Following the present open data policies, traffic data are collected and increasingly made openly available by different organizations. Yet, expanding use of mobile technologies with tracking possibilities provides means to collect precise and rich information about individual vehicles and persons in traffic. This personal driving data, combined with other open traffic data, have a great potential for future open service innovation. However, information privacy presents a major challenge for collection and efficient utilization of the data. In this paper, we present a view of the near future development of personal driving data collection and usage for open traffic data production by addressing the privacy challenges. We review the existing privacy behavior models and present our empirical findings from driving data based service pilot studies. Our results show that, despite their privacy concerns, the data subjects are willing to disclose driving data for services, especially for some benefits in return. We identified the following key factors affecting data disclosure: informing of personal data processing, trust in organizations of the service ecosystem, and users’ control over their data. Understanding of these factors helps mitigating the users’ privacy concerns when personal data based services are designed and production of open data is planned.

Keywords: Open data, Service innovation, Data privacy, Privacy concerns, Privacy behavior models