The goal of our data focused blogposts is to share and explain data methods used in the Toolkit and the insights we find as a result of research. Most of the content here will be written by me (Marc) as the lead analyst and data scientist for the Toolkit.
I appreciate that most of the Toolkit’s users are not data analysts, so I know how important it is that things we share are simply and clearly explained. This is a high standard to aim for when it comes to a technical subject. Nonetheless, I believe it’s worthwhile: it’s better to bring everybody along than make fast progress with only those who are already ahead. We want to expand the understanding and use of data and not just talk to those who already understand it.
Before working on the Toolkit, I spent some time working in open source software. In the simplest terms, open source means showing your working and not just your answers. Open source methods place a lot of value in community and honest collaboration.
Open methods were first used in science, where peer review and publishing the details of experiments have been done for centuries. With the advent of the internet and the wide availability of data analysis skills and tools, many scientists are advocating for even greater openness in science via the Open Science movement. (https://opensource.com/resources/open-science).
Why am I talking about open source and open science? There are reasons why the principles around open source enable those using them to achieve amazing things. When the goal is to solve a problem or get to the correct answer (without concern for owning the rights to the solution), I think there is no better system.
We can use these principles for our research on the Toolkit data to get the most out of it. In this blogpost I’d like to introduce these principles that we’ll be using for our data work going forwards.
This website gives a great overview of the principles in what it calls the open source ‘way’ https://opensource.com/open-source-way. The overriding principle is that of transparency, and that transparency has positive knock on effects.
We want to make it possible for anyone who is interested to be able to access the data, or at the very least be able to understand what we are doing with it and make suggestions or requests.
Let’s take a look at the principles:
Be as open as you can (within data privacy restrictions) with your data, goals, methods and results.
Being transparent means that anyone can bring themselves up to speed and contribute their feedback, their ideas, or even their own work towards a shared goal.
Release early and release often
It’s better to share a work in progress early and get feedback than to wait until it’s ‘perfect’. Experimenting helps us learn by doing, and if we’re transparent then everyone learns from our experiments.
It shouldn’t matter whose idea it is if the idea itself is a good one. Good ideas can come from anywhere, and the best ideas should win.
Communities form when groups of people work towards a common purpose. It results in more eyes on a problem, more ideas, and more solutions. The only way a community can form is for someone to declare their goals, do some work towards them in a transparent way, and invite others to collaborate and share in the rewards!
Transparency for the Toolkit
Now that we’ve looked at the principles, if we want to start following these principles for the Toolkit what does it mean? In brief:
- We’ll share our data and our findings, or provide tools for you to explore the data if it’s private
- We’ll invite anyone to propose research question ideas and pursue answering the questions which offer the most value or interest to the sector
- We’ll talk publicly about the work we are doing e.g. this blog!
Over the coming months we will be sharing more on this blog to improve data transparency for the project.
As well as sharing, it’s equally important for us to listen. Otherwise, how can we benefit from more eyes and minds on the problem and expedite the best ideas and learn? To get involved you can get in touch via email us at email@example.com
We look forward to hearing from you!