The Data Collective — Weeknote #6

By Tom Rintoul, Data Collective organiser. Cross-posted from the Data Collective website, a community for people using data in the social sector.

How It Started…

Volunteered to write a weeknote :facepalm. Wanted inspiration so read the latest from Edafe Onerhime and Tobi Ogunsina. Got slightly intimidated, but lowering my ambitions helped me get back on with it (productivity hacks being an important part of weeknoting so far as I can tell from webofweeknotes).

Getting into the Week’s Data Collective Work

Collectively (if you’ll pardon the pun) we are finding out who is out there in charity world, what kind of help they want with data, and how we could help make that help easier to find/give. I sat down with about 70 requests for help, to start making sense of who wants what.

Who Wants Help with What?

• A big group don’t know where to start. “Where to start” actually comes up more often than any other phrase. There’s a sense that something good ought to be possible, but that we need to talk to someone to work out what a sensible ambition is. Mainly small charities.
• Another group are data people in big charities (mainly £100m+ annual budget) who are thinking about architecture, governance, data models, etc.
• There’s an interesting little group who want to work on data sharing — mainly helpline providers who want to pool data on the themes they are observing to get a bigger dataset and ask new questions. We’re running a workshop with some of them on Friday 26 February — interested in joining? Sign up here.
• The rest are a long tail of one-off requests for help on topics including web-scraping, GIS, recommendation systems, choosing/configuring/embedding CRMs, web analytics, and data visualisation. People are also asking and answering questions like those in the Data Collective and DataKind UK slack channels.

We’re cross-referencing what we find here against what another Data Collective organiser, @MrTomFrench is picking up in his workshops and in this survey which is live for a few more days.

What Can We Learn from Analysing the Social Networks of Self-Declared ‘Charity Data People’?

Really enjoyed hearing @edsaperia talking about how he’d analysed the Twitter activity of the charity data people we know about. After all — if they’re well-networked on Twitter then maybe they don’t need the Data Collective slack channel.

Short version:

• The vast majority of people who’ve already joined the Data Collective are on twitter, but….
• They have very little interconnection — not much following of one another, not much interacting with one another’s content, and they don’t even have many follows in common
• Most who say something about their professional identify on their bios describe themselves as researchers

Ed is still thinking about what has worked to build denser twitter communities in other fields and whether we can catalyse the same effect here. If we succeed, do we still need the slack or does it serve a slightly different purpose?

How It Ended

I joined the Friday morning get-together with the Data Collective organisers. Over two months in now, starting to feel like a team, and I look forward to seeing them.

I’m left with a bit of time this afternoon to think about strategy. We’ve been going for a couple of months and have had a chance to start learning from both our user research and some of the prototype activities. Pivots are probably in order in a few areas, and that brings back the discussion of what we’re trying to do and what is already known about it.

My north star here is a blog from Cassie Robinson. I’ll leave you with her musings (channeling Social Innovation Generation), as they’re what I’ll be thinking about by the time anyone reads this.

Any thoughts on whether, how, and why these are to be done in charity sector data — please shout.

Some of the key activities of field-building include:

• Connecting fragmented players in a given area of work
• Connecting people so that new ideas can be generated and new resources pulled into the field
• Building common infrastructure, practice and shared standards, including access to shared resource

And some of the ways it can be useful are:

• Brings attention and legitimacy to a certain issue
• Brings coherence to a field
• Increases the exchange of theory & practice between domains (in order to tease out best practices and reduce inefficiencies)
• Develops incentives for collaboration that may not have happened organically

Taken from Building the Field? by Cassie Robinson

Community round up

• Take part in our survey: The Data Collective survey is an opportunity to shape the Data Collective while in its pilot phase. Please share your thoughts and pass the survey on to others that you think would be interested. Share your thoughts
• Data science support: DataKind UK supports organisations that think they could be using their data better, with free programmes that kick-start their use of data science. Find out more about our programmes.