Computational Research Infrastructure for Science Now Open-Source
Writer(s): Kristyn Childres
The Computational Research Infrastructure for Science (CRIS), developed at Purdue under the technical leadership of Peter Baker and the scientific supervision of Professor Elisa Bertino, is now available as open source.
Bertino said, “Today’s scientists must conduct relevant, verifiable research in a rapidly changing collaborative landscape, with an ever-increasing scale of data. It has come to a point where research activities cannot scale at the rate required without improved cyberinfrastructure (CI).”
Developed to address these challenges, CRIS provides an easy to use, scalable and collaborative scientific data management and workflow cyberinfrastructure. CRIS offers:
- semantic definition of scientific data using domain vocabularies
- embedded provenance for all levels of research activity (data, workflows, tools, etc.)
- easy integration of existing heterogeneous data and computational tools on local or remote computers
- automatic data quality monitoring for syntactic and domain standards
- shareable yet secure access to research data, computational tools and equipment
CRIS has been used in several different areas of research at Purdue, including agronomy, biochemistry, bioinformatics and healthcare engineering. Bertino said, “The CRIS architecture has been designed based on an extensive requirement analysis carried out in collaboration with colleagues from several colleges at Purdue. I feel confident that CRIS well meets the data management needs of scientific research.”
Download CRIS at https://github.com/crisscience/cris.