You always start with the data in hand, but that is seldom the only data you use. As soon as you start asking your data some questions, you find that you need to connect it to other datasets to build context and help you understand what the data might be able to say. This activity helps understand where, when and why to gather data connected to your topic. It also helps participants broaden the definition of what “counts” as data.
What you need:
- an example data set (it’s best if this is the dataset your group actually cares about)
- whiteboard or big paper
- a scribe
How you do it:
First introduce your dataset. Next introduce the idea of “asking data questions”. Invite participants to come up with questions to ask the data. Lead with an example. For instance, if the data is about the health of trees in a town, one question might be “Are there healthier trees in the fancier parts of town?”. Have the scribe capture these questions on a whiteboard or big sticky. Capture 10 or so questions from the participants.
Now introduce the idea of “data shopping”. Lead with an example; wondering what other data might be needed to answer the question you asked earlier. In the example given, you would need some data about where the nice parts of town are. Next think about where you could get that. In this case house prices might be a good representation of where the “nicer” parts of town are; you could get that from public records. Point participants back at their questions, and ask them what other data they would need to answer those questions, and where the data might come from. Have the scribe capture these too.
Finish off by summarizing the categorize of data sources your scribe captured. It probably includes things like:
- special interest groups
- local and federal government
- crowdsourced new data
We borrow the lovely “data shopping” phrase from our friends at the Tactical Technology Collective.