Our Software
Is a novel tool that combines both data and uncertainty in a unique and intuitive visual to convey the spatial quality of data (2D and 3D), thus communicating spatial data distribution in a holistic way and allowing decisions to be made with substantially greater confidence.
What We Do
The VGM uses varying grid cell sizes to visually communicate and constrain the uncertainty; smaller grids representing less uncertainty, and larger grids representing greater uncertainty.
The VGM is a user-driven tool. It gives the user flexibility in the selection of uncertainty criteria and grid resolution, which enables optimal visualization of relevant opportunities versus knowledge gaps.
“Bringing Uncertainty to the Forefront of Informed Decision Making”
Why Varigrid?
The first visual tool to communicate the data and its uncertainty in one combined visual.
Information on the quality of your data is underestimated across geospatial visualization tools. As the use of big data and data analytics continues to play an increasing role across virtually all industries, it is crucial that uncertainties are appropriately quantified and represented in final products used to support those decisions. This serves to reduce risks and improve the value of the information presented.
Data Collectors?
The VGM offers an efficient and effective tool for assessment of spatial data quality and provides an effective validation of the true value of spatial data on hand.
“The VGM provides simultaneous quantification and visualization of data and its uncertainty”
How It Works?
How do we communicate high vs. low confidence in areas of a spatial map, 2D or 3D?
VGM utilizes varying grid cells to visually communicate the quality of your data, highlighting opportunities vs. knowledge gaps.
- Smaller grids for lower uncertainty
- Larger grids for higher uncertainty
- Colours represent the variable of interest.
But what about UNCERTAINTY?
How do we communicate high versus low confidence in areas of a spatial map, 2D or 3D? For example:
Where original/true data points are densely clustered in some sections versus very few or none in others? or
Areas where data has been acquired with less precision and/or lower accuracy instruments? or
Areas where data was acquired years ago versus others where data was acquired more recently? or
That area where we have more confidence because data is complemented and/or validated by other data/knowledge?
This highlights a need to include information about uncertainty in spatial maps; to shed light on the quality and quantity of data used, to better inform decisions utilizing the data.
VGM over Interpolation
VGM over averaged data within each grid
Why VGM?
- Simultaneously visualize both spatial patterns and trends and the uncertainty associated with data.
- Objectively define and integrate uncertainty into business decisions.
VGM utilizes varying grid cell sizes to visually communicate and constrain uncertainty.
The VGM not only helps to point out knowledge gaps in data, but it also points to opportunities by highlighting sections where there is reduced risk i.e. areas with both high potentials with high confidence (low uncertainty).
Industry segments
- Generic: Optimize data acquisition by using the VGM to drive data acquisition programs to achieve an objective reduction in uncertainty.
- Oil & Gas: Enhance Oil, Gas and Mineral Resource Development by including uncertainty in decisions for placement of Wells & Mines.
Copyright 2023 © All rights Reserved.