Spatial Data Quality: What do you mean?

Spatial data quality has been on the scientific agenda for a long time. Not at a priority spot, because it is a complex and not a sexy issue. However, we think that is going to change rapidly. The data explosion along with the open data policies is increasing data availability. There is finally a choice in what data to use, but how to make that choice? We see potential for spatial data quality as a selection criterion, but for it to reach its full potential more attention is needed to subjects such as determining spatial data quality, validation, communication and business case development. In this paper we focus on the determination and communication of spatial data from a consumers as well as a producers perspective. We developed a framework in which we define different roles (consumer, producer and intermediary) and differentiate product specifications from quality specifications. We used case studies to illustrate our framework. This framework is designed following the fitness for use principle. It helps to understand the differences between producers and consumers and hence the difficulties they encounter when communicating spatial data quality. We list recommendations to improve the communication about spatial data quality between consumers, intermediaries and producers in order to improve use of spatial data and avoid capital mistakes.