Open Data Initiatives: what works, what doesn't, and what you can expect
The National Transportation Data Challenge was launched in May of 2017 as an open-data initiative sponsored by the NSF Big Data Innovation hubs. It had all the right ingredients: fantastic corporate sponsorship, good support from local and even federal government and involvement by major academic centers. The goal was to invigorate discussion and work in areas related to traffic and transportation safety. Six months later, at the Challenge’s “grand finale” event -- rebranded at the last minute as a “summit” -- quite a bit of interesting work was shown, but there were few concreate solutions to transportation safety issues.
The closing summit marked the end of an effort that achieved many of its goals and that successfully engaged thousands of participants. As with many open data intiatives, the impact of the program -- though it only lasted for six months -- will likely be felt over years and in places far from the ones directly involved. If the concluding event felt anticlimactic, it was because expectations for the short term impact were unrealistic and perhaps unimportant.
Open data initiatives are unusual in that the outcomes and even the activities are unpredictable. Not only that, but they will often demand the answers to questions that had not been considered and spawn activities unrelated to the original stated goals. But it is possible to measure success and even more so, it is possible to plan to achieve long-term goals. This presentation will examine the factors that can influence the success of these initiatives, by viewing them through the lens of the National Transportation Data Challenge. It will explore what worked and what didn't, delve into the causes of those successes and failures, cite external examples of greater success, and suggest best practices for future initiatives.