Abstract
Much of our knowledge about the status of and changes in ecological systems and their response to environmental stresses has originated from ecological monitoring. However, concern exists about the ability of monitoring to provide 'good' data. The value of monitoring is often questioned and monitoring itself is seen as an exercise with little contact with true science. Such concerns are justified given several examples of abuse and misuse of monitoring data and failure in documenting errors and flaws. When data are flawed, even the most sophisticated statistical and modelling technique is useless. As a consequence, there are risks that the environmental policy decision-making process may be severely compromised, leading to wrong decisions and additional costs to society. Data quality is therefore essential for decision quality. However, data quality goes beyond the traditional perception of metrological quality, and the process of obtaining 'good' data needs to consider all the steps involved in the monitoring. Ecological monitoring cannot survive outside a rigorous scientific context, and a comprehensive quality assurance framework is necessary to drive the design and the implementation of a monitoring programme.