The problem with data is that it says a lot, but it also says nothing. 'Big data' is terrific, but it's usually thin. To understand why something is happening, we have to engage in both forensics and guess work.
There's been the emergence of a philosophy that big data is all you need. We would suggest that, actually, numbers don't speak for themselves.
Data and data sets are not objective; they are creations of human design. We give numbers their voice, draw inferences from them, and define their meaning through our interpretations.
Numbers can't speak for themselves, and data sets - no matter their scale - are still objects of human design.
Data only exists within the framework of a vision you're building to, a hypothesis of where you're moving to.
To a collector of curios, the dust is metadata.
There is a reasonable concern that posting raw data can be misleading for those who are not trained in its use and who do not have the broader perspective within which to place a particular piece of data that is raw.
In the digital age, we filter forward instead of filtering out. As a result, all that material is still available to us and to others to filter in their own ways, and to bring forward in other contexts.