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 …

Scientific research relies as much on the dissemination and exchange of data sets as on the
publication of conclusions. Accurately tracking the lineage (origin and subsequent …

Objective To explore in depth how primary care clinicians (general practitioners and practice
nurses) derive their individual and collective healthcare decisions. Design Ethnographic …

Data management is growing in complexity as large-scale applications take advantage of
the loosely coupled resources brought together by grid middleware and by abundant …

Data provenance describes how data came to be in its present form. It includes data sources
and the transformations that have been applied to them. Data provenance has many uses …

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 …

In many data-driven applications, analysis needs to be performed on scientific information
obtained from several sources and generated by computations on distributed resources …

Data management is growing in complexity as large-scale applications take advantage of
the loosely coupled resources brought together by grid middleware and by abundant …

With the development of information technology, the border of the cyberspace gets much
broader and thus also exposes increasingly more vulnerabilities to attackers. Traditional …

In e-Science experiments, it is vital to record the experimental process for later use such as
in interpreting results, verifying that the correct process took place or tracing where data …