Towards improved software visualisation of parameterised REE patterns: Introducing REEkit for geological analysis

TL;DR

The paper addresses the challenge of visualising and comparing REE patterns generated by the lambda method, which offers $\lambda_0$, $\lambda_1$, $\lambda_2$, and $\lambda_3$ as a compact description of patterns. It introduces REEkit, a browser-based platform that evaluates six visualization techniques (spider diagrams, scatter plots, 3D scatter plots, scatter plot matrices, density contours, and violin plots) in the lambda context, using contextual inquiry with 10 participants. Key findings show that familiarity and clarity drive effective lambda data visualization, with 2D scatter-based visuals and certain combinations (e.g., 3D scatter plus density contour, scatter plot matrix plus density/violin) offering the most insight, while 3D visuals can overwhelm users. The work demonstrates REEkit’s potential to streamline REE data analysis and stakeholder communication, guiding its iterative development toward industry relevance and broader adoption in mineral exploration.

Abstract

Modern geological studies and mineral exploration techniques rely heavily on being able to digitally visualise and interpret data. Rare earth elements (REEs) are vital for renewable energy technologies. REE concentrations, when normalised to a standard material, show unique geometric curves (or patterns) in geological samples due to their similar chemical properties. The lambda technique can be used to describe these patterns and turn them into points - making it easier to visualise and interpret larger datasets. Lambdas have the potential to help industry understand intricate sample relationships and the geological and economic importance of their data. This study explored the use of lambdas through the evaluation of various visualisation methods to determine their usefulness in mineral exploration. The 'REEkit' platform facilitated the evaluation of the different visualisation methods and gauged industry interest and acceptance of such a service. Qualitative data was gathered through contextual inquiry, utilising semi-structured interviews and an observational session with 10 participants. Conceptual thematic analysis was applied to extract key findings. This study found that two critical factors for successful lambda data visualisation in the mineral exploration industry are familiarity and clarity: visualisations that were familiar and commonplace for users allowed for better analysis and clear communication to non-technical audiences. This included visualisations such as the 3D scatter plot and scatter plot matrix. Furthermore, visualisations that complemented each other and seamlessly integrated into the same workflow provided diverse perspectives on the data. Important aspects included understanding population grouping versus data distribution, achieved through combinations such as scatter plot and density contour plot, or 3D scatter plot and violin plot.

Figures (21)

• Figure 1: Figure 1: A spider diagram depicting a series of rare earth element patterns. Elements are represented on the x-axis by atomic radius in picometers, while the sample’s normalised concentration is plotted on the y-axis.
• Figure 2: Figure 2: Three unique rare earth element patterns (a, b, and c) shown with corresponding lambda values ($\lambda$) and elemental ratios. Elements are represented on the x-axis by atomic radius in picometers, while sample concentration is plotted on the y-axis. Image source: (Anenburg, 2020).
• Figure 3: Figure 3: Promotional material published on LinkedIn by MineDeck highlighting the best drilling results for the first quarter of 2023. These companies are ranked based on the TREO percentage (seen at the end of each row, surrounded by the black box) of their intercepts (MinerDeck, 2023).
• Figure 4: Figure 4: A spider diagram depicting a rare earth element pattern. Elements are represented on the x-axis by atomic radius in picometers, while samples concentration is plotted on the y-axis. Note the ‘zig zag’ nature of the pattern.
• Figure 5: Figure 5: An example of a ratio diagram used to describe REE data from a series of rocks taken from Wongwibinda, NSW (Farmer, 2017).