The dataset
The oh, those everyday spaces database is comprised of a number of fields. These fields are of two types: raw data and derived data. Raw data has not been manipulated and includes: image reference (pointing to an image file), imagedatetime, position components (zone1, zone2, easting, and northing), temperature, condition, visibility, humidity, dewpoint, wind direction, wind speed, and wind gust. Derived data is calculated from raw data and includes: speed (distance/time), direction, avgdirection, gpspointdiff. A random sampling of the dataspace is displayed on the right.
Ordering by speed or temperature for example, creates relationships through grouping experiences based on those parameters. For instance, what are the various situations where I would be traveling 10 km/hr, 25 km/hr or 50 km/hr? Things get quite a bit more complicated when one wants to ask and answer questions like: Given that you are traveling along a particular road, what is the next datapoint in space? What I really needed was a way of thinking about the data that would help me develop strategies for working with these questions.
