The demand for data and accompanying services is ever-increasing, which poses several challenges in managing data driven systems. This led to the creation of data ecosystems, which facilitate creating, consuming, managing and exchanging data for varying purposes and actors. However, when setting-up such an ecosystem, knowledge on what the requirements of the ecosystem should be in order to get (the most) economic value out of its data is still limited. There is a need for support in the decision processes that come with designing a data driven ecosystem. In order to fill this gap, a taxonomy is being made of the different types of ecosystems there (can) exist, in a parameterized manner. These (discrete) parameters should provide a clear overview of the defining characteristics of data driven ecosystems. Once these parameters are established, a crucial next step in this taxonomy analysis is to identify the most feasible ways value can be created by mapping value creation methods to parameter values. This should allow data ecosystems to be designed according to value creation needs. Additionally, existing ecosystems could be analysed in order to discover missed potential value, or even reveal the need for a strategy change.