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To facilitate spatial data sharing and exchange, many organisations developed Spatial Data Infrastructures (SDIs). SDIs, also known as geo-information infrastructures, are becoming nowadays more mature worldwide, but are also challenged by new technologies and user demands. Proper SDI governance seems essential, but it is unclear to what extent current SDI governance is fully equipped to deal with the dynamics and complexity of SDIs. The objective of this research is to analyse SDI governance dynamics and to develop tools in order to gain insights in current SDI governance and their possible future.First, two longitudinal SDI case studies were conducted about the governance of large-scale base maps in the Netherlands and Flanders (Belgium). Both initiatives represent decades-long undertakings to create a large-scale base map. We found that SDI governance is adaptive, as it changed considerably during the evolution of these two SDIs. In most cases, the governance approaches of these SDIs did not hold up very long, as they were either not meeting their goals, were not satisfying all stakeholders or were not in alignment with new visions and ideas. Recently, the instruments governing these SDIs have become increasingly diverse. We see especially an increase in hierarchical instruments in these two cases. In general, governance scientists agree that by using a broader mix of policy instruments, governance becomes more adaptive.To gain more insights in SDI governance and the shifts we observed, a framework was developed for evaluating the governing system of SDIs based on the theoretical conceptions of Kooiman (2003). In this framework we distinguish two levels: an actor level, where images are formed, instruments are chosen and applied into action, and a structural level, where the formal and informal structures and resources reside which enable or constrain the actor level. This framework is applied to two Dutch SDI cases: the Risk Map and the New Map of the Netherlands. With the help of the framework, the strong and weak aspects of the governing system of SDIs become apparent and insights emerge on which interactions, images, instruments, actions and structures enable or constrain SDI governance. By observing changes in governing systems over time, dynamics in this system become visible. Therefore, the framework is an useful analytical tool for gaining more insights in SDI governance and its dynamics.Another tool this research developed is an agent-based model for simulating SDI governance interactions. Agent-based modelling is a suitable method for understanding complex emergent behaviour of a system by modelling local interactions of actors. In this agent-based simulation, we examined interactions between SDI stakeholders, data availability, the effects of different governance styles (hierarchical, network and laissez-faire governance) and budget policies. By running different scenarios, it appeared that a network governance approach is more successful compared to a hierarchical or laissez-faire approach. Expert validation showed that overall the results of the simulation are credible and insightful, although improvements can be made to make the model more realistic. With agent-based modelling, SDI governance becomes more tangible and visible. Therefore, it is a helpful tool in facilitating discussion and understanding of SDI governance and their dynamics.Both tools, the agent-based model and the governing system framework, were applied to INSPIRE, the European Spatial Data Infrastructure. INSPIRE is an initiative which enforces European Union (EU) member states to harmonise data on specified themes and provide this data through network services from their national SDI. By using an online survey, the main stakeholders of INSPIRE provided input to evaluate INSPIRE’s governing system. Furthermore, this input is applied in the agent-based model to project future and alternative governance scenarios. The results from the survey show that strong aspects of INSPIRE’s governing system are the supported vision and its formal structures such as standards, technology and roles and responsibilities. Weak aspects are its data use and the access to resources, especially budget and time resources. Simulations ran with the agent-based model also indicate that the current budget policy is constraining INSPIRE’s governance for the future.This research analysed the SDI governance dynamics of several cases. Based on these cases, it is clear that there is no golden recipe for SDI governance. Even if the results are very similar which is in the case of the large-scale base maps, governance trajectories of SDIs can be very different and change over time. Although SDI governance is already adaptive, SDI governance in general may anticipate better on these dynamics in order to improve its adaptive capacity and prevent governance crisis situations. For example, by allowing a mix of self-organising, network and hierarchical governance forms and regularly reviewing the governing system to ensure it is enabling.With the help of the developed tools, the SDI governing system framework and agent-based model, it is possible to get a better understanding of what enables and constrains the dynamic governance processes of SDIs. With the agent-based model, even possible governance futures can be explored. These tools help to provide more insights in the strong and weak aspects of the governance of an particular SDI. It is important to discuss the outcomes from these tools in order to facilitate learning and discussion among SDI practitioners. In this way, SDI governance may become both more flexible and adaptive, while also improving the robustness of its system for unexpected developments. |
