The Data Density Module, part of the Data Augmentation suite, creates a continuous raster surface that shows how much geoscientific data exists across the Area of Interest (AOI). It stacks multiple input datasets, such as geochemistry, drillhole traces, and geophysical data, then aggregates them spatially to highlight where data is concentrated and where coverage is limited.

This transformation helps highlight areas with strong data coverage versus zones that remain under-explored. In mineral exploration, this supports both planning and modelling by quantifying where information exists and where it does not. The output helps guide follow-up work, assess exploration maturity, and inform the quality of downstream predictions in DORA.

Data Density can be used within DORA or independently to support interpretation, planning, and targeting decisions. Within DORA, it is commonly used to evaluate which areas have enough data to support predictive modelling. It also serves as a reference layer when reviewing model outputs, helping geologists assess whether predicted targets are backed by sufficient information.

Outside of DORA, the output acts as a general-purpose layer that reveals spatial gaps in observation data. It supports planning by showing where new mapping or sampling should be focused. It also helps highlight areas where interpretation may be uncertain due to limited inputs, making it easier to communicate the need for further data collection to stakeholders.

Because the Module applies the same method across all input data, it provides a consistent and unbiased view of data coverage. This allows exploration teams to compare different parts of a project and make informed decisions about where to allocate time and resources. For example, a zone with strong structural or geochemical indicators but low data density might be prioritized for follow-up work.

In areas with uneven historical coverage or limited surface exposure, Data Density helps quantify uncertainty in interpretation. This turns a common challenge into a measurable layer that can guide both near-term exploration efforts and longer-term investment planning.

Data Density provides a clear picture of where data exists, helping teams avoid false confidence in areas with low information and highlighting zones that may have been overlooked. In structurally complex or poorly exposed terrains, this context is essential for planning and prioritization.

The Module supports better decision-making by turning observation presence into a continuous surface. It also helps evaluate the inputs going into DORA, ensuring that predictions are grounded in areas with sufficient support.

Additionally, as the Module accepts any spatially located data, it is flexible across exploration stages and data types. Whether using drillhole collars, geochemical points, or mapped structures, the output helps geologists assess the spatial extents of their dataset and fill in the gaps. This makes the Module valuable for both early-stage reconnaissance and evaluating prospectivity results within DORA.

Reach out to your dedicated DORA contact or email support@VRIFY.com for more information.