Week 4 – Mining data

A few thoughts about  big data/ small data and how data is interpreted and presented within a cultural heritage context.

As Posner and Sherratt point out, it’s messy – the data used in digital cultural heritage is most often ‘mined’ from a variety of sources and often lacks threads of connection and any meaningful engagement and interpretation – flat, lifeless, unwieldy, incomprehensible, nor relatable.

I can see how engaging with the available digital data sets and collection repositories, would help me to navigate this impervious data world, understand its breadth and complexity and exploit its potential to fathom and discern areas of interest or, buried treasure!

The tools presented to us, which are freely available to help us engage and experiment with data (after investing time and working through the guided tutorials), including mapping and graphing with plot.ly, screen scraping with import.io and cleaning data with OpenRefine, all provide a way in.

Still haven’t engaged with or tried GIF tutorial and only just starting to come up with idea(s) for a project – mapping and visualising public and private cultural (artefact based) collections in Australia; but where will I get the data ?? do I start with google…yikes! nooooooooooooooo?

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