What I gathered mostly from these case studies is that using data in the newsroom to tell stories takes a lot of time and teamwork to put together. While all of the same practices from other forms of journalism are present, these case studies are highly visual and take larger teams that dedicate much more time to these than to simpler stories.
Another observation I noticed was that the data that these data journalists gather is rarely up-to-date. Many of the teams who got data had to spend a significant amount of time cleaning the data and making sure they could write a story with data that was older and not exactly breaking news data, but the journalists need to search for stories to tell that their audiences would not be able to ever get a chance to see by themselves.
These stories featured in the data journalism handbook are exemplary and do require a lot of time. It doesn’t have to be that way. My goal is to show you how you can incorporate these tools into your daily workflow, so it won’t require a team to pull off a simple story. And then you can plug into the teams when necessary.
Good comment.
As for the data, a lot of it is “dated” in one sense — but then very up to date compared to where we used to be! Good observation.
Data cleaning takes a lot of time, as you will begin to see today…