Every now and then I drop into the MOL library and flick through the latest journals. There's usually something to catch the eye. Last week, as well as the Bearman interview I mentioned already, I picked up March's Cultural Trends, which includes an article from Sian Everitt that reviews data collection and documentation pracitices for Renaissance in the Regions.
It's not a brilliant piece, to be honest; it's limited by reference to online publications and ends up muddling the question of what data are gathered with that of what is made available on public websites. Everitt was writing in advance of a review being conducted for the MLA (review FAQs) by an advisory group led by Sara Selwood, Phase 1 of which was to be completed last autumn so as to inform the business plan for the years ahead [note to self: track down other Selwood refs on data collection in cultural heritage]. Because of this it's quite likely that Everitt's findings were out of date before they were even accepted for publication. All the same there are some interesting points within the paper. For example, despite the declared intention of Renaissance to standardise methods of evaluating impact, Everitt finds notable variability in how this is actually undertaken. Two Public Service Agreement targets are applied to Renaissance, and measurements against these seem to be uniform, but beyond this and the headline figures there is less consistency; likewise the approaches to making their data, analysis and reports public vary greatly. I also discovered that the MLA also offer a set of Data Collection Guidelines and templates, which I now need to digest. Presumably this 2008 manual (PDF) is the replacement for the 2006 version that Everitt was refering to, and here's a page on the MLA site about the results to 2006.
I look forward to seeing whatever parts of the Selwood-led review are published. The overall direction of Renaissance is up for grabs, it would seem, which could have a big impact in the Museum of London, for one. I will be especially interested, though, in the data collection strand, and in how they suggest we evaluate impact.