yProv is an open-source software ecosystem to support provenance management within scientific workflows. It relies on the W3C PROV family of standards, a RESTful interface and a graph database back-end based on Neo4J. The yProv web service (main component) is implemented in Python by using the Flask micro-framework which is based on the Jinja2 Template Engine and Werkzeug WSGI Toolkit. The service is domain-agnostic, though its primary case studies in the project come from the climate change domain (i.e. climate analytics workflows). The service aims at implementing the micro-provenance concept, to navigate within the provenance space across different dimensions (e.g., horizontal & vertical). yProv includes also the Command Line Interface and additionally, it delivers support for provenance tracking in AI, which adds extra capabilities in key and recurring use cases across different DTs.
Users can exploit the yProv service to manage (i.e. store, retrieve, explore, visualise) the provenance information associated with scientific datasets, thus getting a better understanding about specific datasets. The value proposition is about (i) stronger traceability, transparency, and trust (through a richer set of metadata) and (ii) multidimensional exploration/navigation of provenance metadata information (i.e., multi-level).
