A Feasibility Study of an Agile and Data-Centric Method for Prototyping Services Based on Open Transport Data

Data under open licenses and in reusable formats, often referred to as “open data”, is increasingly being made accessible by both public and private actors. Government institutions, municipalities, private companies and entrepreneurs are among the stakeholders either having visions of new open data-based services, or just looking for new ideas on potential innovations based on open data. It is, however, in both cases, often unclear to the service developers how the open data actually can be utilized. A main reason is that the data needs to be retrieved from multiple sources, understood, quality checked and processed. While gaining insights on possible services that can be created on the top of open data, a service developer has to undergo an iterative “trying and failing” exercise of service prototyping. In order to be practically feasible, such a process needs to be agile and efficient. Open data from the transport sector is in this study particularly focused on and used as a case. The open transport data are characterized by many challenges common for open data in general, but also a few specific ones. One of those challenges is the need for combining (often real-time) data from rather many sources in order to create a new service. This paper is an extension of our earlier research, which introduced a novel data-centric and agile approach to early service prototyping based on open transport data. In particular, we present a refinement of the initial approach and its evaluation in a significantly extended trial and discussion about the lessons learned from it.