Lukasz Grus

Spatial data infrastructures as complex adaptive systems

Many researchers throughout the world have been struggling to better understand and describe spatial data infrastructures (SDIs). Our knowledge of the real forces and mechanisms behind SDIs is still very limited. The reason for this difficulty might lie in the complex, dynamic and multifaceted nature of SDIs. To evaluate the functioning and effects of SDIs we must have a proper theory and understanding of their nature. This article describes a new approach to understanding SDIs by looking at them through the lens of complex adaptive systems (CASs). CASs are frequently described by the following features and behaviours: complexity, components, self-organization, openness, unpredictability, nonlinearity and adaptability, scale-independence, existence of feedback loop mechanism and sensitivity to initial conditions. In this article both CAS and SDI features are presented, examined and compared using three National SDI case studies from the Netherlands, Australia and Poland. These three National SDIs were carefully analysed to identify CAS features and behaviours. In addition, an Internet survey of SDI experts was carried out to gauge the degree to which they consider SDIs and CASs to be similar. This explorative study provides evidence that to a certain extent SDIs can be viewed as CASs because they have many features in common and behave in a similar way. Studying SDIs as CASs has significant implications for our understanding of SDIs. It will help us to identify and better understand the key factors and conditions for SDI functioning. Assuming that SDIs behave much like CASs, this also has implications for their assessment: assessment techniques typical for linear and predictable systems may not be valid for complex and adaptive systems. This implies that future studies on the development of an SDI assessment framework must consider the complex and adaptive nature of SDIs.

An assessment view to evaluate whether Spatial Data Infrastructures meet their goals

The motives for constructing Spatial Data Infrastructures (SDIs) are often based on their anticipated benefits for society, economy, and environment. According to those widely articulated but rarely proven benefits, SDI coordinators have been defining more specific objectives to be achieved by their SDIs. However, there is a limited number of assessment approaches that are able to demonstrate whether SDIs indeed realize the intended goals. In this article we develop, apply and evaluate an assessment view for evaluating the extent to which SDIs realize their goals. The assessment view has been developed stepwise using the Multi-view SDI assessment framework as a guideline. The application of the proposed view in the Dutch SDI demonstrates its potential. In addition, the evaluation of the proposed view by the potential users confirms to a certain extent its usability. The results also show that the ease of determining assessment indicators depends on the precision with which the SDI goals are formulated.

Evaluating the application of the multi-view spatial data infrastructure assessment framework

As a response to the growing interest in assessing Spatial Data Infrastructures (SDIs) the Multi-view SDI assessment framework has been proposed. The Multi-view SDI assessment framework collects multiple assessment approaches and methods with the aim to assess many different aspects of SDI in a comprehensive and unbiased way. Despite the potential strengths of the framework, its complex design raises concerns about its usability and applicability for SDI assessment. In this article we evaluate the application of the Multi-view SDI assessment framework. In addition, we ask the potential users of the framework to evaluate its applicability to assess SDIs. The results show that the framework could be applied to 21 National SDIs. Evaluation of the application process reveals that the completeness of assessment data and time needed to measure indicators depends strongly on the assessment methods used. It is recommended to use those methods that need less time to measure assessment indicators. The results also show that a significant part of the measurements could not be done due to survey questions not being filled in by the respondents. The results also show that the users tend to agree with the applicability of the Multi-view SDI assessment framework to assess SDIs.