My theme is:
With modern data acquisition methods, collecting large quantities of data is easy. Dataloggers can be set at almost any sampling rate you like, and before long you have oodles of data. Dealing with these data and making sense of them is not easy, but that is where I can help you. I’ve had a lot of experience working as a scientist for NIWA in FRST and Marsden funded research dealing with all sorts of data. Here’s a list of some of them:
· sea-level data from tide gauges;
· river levels and flow from water-level recorders;
· atmospheric-pressure data from barometers;
· stream velocities in 3 spatial dimensions and time from acoustic Doppler velocimeters (ADVs);
· laboratory flume velocities in 3 spatial dimensions and time from particle image velocimeters (PIVs);
· ocean current data from current meters and ADCPs;
· wind data from anemometers;
· groundwater data from water-level recorders and piezometers;
· salinity data from conductivity sensors;
· topography data from laser altimeters (like MOLA – Mars Orbiter Laser Altimeter);
· bathymetry data from hydrographic surveys.
You can find examples of each of these in the reports and journal papers listed on my biodata page.
Here are some of the analysis methods that I have in my skills toolbox:
In the Portfolio page, you will find examples of how I’ve used some of these methods to reveal what’s behind otherwise incomprehensible data. I call this the Rumpelstiltskin Paradigm: spinning straw into gold.
Last Updated: 18 November 2003
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