Background

Before promoting the event we used a Google form to ask potential attendees questions, such as their data experience, which Library Carpentry modules they'd be interested in, and what they'd like to talk about at a data event.

How would you describe your experience of working with data?

We asked this so we could get an idea of how people viewed their experience with data. That could influence the training sessions we ran, but was mainly to get an idea of the mix of attendees. Any training would ensure every level of expertise was welcome.

Option Description
Beginner Maybe you don't work with data much, but would like to learn more
Intermediate You use data, but would like to share experiences and see where you could improve
Expert You do a lot with data and feel confident using it, but there's always more to learn

Which Library Carpentry modules would you most like to cover?

We wanted to make this a chance to learn data skills. Library Carpentry materials are lessons in different areas around data, automation and programming. We asked people to vote on which modules they would like to learn (they could choose as many as they liked).

Option Number of votes More Info
Introduction to Data 18 Library Carpentry Link
Tidy data and spreadsheets 25 Library Carpentry Link
Introduction to Programming with Python 20 Library Carpentry Link
Cleaning and enhancing data in OpenRefine 23 Library Carpentry Link
Introduction to Git 17 Library Carpentry Link
Unix shell command line interface 13 Library Carpentry Link
Structured Query Language (SQL) 18 Library Carpentry Link

What else would you like to cover?

We were interested in what people would want to talk about. Everyone will be free to pitch on the day, but these are a selection of suggestions we've already received.

Answers
Open data advocacy
How to talk to leaders and managers about open data
How to allay fears and influence senior managers
How to work with Local authority IT teams or departments
How to extract data from specific LMSs
Using/identifying tools for working with data, from data creation, data cleansing/normalization to manipulating data
Open data and libraries
What primary data libraries own and what they use it for.
Using R Studio (R)

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