Authors: Laine, J; Ortega, F; Luiña, R; Alvarez-Cabal, V

Paper is not available for download
Contact Us

DOI https://doi.org/10.36487/ACG_rep/1504_13_Laine

Cite As:
Laine, J, Ortega, F, Luiña, R & Alvarez-Cabal, V 2015, 'Research trends on thickening mining wastes', in R Jewell & AB Fourie (eds), Paste 2015: Proceedings of the 18th International Seminar on Paste and Thickened Tailings, Australian Centre for Geomechanics, Perth, pp. 195-208, https://doi.org/10.36487/ACG_rep/1504_13_Laine

Download citation as:   ris   bibtex   endnote   text   Zotero


Abstract:
The mining industry is a main generator of wastes. In many cases, those wastes are liquid because the mining process requires wet processes. This aspect is inherent to the industry and it is not completely avoidable. Anyway, during the last three decades this problem has been arisen as a main concern as the environmental conscience grows and the legal requirements become stricter. The effort in the reduction and optimisation of waste disposal techniques is guided by basic and applied research efforts that have been growing during this period. This paper presents a review of the published contributions related to thickening mining wastes in order to detect the evolution of research and engineering practice in the field with the objective to detect the main concerns in the fields, its evolution over time, as well as the relationships between them. It provides very relevant information about how the techniques evolve and specially how to detect the current and next futures trends for research and engineering application. Study is done through the scientometric (bibliometrical) analysis on published articles available from ISI web of Science database between 1900 and 2014. Data is treated with VOSviewer and TxtViz using text and data mining techniques. In order to produce effective searches, a previous identification of the main definitions present in the texts related to the field has been done, from initial knowledge but also created automatically through the scan of the selected papers, identifying patterns in the waste thickening literature. The final concepts, composed of up to three words, constituted the essential dictionary and are combined in the first ontology in this field. Results show clear tendencies in the field by the existence of some key concepts (e.g. flocculation, backfill, disposal) capable to create clusters around them.

