In the last decade, the publication of scientific data as a major research output has become more established. However, providing meaningful metadata and related visualizations that facilitate the discovery, interpretation, evaluation and reuse of scientific data is still a pressing challenge. The FAIR data principles address this and provide guidelines to improve the findability, accessibility, interoperability and reusability of scientific data [Wilkenson et al. 2016, Roos et al. 2016]. Providing provenance information is core to ensure the reusability as addressed in "R1.2: (Meta)data are associated with their provenance.", which shows the demand for detailed workflow descriptions.
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Within the GeoKur Project, we develop a provenance concept to evaluate and reduce the complexity of provenance graphs for geospatial datasets. Further details are published here:
We developed an easy to use python package to facilitate provenance tracking. The package enables researchers to create provenance graphs in PROV-O.
The ProvViewer enables the interactive visualization of provenance information for geospatial datasets based on PROV-O. The client can be parameterized with provenance metadata published in triple stores, like FUSEKI.
GeoMetaFacet is a web client to explore and visualize geodata. It focuses on a user-friendly and interactive navigation through the metadata and allows the user to quickly get an overview of available data. Core features of GeoMetaFacet are an interactive data lineage graph and a hierarchy tree, which can be used to evaluate available data.
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