Our world is ruled by data. One widely-cited figure estimates that humans generate a mind-boggling 2.5 quintillion bytes of the stuff each day — the equivalent of 2.5 million terabytes — and it’s possible the true amount is even greater. Indeed, it’s hard to do anything these days without generating at least a little data. Our smartphones record our movements. Companies track our purchase habits. Data is everywhere, all the time, even in the stories we tell.
For science journalists, the prodigious growth of the world’s total data volume presents both challenges and opportunities. Information that is essential to your reporting may be buried in data that is inaccessible or indecipherable. Even when the data you need is freely available, it can be confusing, misleading, or simply inaccurate. However, for journalists who are able to overcome these obstacles, the storytelling possibilities are practically endless.
Most practicing journalists already have some sense of how to incorporate data into their reporting, especially when that data is presented in a well-structured, user-friendly format. However, the ability to craft a story using raw data — which can be messy and difficult to parse — is a skill worth honing, especially for journalists who cover science. To help you get going, KSJ has provided a collection of resources and tools for finding, analyzing, and presenting data.
They are organized into the following subtopics:
- Data Journalism 101
- Training and Tutorials
- Data Journalism Toolkit
- Further Reading
To explore a subtopic, click on a category at left (desktop) or within the dropdown menu above (mobile).