Articles | Volume 9, issue 1
https://doi.org/10.5194/soil-9-155-2023
https://doi.org/10.5194/soil-9-155-2023
Original research article
 | 
14 Mar 2023
Original research article |  | 14 Mar 2023

Potential of natural language processing for metadata extraction from environmental scientific publications

Guillaume Blanchy, Lukas Albrecht, John Koestel, and Sarah Garré

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Revised manuscript not accepted
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Cited articles

Angeli, G., Johnson Premkumar, M. J., and Manning, C. D.: Leveraging Linguistic Structure For Open Domain Information Extraction, in: Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Beijing, China, 344–354, https://doi.org/10.3115/v1/P15-1034, 2015. 
EJP SOIL – CLIMASOMA: CLIMASOMA – Final report Climate change adaptation through soil and crop management: Synthesis and ways forward, https://climasoma.curve.space/report (last access: 1 March 2023), 2022. 
Furey, J., Davis, A., and Seiter-Moser, J.: Natural language indexing for pedoinformatics, Geoderma, 334, 49–54, https://doi.org/10.1016/j.geoderma.2018.07.050, 2019. 
Haddaway, N. R., Callaghan, M. W., Collins, A. M., Lamb, W. F., Minx, J. C., Thomas, J., and John, D.: On the use of computer-assistance to facilitate systematic mapping, Campbell Systematic Reviews, 16, e1129, https://doi.org/10.1002/cl2.1129, 2020. 
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Short summary
Adapting agricultural practices to future climatic conditions requires us to synthesize the effects of management practices on soil properties with respect to local soil and climate. We showcase different automated text-processing methods to identify topics, extract metadata for building a database and summarize findings from publication abstracts. While human intervention remains essential, these methods show great potential to support evidence synthesis from large numbers of publications.