Taverna has been applied to document the quality of e-Science information by the Qurator project.
The Qurator project aimed to develop and test tools to discover and document the quality of e-Science information.
The tools were developed in close collaboration with user-scientists, with the long term goal of providing generic information quality support in e-Science.
The Qurator project developed an information quality management workbench that supports data experts in the specification, rapid deployment and testing of personal quality hypotheses for specific types of data. This is achieved by providing a declarative model and language for the definition of users’ hypotheses, called “quality views”, and a compilation of views into executable components that can be embedded in a user’s data processing application. Quality views are described in terms of an extensible semantic model for Information Quality.
The Qurator workbench compiles quality views into Taverna workflows, effectively creating reusable quality sub-workflows that can be integrated into a host workflow during a deployment step.
The paper Managing information quality in e-science: the qurator workbench by Missier et al, describes the Qurator workbench.