New Orleans is a tourist town, and for decades hotels and bed-and-breakfasts have been conscious of potential competition from residents. So for decades it was illegal to rent a home in the city for less than a 30-day stretch, and 60 days in the French Quarter.

But it wasn’t hard to get around the law (using Craigslist, among other tools) and the city rarely, if ever, enforced the law. Until Airbnb came along. City leaders heard complaints that the city was becoming overrun with Airbnbs.

The problem was no one knew how many there were, or where they were. Everything was anecdotal. This was important both for policymakers, who had to figure out whether they would try to limit the number of Airbnbs, and if so, by what measurement, as well as neighbors, renters, investors, long-term landlords, and tourists. The city did a study to estimate the number, and an Airbnb watchdog scraped the company’s listings to estimate how many there were. Both were limited.

That changed after the city decided to legalize and regulate Airbnbs. Those licenses, and the applications to get them, were public records, like a business license or a parade permit. And they were available on the city’s website, which was a measure of openness. The city would seem to be best positioned to tell people how many Airbnbs there were and where, because it had all the information.

But bureaucrats aren’t journalists. Their system easily allowed searching for permits by address, which is typically what code enforcement employees needed to see if, for instance, you had permission to renovate your home. It didn’t make it easy to search for all types of a certain type of license, and to get a sense of where they all were.

So one of the reporters for my news organization figured out how to use the city’s online search to show all short-term rental applications. He cleaned the data to remove stuff like applications that had been started but not submitted. Then he mapped them and matched them to photos of the properties that he obtained through another agency. (Unfortunately errors and inconsistencies in the records didn’t allow this to be completely automated.)

It immediately became one of our most popular features, as people checked to see if the places in the neighborhood they suspected were Airbnbs actually were. That’s pretty much what we expected them to do. We also expected people to use the map to gauge where Airbnbs were most concentrated. That happened too. This data guided our reporting as we knew what neighborhoods to focus on. We wanted this debate to be informed by facts rather than anecdotes, and I believe we accomplished that.

But we knew that opening up this data would be somewhat controversial. These are legally public records, so applicants had no reasonable expectation of privacy. But there’s a difference between allowing people to search a government database and putting it all on an easy-to-use map.

So before we published our map, we thought about what to include. The data was based on what applicants or city employees had entered. Government forms aren’t always easy to understand and clerks make mistakes. If you hadn’t looked closely at the data, you would’ve wondered why there were so many Airbnbs downtown. Turns out they were all at City Hall, and they were registered to Mickey Mouse – test data, presumably. Our reporter also noticed inconsistencies in who was named as the applicant. Because of that, and because the name of the applicant isn’t as important to the public policy question as the location of the Airbnb, we decided not to include that information.

That decision turned out to be the right one. At some point, we got a call from a woman who was angry that we had published her name as being the operator of a bunch of Airbnbs. She or her boyfriend had apparently been confronted in a bar about it. That woman actually was just the person who cleaned the Airbnbs, and her name had been entered as a contact person on the applications. We had not published her name, but another news outlet that did its own map had.