Articles | Volume 9, issue 1
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


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-535', Anonymous Referee #1, 10 Aug 2022
    • AC1: 'Reply on RC1', Guillaume Blanchy, 12 Jan 2023
  • RC2: 'Comment on egusphere-2022-535', Anonymous Referee #2, 28 Nov 2022
    • AC2: 'Reply on RC2', Guillaume Blanchy, 12 Jan 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Publish subject to minor revisions (review by editor) (13 Jan 2023) by Olivier Evrard
AR by Guillaume Blanchy on behalf of the Authors (27 Jan 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (27 Jan 2023) by Olivier Evrard
ED: Publish as is (03 Feb 2023) by Kristof Van Oost (Executive editor)
AR by Guillaume Blanchy on behalf of the Authors (13 Feb 2023)  Manuscript 
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.