Abstract. In Earth System Sciences, a data-driven research domain, several communities discuss the importance, guidance and implementation of making research data findable, accessible, interoperable, and reusable. To foster these principles, in particular to support reusability, users need easy-to-use user interfaces with meaningful visualizations for detailed metainformation, e.g. on dataset’s origin and quality. However, visualization tools to facilitate the evaluation of fitness for use of ESS research data on domainspecific metainformation, do hardly exist.We provide a Geo-dashboard concept for user-friendly interactive and linked visualizations of provenance and quality information using standardized geospatial metadata. A provenance graph visualization serves as overview and entry point for further evaluations. Quality information is essential to evaluate the fitness for use of data. Therefore, we developed quality visualizations on several levels of detail to foster evaluation, e.g. by enabling users to choose and classify quality parameters based on their use-case-specific needs.

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Abstract. Extensive data quality descriptions as a vital part of a dataset’s metadata are widely accepted, albeit their provision in a formalized manner is often lacking. This is due to a number of problems that are frequently encountered by geodata producing scientists. As one of these problems, we identified missing, unknown or unused options to model inhomogeneity of data quality across space, time, and theme in a dataset’s metadata. Detailed information of inhomogeneous geodata quality beyond dataset-wide statistical measures (variance, min, max, etc.) is often only described in dataset accompanying papers or quality reports. These text-based approaches prevent precise querying and hinder the development of advanced data discovery tools that could make valuable use of inhomogeneous data quality information. We propose a profile for the data quality vocabulary (DQV) that allows to model inhomogeneous geodata quality. Considering established vocabularies typically used to describe geographic metadata, as well as ensuring compatibility with the default version of DQV, enhances the usability and thus, minimizes the effort for data producers to provide formalized descriptions of inhomogeneous data quality.

Abstract. In today’s research data management, experts discuss datasets to be FAIR, as they should become findable, accessible, interoperable and reusable (Lacagnia et al. 2021). In recent years, quality information and provenance information as well as dataset’s general metadata have become important aspects to evaluate a dataset's fitness for use. In order to capture and process this meta-information in a systematic way, users need frameworks and meaningful user interfaces that allow them to interact with the information and to visualize them. Therefore, we provide a user-friendly and interactive geodashboard implementation as first prototype that supports the evaluation of spatial datasets with linked widgets by applying semantic concepts and using open source libraries.