We’ve had a fantastic early response to our call for contributions, and it has been pleasing to see and hear how our plans for Real World Data Science chime with the wants and needs of the data science community. But one question we’ve been asked frequently is: “What particular topics are you most interested in?”
The honest answer to that question is this: we’re interested in any and all topics that are of interest and importance to you, the data science community at large. However, we thought it might be helpful to identify some themes around which potential contributors could construct different types of content.
These themes are outlined below. If you’d like to discuss any of them further, please do not hesitate to contact us.
Can data science save the world?
Earth today faces major challenges – from the global to the regional to the local, and from the natural and physical to the social and digital. We have rich sources of data to help us understand many of these challenges, and there are teams of data scientists around the world who are working with, analysing, and extracting insights from that data in the hope of delivering positive lasting change.
On Real World Data Science we want to highlight this vital work, through case studies of data science projects and applications in such areas as:
- monitoring and mitigating climate change and biodiversity loss
- building sustainable futures
- safeguarding public health and developing new medical treatments
- understanding human happiness and wellbeing
- identifying and preventing online harms
- measuring national, regional, and local economies
As well as exploring the benefits that data science can deliver, we also want to have an informed conversation about the unintended negative consequences that can arise without careful consideration of data ethics and responsibilities.
What is a data scientist?
Don’t be misled by the title of this theme. Definitions abound, but we’re not interested in establishing the exact boundaries of what a data scientist is or isn’t. Rather, our goal is to profile actual working data scientists. We want to hear about their skillsets, their experiences, and their career journeys so far. We want to learn about the ways in which they work, who they work with, the challenges they face, and their thoughts on where data science is heading next.
If you’re a working data scientist and you are happy to share your own career story, please get in touch.
Statistical ideas all data scientists need to know
Statistics is a crucial component of data science, but not all data scientists have a background in statistics. For those just starting out in their data science careers, or for those coming in from other fields, we want to highlight some of the statistical ideas that are absolutely vital to know.
We’re particularly interested in explainers that serve as an introduction to these ideas, alongside which we’ll be looking to publish exercises and example datasets to help people put what they’ve learned into practice.
We are also keen to explore the origins of modern data science techniques, including tracing their roots back to some of the foundational ideas in statistics and other disciplines.
What’s happening in the world of data science?
Data science is such a fast-moving, fast-developing field that it’s difficult to stay on top of all the latest news and developments. But racing to keep up can be counterproductive. It leaves little time to sit back and reflect on what the genuinely important new developments are, and what these might mean for data science longer term.
On Real World Data Science, we want to create a space for people to have these conversations – to step outside the news hype cycle, to ask big questions about what’s happening in the field, and to discuss new papers and ideas that otherwise might be lost amid the daily rush and noise.
So, if you have thoughts to share, a question you want to ask, or a new paper you want to talk about (one you’ve not written yourself, of course!), let us know.
- Copyright and licence
- © 2022 Royal Statistical Society
This work is licensed under a Creative Commons Attribution 4.0 (CC BY 4.0) International licence, except where otherwise noted.
- How to cite
- Tarran, Brian. 2022. “Four themes for potential contributors to think about.” Real World Data Science, December, 1 2022. URL