  Scenario-based testing is a promising method to develop, verify and validate
automated driving systems (ADS) since pure on-road testing seems inefficient
for complex traffic environments. A major challenge for this approach is the
provision and management of a sufficient number of scenarios to test a system.
The provision, generation, and management of scenario at scale is investigated
in current research. This paper presents the scenario database scenario.center
( https://scenario.center ) to process and manage scenario data covering the
needs of scenario-based testing approaches comprehensively and automatically.
Thereby, requirements for such databases are described. Based on those, a
four-step approach is proposed. Firstly, a common input format with defined
quality requirements is defined. This is utilized for detecting events and base
scenarios automatically. Furthermore, methods for searchability, evaluation of
data quality and different scenario generation methods are proposed to allow a
broad applicability serving different needs. For evaluation, the methodology is
compared to state-of-the-art scenario databases. Finally, the application and
capabilities of the database are shown by applying the methodology to the inD
dataset. A public demonstration of the database interface is provided at
https://scenario.center .
