., Harrow, J. et al. (2022) ‘Introducing the FAIR Principles for research software’, Scientific Data, 9, p. 622. Available at: 10.1038/s41597-022-01710-x
Open DOI Search in Google Scholar Back to article
Celebi, R., Moreira, J., Hassan, A., Ayyar, S., Ridder, L., Kuhn, T. and Dumontier, M. (2020) ‘Towards FAIR protocols and workflows: the OpenPREDICT use case’, PeerJ Computer Science, 6, p. e281. Available at: 10.7717/peerj-cs.281
Open DOI Search in Google Scholar Back to article
Chen, F., Slusallek, P., Müller, M. and Dahmen, T. (2022) ‘Chaldene: Towards Visual Programming Image Processing in Jupyter Notebooks’, 2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). IEEE, pp. 1–3. Available at: 10.1109/VL/HCC53370.2022.9832910
Open DOI Search in Google Scholar Back to article
Chue Hong, N., Katz, D., Barker, M., Lamprecht, A.L., Martinez, C., Psomopoulos, F., Harrow, J. et al. (2022) ‘FAIR Principles for Research Software (FAIR4RS Principles)’.
Search in Google Scholar Back to article
Coscine (2024) Coscine. Available at: https://about.coscine.de/en/ (Accessed: 29 May 2024).
Search in Google Scholar Back to article
DataCite Metadata Working Group (2016) DataCite Metadata Schema Documentation for the Publication and Citation of Research Data v4.0. Tech. rep., DataCite e.V.
Search in Google Scholar Back to article
de Visser, C., Johansson, L., Kulkarni, P., Mei, H., Neerincx, P., van der Velde, J., Horvatovich, P. et al. (2023) ‘Ten quick tips for building FAIR workflows’, PLoS Computational Biology, 19, p. e1011369. Available at: 10.1371/journal.pcbi.1011369
Open DOI Search in Google Scholar Back to article
DeCost, B., Hattrick-Simpers, J., Trautt, Z., Kusne, A., Campo, E. and Green, M. (2020) ‘Scientific AI in Materials Science: a Path to a Sustainable and Scalable Paradigm’, Machine Learning: Science and Technology, 1. Available at: 10.1088/2632-2153/ab9a20
Open DOI Search in Google Scholar Back to article
Deutsche Forschungsgemeinschaft (2022) Guidelines for Safeguarding Good Research Practice. Code of Conduct. Deutsche Forschungsgemeinschaft
Search in Google Scholar Back to article
German Research Foundation (2022) Leitlinien zur Sicherung guter wissenschaftlicher Praxis. Available at: 10.5281/zenodo.3923601
Open DOI Search in Google Scholar Back to article
GitLab (2024) GitLab. Available at: https://about.gitlab.com/ (Accessed: 29 May 2024).
Search in Google Scholar Back to article
Go-FAIR (2024) Go-FAIR Initiative. Available at: https://www.go-fair.org/ (Accessed: 29 May 2024).
Search in Google Scholar Back to article
Goble, C., Cohen-Boulakia, S., Soiland-Reyes, S., Garijo, D., Gil, Y., Crusoe, M., Peters, K. et al. (2020) ‘FAIR Computational Workflows’, Data Intelligence, 2, pp. 108–121. Available at: 10.1162/dint_a_00033
Open DOI Search in Google Scholar Back to article
Higgins, S., Nogiwa-Valdez, A. and Stevens, M. (2022) ‘Considerations for implementing electronic laboratory notebooks in an academic research environment’, Nature Protocols, 17, pp. 179–189. Available at: 10.1038/s41596-021-00645-8
Open DOI Search in Google Scholar Back to article
Himanen, L., Geurts, A., Foster, A. and Rinke, P. (2019) ‘Data-driven materials science: status, challenges and perspectives’, Advanced Science, 6, p. 42. Available at: 10.1002/advs.201900808
Open DOI Search in Google Scholar Back to article
Janssen, J., Surendralal, S., Lysogorskiy, Y., Todorova, M., Hickel, T., Drautz, R. and Neugebauer, J. (2019) ‘pyiron: An integrated development environment for computational materials science’, Computational Materials Science, 163, pp. 24–36. Available at: 10.1016/j.commatsci.2018.07.043
Open DOI Search in Google Scholar Back to article
Jelinek, B., Groh, S., Horstemeyer, M., Houze, J., Kim, S., Wagner, G., Moitra, A. et al. (2012) ‘Modified embedded atom method potential for Al, Si, Mg, Cu, and Fe alloys’, Physical Review B, 85. Available at: 10.1103/PhysRevB.85.245102
Open DOI Search in Google Scholar Back to article
Kanza, S., Willoughby, C., Gibbins, N., Whitby, R., Frey, J., Erjavec, J., Zupančič, K. et al. (2017) ‘Electronic lab notebooks: can they replace paper?’, Journal of Cheminformatics, 9, p. 31. Available at: 10.1186/s13321-017-0221-3
Open DOI Search in Google Scholar Back to article
MatPortal: the ontology repository for materials science (2024) MatPortal: the ontology repository for materials science. Available at: https://matportal.org/ (Accessed: 03 October 2024).
Search in Google Scholar Back to article
MatWerk Ontology templates (2024) MatWerk Ontology templates. Available at: https://git.rwth-aachen.de/nfdi-matwerk/ta-oms/mste (Accessed: 03 October 2024).
Search in Google Scholar Back to article
MSE Knowledge Graph (2024) MSE Knowledge Graph. Available at: https://demo.fiz-karlsruhe.de/matwerk/ (Accessed: 29 May 2024).
