With the development of new experimental technologies, biologists are faced with an
avalanche of data to be computationally analyzed for scientific advancements and …

Reproducible computational research (RCR) is the keystone of the scientific method for in
silico analyses, packaging the transformation of raw data to published results. In addition to …

Provenance refers to any information describing the production process of an end product,
which can be anything from a piece of digital data to a physical object. While this survey …

The act of sharing scientific knowledge is rapidly evolving away from traditional articles and
presentations to the delivery of executable objects that integrate the data and computational …

Accountability is widely understood as a goal for well governed computer systems, and is a
sought-after value in many governance contexts. But how can it be achieved? Recent work …

Computational workflows describe the complex multi-step methods that are used for data
collection, data preparation, analytics, predictive modelling, and simulation that lead to new …

Data processing pipelines that are designed to clean, transform and alter data in preparation
for learning predictive models, have an impact on those models' accuracy and performance …

There has recently been a lot of ongoing research in the areas of fairness, bias and
explainability of machine learning (ML) models due to the self-evident or regulatory …

Abstract Machine learning (ML) is increasingly used to automate impactful decisions, and
the risks arising from this widespread use are garnering attention from policy makers …

We present noWorkflow, an open-source tool that systematically and transparently collects
provenance from Python scripts, including data about the script execution and how the script …