LLNL-SCDC (LLNL Surface Complexation Database Converter)
SCDC is a R-based script that creates a unified dataset of surface complexation experimental data with respective parameters and results
The Lawrence Livermore National Laboratory Surface Complexation Database Converter (SCDC) is a R-based script that creates a unified dataset of surface complexation experimental data with respective parameters and results. To provide context, it is commonly understood in the data science community that gathering and cleansing data can take up to 80% of the time in analytics - with the remaining 20% being the actual analysis. This script turns the 80% process of data cleansing into a more seemless, time efficient process. The LLNL SCDC consists of three process tabs: (1) Unifier, which reads a Dataset/Data .csv and a mineral reference Excel file in order to create a collective dataset, (2) Filterer, which reads in the output from the Unifier to filter for specific mineral-sorbent pairs, and (3) Formatter, which reads the output from the Filterer to prepare the dataset for future data manipulation and processing. The server.R, ui.R scripts, and all necessary Excel/.csv files for running the SCDC are presented in this public release to allow for scientists to more easily compile experimental data on metal-mineral surface interactions.
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swap_vertical_circlelibrary_booksReferences (1)
- Zavarin, M.; Chang, E.; Wainwright, H.; Parham, N.; Kaukuntla, R.; Zouabe, J.; Deinhart, A.; Genetti, V.; Shipman, S.; Bok, F.; Brendler, V. (February 1, 2022), Community Data Mining Approach for Surface Complexation Database Development, Environmental Science & Technology, 56(4), 2827-2838
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swap_vertical_circlecloud_downloadSupporting documents (1)Product brochureLLNL-SCDC (LLNL Surface Complexation Database Converter).pdfAdditional files may be available once you've completed the transaction for this product. If you've already done so, please log into your account and visit My account / Downloads section to view them.