On the left we have zero, our integer measure of nothingness. On the right we have missing value, aka N/A, aka NA, our signal that the value of a datapoint is unknown. Everyone who deals with data has to deal with this important distinction. And far too often people get it wrong.Continue reading
In the marketplace, the needs of producers and consumers are often at odds: producers want higher prices, consumers lower ones; producers want easy assembly, consumers easy dis-assembly; producers want flexibility and rapid prototyping, consumers reliability and long-term support.
The same competing needs exist in the world of scientific data management where producers of data and consumers of data often operate in very different worlds with very different sets of tools.Continue reading
What? Where? When?
These are key questions that every scientist or other collector of environmental data must answer.
- What is the value of the thing we are measuring?
- Where are we taking the measurement?
- When are we taking the measurement?
In a previous post we discussed how to standardize “when”. But what about “where”?Continue reading
One of the big jokes among people who manage scientific datasets goes like this:
The great thing about standards is … there are so many to choose from!
While this one liner may never make it to late-night TV, there is much truth to it. Many “standards” exist, and many more are invented each month to accommodate the special needs of new types of data or new software for processing data.
There is, however, one exception that proves the rule: ISO 8601– the international standard for representing dates and times.Continue reading