Getting in a spin with some cultural data

By Julian and Sarah Hartley of Dim Sum Digital

Remember the story of the amazing spinning statuette from Manchester Museum? If your memory needs a jog, this is our favourite piece of coverage on the matter from 2013 to set this blogpost in context.

he story became a viral phenomena in the way that only curiously quirky summer stories can and at the last meeting of the cultural metrics project group, we heard more about the data which researcher Chiara Zuanni has collated on the topic:

  • 14927 tweets.

  • 622 media articles, blogs and forums.

  • around 70 youTube videos.

  • 2868 of comments below online articles.

  • observations and interviews in the Ancients Worlds Galleries.

It was a fascinating insight into the data Chiara had collected and analysed as part of her phd.

But was it big data?

During the session at Cornerhouse, the participants discussed the big data question without too much attempt to define what we mean by the term. In our last blog post here, we hoped to provoke some of that debate further and introduced ideas around the ‘open data’ movement into the equation too.

This was intentional because it’s hard to consider the two things in isolation with them being so intrinsically linked when it comes to practical work in this field.

There’s always a danger of falling into a purely theoretical process to work on a big data definition so, for the purposes of this blog post, we are taking ‘big data’ to mean anything taken from varied and multiple data sources. The classic definition is that big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. In other words, it’s data that’s too big for an excel spreadsheet!

Using that definition, the spinning statuette data on its own, wouldn’t necessarily fall into a ‘big data’ area BUT there were many other organisations and individuals in the room that day with access to additional data which could expand that and, if it was incorporated into data from data sets outside of the immediate cultural sector then - there’s some very big data potential indeed.

The workshop discussions (which will be summed up more fully in a blog post to come this week) considered the data channels and sources held by the different cultural organisations. These revealed that ‘boring’ data, ie. everyday stuff such as attendance levels, can be as useful as the rarer forms of analysis available through organic or social media data, such as the data associated with the spinning statue.

We’d suggest there’s an interesting space to be developed here where the cultural institutional data and the many bigger data sets out there in the world could be interrogated together.

What difference would it make to your institution if your internal data could be overlaid with shopping habits from your locality? With transport trends for your area? With census data? With benefits data? etc. etc.

How would your organisation cope with that? How would it address the supply and demand elements of the findings? Would it change the very structure of your organisation and its activities?

And finally…….

As we leave this project, hopefully with some provocative questions to be considered, we’d like to share an amusing big data set which would be easy to replicate with a whole variety of topics and locations - the autocomplete from Google searches.

It was created by Twitter user @TechnicallyRon and shows a map of England according to the results you get when you type into Google '[Name of county] is’. Does this data set give us a unique perspective on how people feel about the place they live in?


* If you’d like to hear more about data in the cultural sector please do stay in touch via the directors’ blog or on Twitter @dimsumdigital.