Lightweight data engineering, tools, and software to facilitate data reuse and data science


Lightweight tools, software, and publication processes that tie together data resources, analysis tools, documentation can powerful stimuli for the high-quality reuse of available data. While developed with reproducibility as a core value, Bioconductor tooling and infrastructure has reduced barriers to data reuse and established best practices for rich data and metadata sharing in genomics and proteomics. In this talk, I give a few examples and motivation for how the Bioconductor data ecosystem can be a model for other communities to enhance the value of available data.

May 14, 2019 12:00 AM
Carnegie Mellon University, Pittsburgh, PA
Professor of Medicine

My interests include biomedical data science, open data, genomics, and cancer research.

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