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. 2019 Dec 5;6:307. doi: 10.1038/s41597-019-0306-0

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — The workflow associated with different stages of data processing. Stage I (top row): ChemDataExtractor extracts chemical information from the academic journal. Stage II (middle row): Unique chemical entries from the MongoDB server are passed through a fast-screening layer. Stage III (bottom row): Best candidates are identified and TD-DFT calculations are performed for those select cases. All of the stages utilize a secure MongoDB server for database management. Numbers enclosed in rectangular boxes indicate the number of data samples entering or leaving a stage.