In 2010, staff at Adolfo Ibáñez University, University of Chile, and Colorado School of Mines created a website called Minelib along with an associated published paper in the Annals of Operations Research.
The website contains a small number of open pit mine block models for mine planning optimisation research. The success of the library is illustrated by the fact that the paper has been cited over 60 times in peer-reviewed journals. This year it is hoped to expand the variety of datasets and projects for use by mining universities, both as a classroom tool and as a worldwide research resource.
As you know, one of the challenges of teaching both undergraduate and postgraduate students is the ability to find industry data. For example, the majority of mining universities in the US require a senior design or capstone course involving a student or team of students to complete a scoping or prefeasibility study. Similar projects are undertaken at Australian universities in the final years of Bachelor of Engineering studies. Each year, academic staff struggle to find realistic datasets and to obtain the necessary permissions to share the data with the students.
The same thing happens in research. It is very difficult currently for academics working in different institutions to compare and validate their methodologies and results without common data to work with. Moreover, a lot of research is done with artificial data sets, or very small portions of real data sets, raising legitimate questions concerning the validity of findings.
As such the search is on for data which can be used to expand the library of data within Minelib, maybe also including underground mining deposits. An idea of the data required includes:
- drill hole data and corresponding documentation describing the fields, rock types, etc
- block models and corresponding documentation
- topography data
- design parameters, ie processing type, recovery rates, environmental conditions, reclamation requirements, etc.
It is understood that this type of data is sensitive especially for currently mined deposits or deposits with potential to be mined. Strategic information pertaining to costs, location, dates, or others, can be disguised or modified to protect participants. However perhaps a better way forward would be data originating from mined out or inactive deposits; this can be just as valuable and yet may be easier for some companies to share.
As such it is being requested that mining companies consider this request for data and provide it where possible to be included within the Minelib library of deposits. For further details of the project contact Dr Andrea Brickey, Associate Professor at the South Dakota School of Mines, Andrea.Brickey@sdsmt.edu, or Dr Michael Tuck, Associate Professor of Mining Engineering at Federation University Australia, firstname.lastname@example.org.
The aim is to improve the education of students and to make their studies more industry relevant, leading to the development of better qualified industry relevant graduates.