International Trends in Mining Tailings Research through Machine Learning Method: Retrospective or Prospective Oriented Research?

• Published in: Mineral processing and extractive metallurgy review 2023-01, Vol.44 (1), p.64-75
• Main Authors: Campos-Medina, Fernando, Ojeda-Pereira, Iván, Quiroz, Joaquín, Guzmán, Joao
• Format: Article
• Language: English
• Subjects: engineering; environmental and earth sciences; Machine learning; Mine tailings; Mine wastes; mining tailings; Natural language processing; prospective/retrospective research; social sciences; Tailings
• ISSN: 0882-7508; 1547-7401
• DOI: 10.1080/08827508.2021.2023520

Using a conceptual distinction between prospective and retrospective research, we analyze the international high-impact literature on tailings. This distinction differentiates between investigations concentrated on specific case studies, where the socio-environmental consequences of tailings are addressed or specific actions on them are documented, and the investigations that model interventions on tailings, propose new forms of design, management and remediation applicable to tailings. Using Natural Language Processing (NLP) tools, we covered all the publications registered in the Scopus database between 2010 and 2020 on mining tailings. Our research question ask for the temporal orientations in the international publication on mining tailings deposits between 2010 and 2020? Our results show an increase in the number of prospective investigations, which practically double the retrospective ones. However, at the level of citations, this difference is reduced and the most cited investigations in the retrospective perspective outnumber the most cited ones in the prospective perspective. We conclude by discussing the need to address the impact of prospective research on mining companies and overcoming resistance to innovation in the industry when there are no regulatory or legal obligations. In the same way, we call for an increase in the public contribution to maintain the independence of retrospective research, without neglecting the necessary construction of updated evidence on the socio-environmental consequences of mining tailings.