A data integration framework of additive manufacturing based on FAIR principles
-
Published:2024-05-28
Issue:10
Volume:9
Page:844-851
-
ISSN:2059-8521
-
Container-title:MRS Advances
-
language:en
-
Short-container-title:MRS Advances
Author:
Hernandez Kristen J.ORCID, Barcelos Erika I.ORCID, Jimenez Jayvic C.ORCID, Nihar ArafathORCID, Tripathi Pawan K.ORCID, Giera BrianORCID, French Roger H.ORCID, Bruckman Laura S.ORCID
Abstract
Abstract
Laser-powder bed fusion (L-PBF) is a popular additive manufacturing (AM) process with rich data sets coming from both in situ and ex situ sources. Data derived from multiple measurement modalities in an AM process capture unique features but often have different encoding methods; the challenge of data registration is not directly intuitive. In this work, we address the challenge of data registration between multiple modalities. Large data spaces must be organized in a machine-compatible method to maximize scientific output. FAIR (findable, accessible, interoperable, and reusable) principles are required to overcome challenges associated with data at various scales. FAIRified data enables a standardized format allowing for opportunities to generate automated extraction methods and scalability. We establish a framework that captures and integrates data from a L-PBF study such as radiography and high-speed camera video, linking these data sets cohesively allowing for future exploration.
Graphical abstract
Funder
Department of Energy’s National Nuclear Security Administration
Publisher
Springer Science and Business Media LLC
Reference30 articles.
1. T. Hey, S. Tansley, K. Tolle, The fourth paradigm: data-intensive scientific discovery. Microsoft Corporation, Redmond Washington (2009). https://www.microsoft.com/en-us/research/publication/fourth-paradigm-data-intensive-scientific-discovery/, ISBN 9780982544204 2. R.M. Chang, R.J. Kauffman, Y. Kwon, Understanding the paradigm shift to computational social science in the presence of big data. Decis. Supp. Syst. 63, 67–80 (2014). https://doi.org/10.1016/j.dss.2013.08.008 3. M.D. Wilkinson, M. Dumontier, I.J. Aalbersberg,G. Appleton, M. Axton, A. Baak, N. Blomberg, J.-W. Boiten, L.B. da Silva Santos, P.E. Bourne,J. Bouwman, A.J. Brookes, T. Clark, M. Crosas, I. Dillo, O. Dumon, S. Edmunds, C.T. Evelo,R. Finkers, A. Gonzalez-Beltran, A.J.G. Gray, P. Groth, C. Goble, J.S. Grethe, J. Heringa, P.A.C. ’tHoen, R. Hooft, T. Kuhn, R. Kok, J. Kok, S.J. Lusher, M.E. Martone, A. Mons, A.L. Packer,B. Persson, P. Rocca-Serra, M. Roos, R. van Schaik, S.-A. Sansone, E. Schultes, T. Sengstag, T. Slater,G. Strawn, M.A. Swertz, M. Thompson, J. van der Lei, E. van Mulligen, J. Velterop,A. Waagmeester, P. Wittenburg, K. Wolstencroft, J. Zhao, B. Mons, The FAIR Guiding Principlesfor scientific data management and stewardship. Scientific Data 3(1), 1–9 (2016). https://doi.org/10.1038/sdata.2016.18. Accessed 29 Dec 2021 4. P. Rocca-Serra, W. Gu, V. Ioannidis, T. Abbassi-Daloii, S. Capella-Gutierrez, I. Chandramouliswaran, A. Splendiani, T. Burdett, R.T. Giessmann, D. Henderson, D. Batista, I. Emam, Y. Gadiya, L. Giovanni, E. Willighagen, C. Evelo, A.J.G. Gray, P. Gribbon, N. Juty, D. Welter, K. Quast, P. Peeters, T. Plasterer, C. Wood, E. van der Horst, D. Reilly, H. van Vlijmen, S. Scollen, A. Lister, M. Thurston, R. Granell, S.-A. Sansone, The FAIR cookbook-the essential resource for and by FAIR doers. Sci. Data 10(1), 292 (2023). https://doi.org/10.1038/s41597-023-02166-3 5. D. Welter, N. Juty, P. Rocca-Serra, F. Xu, D. Henderson, W. Gu, J. Strubel, R.T. Giessmann, I. Emam, Y. Gadiya, T. Abbassi-Daloii, E. Alharbi, A.J.G. Gray, M. Courtot, P. Gribbon, V. Ioannidis, D.S. Reilly, N. Lynch, J.-W. Boiten, V. Satagopam, C. Goble, S.-A. Sansone, T. Burdett, FAIR in action-a flexible framework to guide FAIRification. Sci. Data 10(1), 291 (2023). https://doi.org/10.1038/s41597-023-02167-2
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
|
|