There is agreement on the need for open data to give an accurate picture of UK public libraries. Locations, staff, type, financial details, stock, and what goes on in them.
How can we encourage all UK public libraries to publish accurate and timely data to a set standard?
National library statistics provide high-level comparative stats. For example, number of book issues per year, per authority. Not much about individual libraries.
The problem with this is that it has no obvious use. No local authority would accept data without the detail of each library. So why compile such data at a national level?
Although the end goal is to have national data, the starting point needs to be local data in a standard form.
Task 1: Create a schema for library data that presents data that can be used at a local level
Make data useful
National stats can be presented with a lack of detail for reasons. One is to make the data more manageable. Easier to compile and publish on paper, or in a simple spreadsheet. Having borrowing data per library may be OK for a single library service, but at a national level? Excel would explode!
Except it wouldn’t, not any more. Computers are powerful and Excel will be fine. The more detail the better. Even monthly data isn’t enough. That tells us nothing about how Monday compares to Friday. Have it daily.
Task 2: Make the data as comprehensive and detailed as possible
Dogfooding, is a term describing people using their own product. In open data, this means using the data. Don’t publish what wouldn’t be useful to yourself, and publish whatever you use.
We want published data to be used, so let’s make it useful. Then get early feedback from the public and data analysts as to what else they’d like to see.
Task 3: Trial data exports with volunteer authorities. Run public events to get feedback on the data
Libraries do things differently, and this will be reflected in their data. For example, some services may use 100 item types to categorise their stock, others may have 30. And those differences are interesting and useful to share.
Attempts at standardising data often attempt to mask these differences. For example, CIPFA provide a set of item types that each library has to convert their own to when reporting their data. This doesn’t accurately reflect the ‘real’ data.
Task 4: Ensure the data schema enforces a standard structure, but allows for differences in content
If you tell services that you want comparable data, the assumption may be that you want to define which are ‘good’ and ‘bad’.
That’s a goal only served by overly-simplistic data. People interested in libraries will want to understand differences. We know that some library services have increases in borrowing, while others have seen a decrease. That could be for all sorts of reasons: changes in opening hours, socioeconomic factors, location of libraries, shifting trends in high street use, etc. Understanding how these affect library use is the first step to increasing usage across libraries.
It’s important to emphasise that more is not always better between libraries. Some libraries may have an increase in borrowing due to their location. Good for them, but they’re no more essential than a library with a decrease in borrowing that serves a particularly deprived area.
Task 5: Commission data analysis to look at key questions using trial authority data. Make that process available to any authority publishing using the data schema.
Data has a bad reputation in public libraries, and the people who have to do it will be sick of it.
At one local authority, data reporting meant manually keying monthly figures into a ‘key performance indicator’ system. This included book loans and visits per library. Data from other council services also went into the system. It would be a dull job even for someone who loved data. But for libraries, reporting performance to senior leaders and councillors as a slow downward trend must be soul-destroying.
That’s not how to use data. Data tells us stories about things we are curious about. We don’t need it to prove worth, but it’s useful for improving services, and making data-informed decisions.
A culture of curiosity about libraries should be enough to encourage data publishing. When is the library most busy? Is that the same everywhere? Is it affected by weather? What about local events and footfall in the surrounding town?
Data can inform policies. Ever wondered if overdue fines are effective? If you can’t remove fines, could lowering them actually bring in more money? What about loan periods for different types of items? Are they informed by data?
An Open Data Literacy project in Seattle has been working with interns to publish stories about library data, and they are wonderful. See this one about using census data in public libraries or the more frivolous but enjoyable hipster reading list of books that haven’t been taken out for 10 years.
Task 6: Blog and experiment with the data. Create interesting stories and make them reproduceable for those with the same data
No-one likes doing the same thing with data all the time. Extracting and publishing datasets should be as automated as possible.
We don’t have that many library systems in public libraries. 6 or so? Capita, Civica, Axiell, SirsiDynix, Infor, Koha. Probably another, and Durham have their own. But that should be 6 pieces of work to automate those datasets, not 200.
Task 7: Pay a reasonable fee to library suppliers, or individuals experienced with each system, to extract the data on an automated basis. Document it and ensure it’s made available to every library service and enabled in all systems
Most essentially, library staff need the skills to do data work. To choose what they want to find out about their library, and get away from repetitive data reporting that isn’t useful.
There are some excellent resources for data training. Artefacto publish listings of Free resources to help library staff level up and learn new skills, and library carpentry lessons and workshops are freely available for anyone to use.
Standard data would allow for training materials that taught library staff skills with actual data. Workshops and training events would give staff the opportunity to use their data with set examples.
Task 8: Create training materials with the data. Run workshops across the UK to provide hands on training opportunities for those authorities publishing it