Search in Google Scholar Back to article
Nečas, D. and Klapetek, P. (2012) ‘Gwyddion: an open-source software for SPM data analysis’, Open Physics, 10, pp. 181–188. Available at: 10.2478/s11534-011-0096-2
Open DOI Search in Google Scholar Back to article
Nicolae, B., Islam, T., Ross, R., van Dam, H., Assogba, K., Shpilker, P., Titov, M. et al. (2023) ‘Building the I (Interoperability) of FAIR for Performance Reproducibility of Large-Scale Composable Workflows in RECUP’, 2023 IEEE 19th International Conference on e-Science (e-Science). IEEE, pp. 1–7. Available at: 10.1109/e-Science58273.2023.10254808
Open DOI Search in Google Scholar Back to article
Oliver, W. and Pharr, G. (1992) ‘An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments’, Journal of Materials Research, 7, pp. 1564–1583. Available at: 10.1557/JMR.1992.1564
Open DOI Search in Google Scholar Back to article
Oliver, W. and Pharr, G. (2004) ‘Measurement of hardness and elastic modulus by instrumented indentation: Advances in understanding and refinements to methodology’, Journal of Materials Research, 19, pp. 3–20. Available at: 10.1557/jmr.2004.19.1.3
Open DOI Search in Google Scholar Back to article
PASTA-ELN (2024) PASTA-ELN. Available at: https://github.com/PASTA-ELN/pasta-eln (Accessed: 29 May 2024).
Search in Google Scholar Back to article
pyiron (2024) pyiron. Available at: https://github.com/pyiron (Accessed: 29 May 2024).
Search in Google Scholar Back to article
Rodrigues, J., Florea, L., de Oliveira, M., Diamond, D. and Oliveira, O. (2021) ‘Big data and machine learning for materials science’, Discover Materials, 1, p. 12. Available at: 10.1007/s43939-021-00012-0
Open DOI Search in Google Scholar Back to article
Scheffler, M., Aeschlimann, M., Albrecht, M., Bereau, T., Bungartz, H.J., Felser, C., Greiner, M. et al. (2022) ‘FAIR data enabling new horizons for materials research’, Nature, 604, pp. 635–642. Available at: 10.1038/s41586-022-04501-x
Open DOI Search in Google Scholar Back to article
Schema.org (2024) Schema.org. Available at: https://schema.org/ (Accessed: 03 October 2024).
Search in Google Scholar Back to article
Sefton, P., Carragáin, E.Ó., Soiland-Reyes, S., Corcho, O., Garijo, D., Palma, R., Coppens, F. et al. (2023) RO-Crate Metadata Specification 1.1.3, Zenodo.
Search in Google Scholar Back to article
Soiland-Reyes, S., Sefton, P., Crosas, M., Castro, L., Coppens, F., Fernández, J., Garijo, D. et al. (2022) ‘Packaging research artefacts with RO-Crate’, DS, 5, pp. 97–138. Available at: 10.3233/DS-210053
Open DOI Search in Google Scholar Back to article
Stickdorn, M. and Schneider, J. (2012) This is Service Design Thinking: Basics, Tools, Cases. Wiley.
Search in Google Scholar Back to article
The MatWerk Ontology (MWO) (2024) The MatWerk Ontology (MWO). Available at: http://purls.helmholtz-metadaten.de/mwo (Accessed: 29 May 2024).
Search in Google Scholar Back to article
Tsybenko, H., Menon, S., Chen, F., Guzman, A., Grünwald, K., Brinckmann, S., Hickel, T. et al. (2023a) Project Data: Elastic properties of EN AW-1050A alloy: a scientific user journey built upon NFDI-MatWerk infrastructure solutions. Available at: http://hdl.handle.net/21.11102/4781e163-229d-4a2a-91c2-75e107c21730 (Accessed: 29 May 2024).
Search in Google Scholar Back to article
Tsybenko, H., Menon, S., Chen, F., Guzman, A., Grünwald, K., Brinckmann, S., Hickel, T. et al. (2023b) Project Data: Elastic properties of EN AW-1050A alloy: a scientific user journey built upon NFDI-MatWerk infrastructure solutions. Available at: https://git.rwth-aachen.de/nfdi-matwerk/ta-wsd1/user-journey-indentation (Accessed: 17 October 2024).
Search in Google Scholar Back to article
van der Walt, S., Schönberger, J., Nunez-Iglesias, J., Boulogne, F., Warner, J., Yager, N., Gouillart, E. et al. (2014) ‘scikit-image: image processing in Python’, PeerJ, 2, p. e453. Available at: 10.7717/peerj.453
Open DOI Search in Google Scholar Back to article
Wilkinson, M., Dumontier, M., Aalbersberg, I., Appleton, G., Axton, M., Baak, A., Blomberg, N. et al. (2016) ‘The FAIR Guiding Principles for scientific data management and stewardship’, Scientific Data, 3, p. 160018. Available at: 10.1038/sdata.2016.18
Open DOI Search in Google Scholar Back to article
Wilkinson, S.R., Eisenhauer, G., Kapadia, A., Knight, K., Logan, J., Widener, P. and Wolf, M. (2022) ‘F*** workflows: when parts of FAIR are missing’, in 2022 IEEE 18th International Conference on e-Science (e-Science), Salt Lake City, UT, USA, pp. 507–512. Available at: 10.1109/eScience55777.2022.00090
Open DOI Search in Google Scholar Back to article

Digital Transformation in Materials Science: A User Journey of Nanoindentation, Image Analysis and Simulations

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