Provenance in the context of workflows, both for the data they derive and for their
specification, is an essential component to allow for result reproducibility, sharing, and …

Provenance refers to the entire amount of information, comprising all the elements and their
relationships, that contribute to the existence of a piece of data. The knowledge of …

Provenance, ie, the origin or source of something, is becoming an important concern, since it
offers the means to verify data products, to infer their quality, to analyse the processes that …

Digital provenance is meta-data that describes the ancestry or history of a digital object.
Most work on provenance focuses on how provenance increases the value of data to …

The provenance of data has recently been recognized as central tothe trust one places in
data. It is also important to annotation, todata integration and to probabilistic databases …

As the world is increasingly networked and digitized, the data we store has more and more
frequently been chopped, baked, diced and stewed. In consequence, there is an increasing …

In the last years, scientific workflows have emerged as a fundamental abstraction for
structuring and executing scientific experiments in computational environments. Scientific …

As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an
urgent need to develop scalable and sustainable tools to simplify the process of data …

Loss of life and property, disruptions to transportation and trading operations, etc. caused by
meteorological events increasingly highlight the importance of fast and accurate weather …

cData provenance, or data lineage, describes the life cycle of data. In scientific workflows on
HPC systems, scientists often seek diverse provenance (eg, origins of data products, usage …