The search for hydrocarbons is inherently spatial: we are trying to
answer the question "Where is the oil?".
 "Southern England")
And the image to the right is not some random satellite photograph
of southern England- I was part of a crew that shot a seismic survey
over this area. Fortunately, my efforts at saving the environment
were well placed and, as I managed to achieve on every survey,
we either came up dry or the discoveries were not commercial. I
absolutely believe that I used more oil during my career in
exploration than I ever found.
Fortunately, I believe that I am slightly more successful at
delivering computer systems.
But back to the fact that we are looking for the location of the oil it is not surprising that virtually every interpretation and analysis application used in oil companies contains some sort of map.
The Shape of the Earth
Creating a map using spatial data comes with a series of unique challenges. Many of these
challenges arise simply because the earth is not flat, and nor
is it some easily modelled sphere.
 "The Geoid")
Instead it is an odd shape
and the only way to convert locations from this odd shape to
a 2D map suitable for printing is to perform some sort of
mathematical operations.
The science behind these calculations form a whole other section on datum and projections. But for a more academically correct point of view, you should probably check out a book such as Datums and Map Projections by Jonathan Iliffe, a professor at University College London. He also presented a course on datums that I took- and for such a dry subject it was really rather good.
Resolution of Spatial Data
Building a system that is aware of these complexities is the first step to being 'spatially aware'. However, this is not the end of the problem. The next step is to address questions such as "How long is the coastline of Great Britain?". This simple question is heavily involved with fractal geometry- the answer to the question is "It depends" and the reason it depends is that the length of the coastline varies according to the stick used to do the measuring. If a 1m stick is used then the answer will be different from using a 1cm stick. The science behind this is explained in a classic "popular science" book called Chaos by James Gleick. If you haven't read it, then you really should- not only does it explain some incredibly neat science, it does it in a way that made me want to investigate it more. But that is a whole other story.
Spatial data is tightly dependent on the scale that the data was sampled at. Fortunately, spatial data does not (at least not to the best of my knowledge) often run into Nyquist frequency issues but it does determine scale ranges that the data can (or should) be used over.
But what about GIS?
You may have noticed that there is no mention of a GIS- this is because spatial systems are more than simply the functionality that we can see through a GIS: Spatial systems can be
- Location based services that allow you to find your way home
- Spatial searches in a document management system
- Or many other systems
And yes, I recognise that I may now be strung up for heresy. In my defence, I believe that holding this opinion allows me to design better systems as I am not blinkered into thinking that a single solution is the way to go.
On the other hand, there is a whole other section on GIS, just waiting for you to click on. Go on, you know you want to.