b'CommentaryData trendsavailable programs are capable of handlingA concern is if dependencies change in the format. Many export, but few import.the background such as HDF5 functions Open source GDAL and QGIS openwere incompatible with HDF4 functions,ModelVision NetCDF grids but GDF2 is a vector andespecially since HDF supplies the will not load. ESRI ArcPro was able tocompression. NetCDF was not designed load the \x1ele as a table then convertedto be a database and write operationsMagnetic & Gravity into a point shape \x1ele (Figure 2). OriginProcan be slow, at least in Python. Interpretation System(https://www.originlab.com/) and MATLAB (https://www.mathworks.comN/) willNote the data is e\x1fectively the same size read data \x1eles in the NetCDF format. compressed within NetCDF or ZippedAll sensorsMinerals text, implying software that reads textProcessingPetroleum The recent Python training course by\x1eles inside zip \x1eles would result in the3D modellingNear Surface Nathaniel Butterworth converted manysame \x1ele size footprint for both data3D inversionGovernment grids from many \x1ele types into NetCDF toexchange solutions.standardise \x1ele input for machine learning. VisualisationContracting AnalysisConsulting UtilitiesEducation Tensor Research support@tensor-research.com.au Figure 2: Point shape \x1dle generated by ERSI ArcPro from raw magnetic survey data in NetCDFformat. www.tensor-research.com.au 36 PREVIEWAPRIL 2024'