Feedback Loops in Open Data Ecosystems
This work addresses the problem of ensuring continuous data re-use for public agencies and data-driven innovators, though it appears incremental as it builds on existing practices.
The paper tackled the challenge of maintaining data quality in open data ecosystems by studying successful feedback loops between data publishers and users in Scandinavian transportation agencies, resulting in the identification of four distinct types of data feedback loops.
Public agencies are increasingly publishing open data to increase transparency and fuel data-driven innovation. For these organizations, maintaining sufficient data quality is key to continuous re-use but also heavily dependent on feedback loops being initiated between data publishers and users. This paper reports from a longitudinal engagement with Scandinavian transportation agencies, where such feedback loops have been successfully established. Based on these experiences, we propose four distinct types of data feedback loops in which both data publishers and re-users play critical roles.