Tools for Aggregating, Analyzing and Mining Combinatorial Data: Paper No. 1159-G03-08

Wesley B. Jones; Changwon Suh; Peter A. Graf; Daniel Korytina; Craig Swank; Christopher Perkins

doi:10.1557/PROC-1159-G03-08

Tools for Aggregating, Analyzing and Mining Combinatorial Data: Paper No. 1159-G03-08

Wesley B. Jones, Changwon Suh, Peter A. Graf, Daniel Korytina, Craig Swank, Christopher Perkins

Computational Science

Research output: Contribution to conference › Paper › peer-review

Abstract

We demonstrate how data mining techniques can be applied to complex combinatorial data sets and how data from multiple sources can be aggregated via the developed scientific data management system. An example is shown for the case of aggregated combinatorial data for the study of composition, processing, structure, and property relationships of transparent conducting oxides by applying data mining techniques such as principal component analysis. Data mappings of mined results are shown to effectively enable visualization of data trends, identification of anomalies in Fourier transform infrared spectroscopy patterns, and scientifically interesting libraries and spectral regions.

Original language	American English
Pages	7-12
Number of pages	6
DOIs	https://doi.org/10.1557/PROC-1159-G03-08 https://doi.org/10.1557/proc-1159-g03-08
State	Published - 2009
Event	2009 MRS Spring Meeting - San Francisco, CA, United States Duration: 13 Apr 2009 → 17 Apr 2009

Conference

Conference	2009 MRS Spring Meeting
Country/Territory	United States
City	San Francisco, CA
Period	13/04/09 → 17/04/09

NREL Publication Number

NREL/CP-530-45600

Keywords

combinatorial synthesis
oxide
transparent conductor

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abstract = "We demonstrate how data mining techniques can be applied to complex combinatorial data sets and how data from multiple sources can be aggregated via the developed scientific data management system. An example is shown for the case of aggregated combinatorial data for the study of composition, processing, structure, and property relationships of transparent conducting oxides by applying data mining techniques such as principal component analysis. Data mappings of mined results are shown to effectively enable visualization of data trends, identification of anomalies in Fourier transform infrared spectroscopy patterns, and scientifically interesting libraries and spectral regions.",

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AU - Suh, Changwon

AU - Graf, Peter A.

AU - Korytina, Daniel

AU - Swank, Craig

AU - Perkins, Christopher

PY - 2009

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AB - We demonstrate how data mining techniques can be applied to complex combinatorial data sets and how data from multiple sources can be aggregated via the developed scientific data management system. An example is shown for the case of aggregated combinatorial data for the study of composition, processing, structure, and property relationships of transparent conducting oxides by applying data mining techniques such as principal component analysis. Data mappings of mined results are shown to effectively enable visualization of data trends, identification of anomalies in Fourier transform infrared spectroscopy patterns, and scientifically interesting libraries and spectral regions.

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KW - oxide

KW - transparent conductor

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ER -

Tools for Aggregating, Analyzing and Mining Combinatorial Data: Paper No. 1159-G03-08

Abstract

Conference

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Keywords

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