In a time of constant evolution, data journalism is becoming more of a necessity in multimedia reporting. Darryl Laiu is helping the DevHub at Hearst Newspapers to help make interactive graphics accessible to local newsrooms as their 2025-26 data visualization fellow. By blending together engineering, design, and reporting, he helps make data visualization possible for other journalists who may not know how to code. 

Laiu, a graduate of the Columbia University Graduate School of Journalism and a former BBC multimedia video fellow, developed a passion for all things data during his time in New York. Whether through projects at Hearst or personal projects on his GitHub, he is always looking for opportunities to make data engaging and accessible. 

Storybench talked to Darryl Laiu about his fellowship, his data visualizations and his outlook on data journalism. Laiu shared anecdotes about his projects and his experiences with capacity building at local news organizations. 

The following interview has been edited for length and clarity.

What does your day to day look like as a data visualization fellow at Hearst?

I’m on the visual storytelling pod, or team, so my day to day depends on the project I’m on. For some projects, if it was already kind of built out, then I’ll be helping them build some of the graphical elements or even some of the connections and small components of the bigger project. If it’s a project that I’m part of from the start, then I’d ask myself “how do I want to tell that story?” And then the process entails coming up with mocks for it and thinking about the reader’s experience, and then possibly data analysis. And then eventually, I’d build the project out.

What does that relationship look like between what you’re creating versus how it’s disseminated to newsrooms?

The DevHub existed way before I joined, with many experts on the team already. I think first is interesting in this aspect where they built a whole bunch of templates called React templates These templates help newsrooms create simple interactive stories without having to code. Part of my role is to help upkeep those templates, think of new templates, and to improve those templates. One cool thing about this sort-of Hearst universe is also that if one newsroom does a story, then the DevHub helps to replicate that story across different cities and different markets. One specific example is that the SF Chronicle did a story about the return on investments of different colleges within California. The data set was national, but they scoped it down to California. After it was published in the SF Chronicle, DevHub thought that it could be done for different states and different cities also. That was assigned to me and then I took it out, translated the analysis into the other states – like New York, Connecticut, Texas – and then helped local reporters work on the story. I do the data analysis and then they know the context and do the reporting. Then we piece together a new story for Connecticut, New York and Texas.

Can you walk me through another recent project that you’re proud of?

A lot of them are in progress, but there is one project that I’m proud of. It was a project that I joined a bit later, when a lot of it was already built out, but we built a grocery price dashboard. There’s grocery price data online, and then we managed to scrape it and restructure it. We built a dashboard for each of the newspapers that Hearst owns for readers to compare prices of groceries across time. You can see the prices of the different categories of groceries, like produce, from 2019 all the way to the present. It updates live and you can compare it with national data. I was very happy to be part of that because it’s not your typical news story. It really does resemble more of a dashboard where readers can play around with it and compare the prices. 

How do you make sure that the projects work for a broad range of audiences?

I think at the DevHub, it’s a core part of our brainstorming process to think about how projects would work for a broad range of audiences, and that includes demographics and interests.For example, when we pitch the different newsrooms an idea, we are always thinking, “Is it something that can be done for all markets or is it something that would only work in one market?” The grocery price dashboard is an example of a project that works well because it’s one idea that was executed and localized for the different cities that we cover. [For example,] if I’m going to the Houston Chronicle, it would show me prices in Houston compared to national prices, versus if I logged into the SF Chronicle dashboard, it would show me San Francisco compared to national prices. We also take stories done by the newsrooms if we think they would work well for other cities. For example, the SF Chronicle did a college story that’s specifically about California and UCs [University of California system]. Obviously, UCs is a super Californian thing, so then part of my role was seeing how can I translate that to New York or how can I translate that to Texas? Then I ask what questions make more sense for those states, those cities? That’s the cool part about Hearst, they are very into local news and stories. Data can be national,but how do we contextualize it for the more localized content?

In your experience, what are the biggest challenges and opportunities for data visualization in local journalism today? 

I think it’s just resources. If the newsroom’s smaller, they don’t have as much of a budget to bring on people to help do data. For Hearst, being part of that bigger network helps because you not only can learn from the other newsrooms, but then you have a DevHub that you can tap on. If you’re a smaller newsroom, you can use some of the tools and the templates that we’ve already built for it. Some of our newsrooms may only have two data reporters or graphics reporters, but because we have some of the templates that already make it easy, like we have a scrollytelling template and other templates that hook up to Datawrapper a lot easier. And that means that you don’t need the coding skills or the hard data skills to do a data visualization or a quick data analysis. I think that’s one thing that Hearst has done well, making it easier for any journalist to create a story with a more interactive experience.