Applying the FAIR Principles to computational workflows.

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative’s FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows.

A Linked Science Investigation: Enhancing Climate Change Data Discovery with Semantic Technologies.

is the practice of inter-connecting scientific assets by publishing, sharing and linking scientific data and processes in end-to-end loosely coupled workflows that allow the sharing and re-use of scientific data. Much of this data does not live in the cloud or on the Web, but rather in multi-institutional data centers that provide tools and add value through quality assurance, validation, curation, dissemination, and analysis of the data. In this paper, we make the case for the use of scientific scenarios in Linked Science.

Linking human anatomy to knowledge bases: a visual front end for electronic medical records.

A new concept of a visual electronic medical record is presented based on developments ongoing in the Defense Advanced Research Projects Agency Virtual Soldier Project. This new concept is based on the holographic medical electronic representation (Holomer) and on data formats being developed to support this. The Holomer is being developed in two different visualization environments, one of which is suitable for prototyping the visual electronic medical record.