References:
Adhau, SP, Moharil, RM & Adhau, PG 2014, ‘K-Means clustering technique applied to availability of micro hydro power’, Sustainable Energy Technologies and Assessments, vol. 8, pp. 191-201.
Bailón-Moreno, R, Jurado-Alameda, E & Ruiz-Baños, R 2006, ‘The scientific network of surfactants: structural analysis’, Journal of the American Society for Information Science and Technology, vol. 57, no. 7, pp. 949-960.
Börner, K, Chen, C & Boyack, KW 2003, ‘Visualizing knowledge domains’, Annual review of Information Science and Technology, vol. 37, no. 1, pp. 179-255.
Callon, M, Courtial, JP & Laville, F 1991, ‘Co-word analysis as a tool for describing the network of interactions between basic and technological research: the case of polymer chemistry’, Scientometrics, vol. 22, no. 1, pp. 155-205.
Callon, M, Courtial, JP, Turner, WA & Bauin, S 1983, ‘From translations to problematic networks: an introduction to co-word analysis’, Social Science Information, vol. 22, pp. 191-235.
Chen, C, Ibekwe-SanJuan, F & Hou, J 2010, ‘The structure and dynamics of co-citation clusters: a multiple-perspective co-citation analysis’, Journal of the American Society for Information Science and Technology, vol. 61, no. 7, pp. 1386-1409.
Cobo, MJ, López-Herrera, AG, Herrera-Viedma, E & Herrera, F 2011, ‘An approach for detecting, quantifying, and visualizing the evolution of a research field: a practical application to the Fuzzy Sets Theory field’, Journal of Informetrics, vol. 5, no. 1, pp. 146-166.
Costa, IG, Carvalho, F & Souto, M 2004, ‘Comparative analysis of clustering methods for gene expression time course data’, Genetics and Molecular Biology, vol. 27, no. 4, pp. 623-631.
Coulter, N, Monarch, I & Konda, S 1998, ‘Software engineering as seen through its research literature: a study in co-word analysis’, Journal of the American Society for Information Science, vol. 49, no. 13, pp. 1206-1223.
Courtial, JP 1994, ‘A coword analysis of scientometrics’, Scientometrics, vol. 31, no. 3, pp. 251-260.
De Looze, MA & Lemarié, J 1997, ‘Corpus relevance through co-word analysis: An application to plant proteins’, Scientometrics, vol. 39, no. 3, pp. 267-280.
Ding, Y, Chowdhury, GG & Foo, S 2001, ‘Bibliometric cartography of information retrieval research by using co-word analysis’, Information Processing & Management, vol. 37, no. 6, pp. 817-842.
Fourie, AB 2012, ‘Perceived and realized benefits of paste and thickened tailings for surface deposition’, in RJ Jewell, AB Fourie & A Patterson (eds), Proceedings of 15th International Seminar on Paste and Thickened Tailings, Australian Centre for Geomechanics, Sun city, South Africa, pp. 53-64.
Garfield, E 1979, Citation indexing: its theory and application in science, technology, and humanities, Isi Press, Philadelphia.
Hess, DJ 1997, Science studies: an advanced introduction, NYU Press, New York.
Hirsch, JE 2005, ‘An index to quantify an individual’s scientific research output’, Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 46, pp. 16569-16572.
Instem Scientific Limited, 2014, TxtVizTM Blog Archive, Instem Scientific Limited, Melbourn, viewed 26 October 2014, www.txtviz.com/category/blog
International Commission on Large Dams & United Nations Environmental Programme (UNEP & UNEP) 2001, Tailings dams – risk of dangerous occurrences, lessons learnt from practical experiences (Bulletin no. 121), ICOLD & UNEP, Paris.
Jewell, RJ & Fourie, AB 2006, Paste and Thickened Tailings - A Guide, 2nd edn, Australian Centre for Geomechanics, Perth.
Koonsanit, K, Jaruskulchai, C & Eiumnoh, A 2012, ‘Determination of the Initialization number of clusters in K-means clustering application using co-occurrence statistics techniques for multispectral satellite imagery’, International Journal of Information and Electronics Engineering, vol. 2, no. 5, pp. 785-789.
Lee, B, Jeong, Y-I 2008, ‘Mapping Korea’s national R&D domain of robot technology by using the co-word analysis’, Scientometrics, vol. 77, no. 1, pp. 3-19.
Leydesdorff, L & Rafols, I 2009, ‘A global map of science based on the ISI subject categories’, Journal of the American Society for Information Science and Technology, vol. 60, no. 2, pp. 348-362.
McCain, KW 1990, ‘Mapping authors in intellectual space: A technical overview’, Journal of the American Society for Information Science, vol. 41, no. 6, pp. 433-443.
Noyons, ECM, Moed, HF & Luwel, M 1999, ‘Combining mapping and citation analysis for evaluative bibliometric purposes: a bibliometric study’, Journal of the American Society for Information Science, vol. 50, no. 2, pp. 115-131.
Rikken, F, Kiers, HAL & Vos, R 1995, ‘Mapping the dynamics of adverse drug reactions in subsequent time periods using INDSCAL’, Scientometrics, vol. 33, no. 3, pp. 367-380.
Small, H, Boyack, KW & Klavans, R 2014, ‘Identifying emerging topics in science and technology’, Research Policy, vol. 43, no. 8, pp. 1450-1467.
Small, H & Upham, P 2009, ‘Citation structure of an emerging research area on the verge of application’, Scientometrics, vol. 79, no. 2, pp. 365-375.
Small, H 2006, ‘Tracking and predicting growth areas in science’, Scientometrics, vol. 68, no. 3, pp. 595-610.
Small, H, Sweeney, E & Greenlee, E 1985, ‘Clustering the science citation index using co-citations. II. Mapping science’, Scientometrics, vol. 8, no. 5-6, pp. 321-340.
Small, H 1973, ‘Co-citation in the scientific literature: a new measure of the relationship between two documents’, Journal of the American Society for Information Science, vol. 24, no. 4, pp. 265-269.
van Eck, NJ, Waltman, L 2007, ‘VOS: A new method for visualizing similarities between objects’, in R Decker & HJ Lenz (eds), Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V., Springer Berlin Heidelberg, Berlin, pp. 299-306.
Van Raan, J 2004, ‘Measuring science’, in HF Moed, W Glänzel 6 U Schmoch (eds), Handbook of Quantitative Science and Technology Research – The Use of Publication and Patent Statistics, Kluwer Academic Publishers, New York.
Waltman, L, van Eck, NJ & Noyons, ECM 2010, ‘A unified approach to mapping and clustering of bibliometric networks’, Journal of Informetrics, vol. 4, no. 4, pp. 629-635.




© Copyright 2024, Australian Centre for Geomechanics (ACG), The University of Western Australia. All rights reserved.
View copyright/legal information
Please direct any queries or error reports to repository-acg@uwa.edu.au