FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

Oltjen, William C.; Fan, Yangxin; Liu, Jiqi; Huang, Liangyi; Yu, Xuanji; Li, Mengjie; Seigneur, Hubert; Xiao, Xusheng; Davis, Kristopher O.; Bruckman, Laura S.; Wu, Yinghui; French, Roger H.

doi:10.1109/pvsc48317.2022.9938523

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Cited by 3 publications

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Missing Data Imputation for Photovoltaic Station Based on Spatiotemporal Features

Zhou,

Gao,

Zhang

et al. 2024

2024 CPSS &Amp;amp; IEEE International Symposium on Energy Storage and Conversion (ISESC)

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Missing Data Imputation for Photovoltaic Station Based on Spatiotemporal Features

Zhou,

Gao,

Zhang

et al. 2024

2024 CPSS &Amp;amp; IEEE International Symposium on Energy Storage and Conversion (ISESC)

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Data-Driven Photovoltaic Module Performance Analysis with FAIR Data

Li,

Kaltenbaugh,

Colvin

et al. 2023

2023 IEEE 50th Photovoltaic Specialists Conference (PVSC)

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A data integration framework of additive manufacturing based on FAIR principles

Hernandez,

Barcelos,

Jimenez

et al. 2024

MRS Advances

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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

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FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

Cited by 3 publications

References 8 publications

Missing Data Imputation for Photovoltaic Station Based on Spatiotemporal Features

Missing Data Imputation for Photovoltaic Station Based on Spatiotemporal Features

Data-Driven Photovoltaic Module Performance Analysis with FAIR Data

A data integration framework of additive manufacturing based on FAIR principles

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