NICAR, from a Programmer's Eyes

Last week I attended NICAR 2012, a conference for computer assisted investigative reporting. I was there to help David teach reporters how to use tools such as Datapress and Exhibit and to learn about the needs and state-of-the-art of computers in reporting. It is always a privilege to get to visit and observe someone’s world as an outsider; and even more so to see how they are using tools from your world to do their work. So here are some parting thoughts I took away from the conference: NICAR from the eyes of a computer scientist.

Visualization is just the "last mile" of data in reporting. And an optional one at that. We spend a lot of time talking about data publication and visualization tools in Haystack, but this is just one small slice of the needs of computer-assisted reporting. A story might take months of investigative work- gathering data, cleaning data, interviewing people, assembling scraps of paper — and a presentation of that data is only prepared in the final run-up to publication. That presentation isn’t always a wiz-bang interactive graphic, either. Many times a data-intensive story might be presented entirely as narrative, if the medium fits better.

Scraping tools seriously needed. Web scraping wins the award for highest ratio of need over capability. Scraping the web is absolutely essential to do good investigative work when it comes to municipalities, many of which publish web pages with daily administrative information (such as arrests) while removing the previous days’. Without a scraper, reporters would have to spend a large portion of each day copying and pasting this information down into a spreadsheet by hand.

Big Opportunities for Automation. Ben Welsh of the LA Times gave a great talk about how he automates his reporting through a combination of web and email scrapers, databases, and automated copy generators. The goal being to auto-generate 100% of reactive stories (deaths, arrests, etc) and then go back and rewrite the most important ones by hand. Reminiscent of AtomsMasher for the newsroom.

And machine learning, too. Tools that enable reporters to perform topic modeling and hierarchical clustering are making a big splash. They can go a long way toward helping a reporter understand a big data dump so they know what documents to focus on. I think the coming years are going to big for the dissemination of machine learning components into a lot of consumer software. Tools that enable reporters to say “give me more documents like these ones” will be a bit hit.

The CMS is Broken. One refrain I heard over and over is how much the reporters have to fight with their CMS. For reasons both technical and administrative. A common solution seems to be for custom news apps to be hosted out of a subdomain on third party sites (AWS, Heroku, etc) with window dressing to provide the illusion of being a part of the main news site. However as a totally separate entity, these news apps don’t get integrated into the standard RSS feed, advertising system, top stories feature, and other critical elements of the CMS-managed web of data, casing traffic and revenue challenges for their authors.

What happens when your paper is the business of causing protests? I went one session where the creators of, two employees from The Omaha World-Herald, discussed the hopeful (revenue-wise) but new territory of transforming the news into apps. Here’s the gist: print ad revenues are falling, but online ad revenues are a pittance in comparison. To make up for lost revenue, newspapers can exploit their intimate knowledge of a locale by creating community-specific information sites and charging for them somehow. But what happens when that site is, like Curbwise, a way to protest your home’s valuation? Now the newspaper has a financial interest in causing people to protest their home valuations. Is that territory we should be comfortable with newspapers occupying? Do they occupy it already (to the extent that extreme news is news that sells well, so there’s always an incentive to fan a fire)? Food for thought.

Appification of news, in general. Continuing on the previous thought, there was enormous interest in the idea of transforming news into for-fee “apps” that deliver a targeted news experience. Such as paying a small fee to get your kid’s high school football scores in a format that looks like

The need for computer science as a liberal arts requirement. If ever I haveeen a good argument for computer science as a liberal arts requirement, going to NICAR was it. It was amazing and energizing to see the extent to which computers are enabling better reporting and storytelling. In some cases, surprising to see how programming has become an essential tool for some areas of reporting. In today’s world, knowing how to program better equips you to make sense of the information around you and communicate your findings to others.

The need for computer scientists to grok liberal arts. On the other hand, we as computer scientists need to be delivering tools — serious data crunching tools, visualization tools, curation tools, scraping tools — that are built for use by people who spend their days thinking about things other than computers. Because I want my local reporters to spend their days fact checking the good stories, not brushing up on Python.