I’m looking for a starting point for some sessions on data-driven journalism – one that’s based on scepticism, rather than one that just launches us into the technology and the tools.

This is an interesting quote from the Data Journalism Handbook:

When information was scarce, most of our efforts were devoted to hunting and gathering. Now that information is abundant, processing is more important.

The key to the quote is the conflation of data and information. Yet it’s a truism of knowledge management that these aren’t the same thing. Information is data that have been processed.

So an abundance of information merely means that there’s more data-processing going on. This might be for a variety of reasons: easier tools; cheaper kit with more processing power; more people to do the processing …

In this context, of course, by more people, I mean more journalists.

So is the growth in data-driven journalism based merely on a (per)version of Parkinson’s law – the more people there are to process data, the more information there is?

And, if so, so what?

Here’s what: a key assumption behind data-driven journalism is that it has a value-free source as its basis: raw data.

But does it?