Verified data quality is a prerequisite for the reusability of data in all areas of application. Concentrating on the agrosystem domain, we identified relevant metrics to describe the data quality along the whole data life cycle. Based on these metrics, we are building an interactive interface that supports both data providers and users in analyzing and improving the quality of data sets. As a mathematical framework, we develop flexible algorithms that we collate in an algorithmic suite for data curation, which aims at an automatic detection, quantification and resolution of certain quality problems. To communicate certain quality measures, we are focusing on appropriate representations of quality-related data annotations, which will become accessible and editable through the user interface.