This article surveys existing vocabularies, ontologies and policy languages that can be used
to represent informational items referenced in GDPR rights and obligations, such as the …

Recording the provenance of scientific computation results is key to the support of
traceability, reproducibility and quality assessment of data products. Several data models …

Workflow technology continues to play an important role as a means for specifying and
enacting computational experiments in modern science. Reusing and re-purposing …

In this work, we develop a derived information framework to semantically annotate how a
piece of information can be obtained from others in a dynamic knowledge graph. We encode …

With digital transformation, industrial companies today are facing the challenges to change
and innovate their business, by leveraging digital technologies and tools to support their …

To realise accountable AI systems, different types of information from a range of sources
need to be recorded throughout the system life cycle. We argue that knowledge graphs can …

Reproducibility is one of the core dimensions that concur to deliver Trustworthy Artificial
Intelligence. Broadly speaking, reproducibility can be defined as the possibility to reproduce …

PROV-TEMPLATEIS a declarative approach that enables designers and programmers to
design and generate provenance compatible with the PROV standard of the World Wide …

With the rapid growth of data science and machine learning, interactive notebooks have
gained widespread adoption among scientists across all disciplines to publish their …

Scientific workflows are increasingly used to manage and share scientific computations and
methods to analyze data. A variety of systems have been developed that store the workflows …