Imagine 'Data' being an organism, a living being existing in an environment we tend to call 'organization'. In the field of biology there are two types of organisms in such an environment; conformers and regulators.
Those organisms that conform allow the environment to determine several important life system parameters. A reptile for example uses a sun-heated rock in the morning to raise its body temperature. So - conformers needs to change its behavior to maintain homeostasis.
Those that regulate, maintain life system parameters at a constant level over possibly wide ambient environmental variations. It has the capability to adjust its metabolism to maintain homeostasis. In other words; we - human beings - are regulators.
Now, imagine 'Data' being a regulator. This would mean that 'Data' is capable of adapting, self-sufficiently, to different environmental variations. Now, in several discussions regarding data - especially Big Data - I encounter an assumption that data by itself can have value, meaning and relevance. And if there are lots of it, its value is even bigger!
That is just so wrong….
'Data' is definitely a conformer - its environment determines its life system parameters. Its value, it’s meaning, its relevance is - by definition - determined by the environment.
Still with me? Lets continue.
What is left of 'Data' - being a conformer - when it cannot correctly detect its environment? Or even worse, what happens to 'Data' when the environment is void? The answer is simple; it can not sustain, even worse, it can not exist. 'Data' is profoundly in existential trouble.
Data needs context
Data needs metadata
Data needs definitions