The where aspect in data journalism is a bit ambiguous because it can refer to a geographical location or a digital location, or both.
Where is the story relevant?
You need to focus on where your story is most relevant so that you can craft the most compelling story by reporting on the most relevant trends.If your story is location independent — you're reporting on a trend that's irrelevant to location — of course you want to use data sources that most clearly demonstrate the trend on which you're reporting. Likewise, if you're reporting a story that's tied to a specific geographic location, you probably want to report statistics that are generated from regional areas demonstrating the greatest degree of extremes — either as greatest value fluxes or as greatest value differences for the parameters on which you're reporting.
Sometimes you find multiple geographic or digital locations that exemplify extreme trends and unusual outliers. In other words, you find more than one excellent information source. In these cases, consider using all of them by creating and presenting a data mashup — a combination of two or more data sources that are analyzed together in order to provide readers with a more complete view of the situation at hand.
Where should the story be published?
Another important question to consider in data journalism is, "Where do you intend to publish your story?" This where can be a geographical place, a particular social media platform, or certain series of digital platforms that are associated with a particular brand — Facebook, Twitter, Pinterest, and Instagram accounts, as well as blogs, that are all tied together to stream data from one branded source.Just as you need to have a firm grasp on who your audience is, you should clearly understand the implications of where your publication is distributed. Spelling out where you'll be publishing helps you conceptualize to whom you're publishing, what you should publish, and how you should present that publication. If your goal is to craft high-performing data journalism articles, your headlines and storylines should cater to the interests of the people that are subscribed to the channels in which you're distributing. Since the collective interest of the people at each channel may slightly differ, make sure to adapt to those differences before posting your work.