Traffic accidents have a devastating effect on society, and despite the measures taken by transport authorities, numbers still are of concern. As such, various studies emphasize the need for investments in the road infrastructure, vehicle safety, and enforcement measures. However, traffic and accident data are scattered among several stakeholders. Police authorities, emergency agencies, hospitals, road concessions, and the national road safety authorities all hold partial data about accidents and their consequences related to human lives. If such data could become widely available on production time, e.g., when an emergency doctor reports injuries or deaths, a police officer registers the scenario, etc., intelligent analytics could be used on such data towards helpful decision support. To cope with the wide diversity of data sources and ownership, more than data integration, this requires an approach for collaborative data management. Based on previous work on strategies to structure computing and communication artifacts and data science management, we present and discuss a collaborative traffic data management strategy considering the data producers as part of an intelligent traffic collaborative network. The challenge is thus to rethink traffic and accident data collection and management under the responsibility of diverse organizations, keeping their processes and technology culture, but promoting sharing and collaboration. Therefore, the proposed approach considers data analysis performed through business processes executed in the context of virtual organizations.