The NIH data landscape comprises an estimated 650 petabytes of data, with 20 petabytes residing in NCBI/NLM and significant growth expected in genotyping. A vast majority of published data remains unarchived, leading to challenges in managing the research data lifecycle across diverse types, including genomic data and patient information. The document outlines a collaborative virtual commons for data sharing that emphasizes compliance with FAIR principles to enhance cost-effectiveness and productivity in research.

1. The NIH Data Landscape
• Total data currently in the intramural and
extramural communities is est at 650 PB
• 20 PB of that is in NCBI/NLM(.3%) and it is
expected to grow by 10 PB this year with
genotyping most significant
• 12% of data described in published papers is in
recognized archives – 88% is dark data
• In the 8 years 2007-2014 we spent $1.2Bn on
those archives
• Grappling to understand the research data
lifecycle

2. Example Data Types
• From Molecules to Populations
– Longitudinal patient data e.g. Framingham
– The Cancer Genome Atlas TCGA – genomic
changes in the over 200 types and many more
subtypes of cancer
– The human microbiome – microbes more
numerous than human cells of which there are
37.2 trillion

3. BD2K
• 110M per year research project
– 20% on training
– Standards coordination
– Sustainability
– New developments applied to biomedical
problems
• Compression
• Visualization
• Data wrangling
• Privacy

4. The Commons
• A virtual collaborative space physically
instantiated on public clouds which agree to be
Commons compliant
• Content – data, software, narative etc are
research objects within that space with unique
identifiers and metadata of varying degrees
• Commons compliant means
– They conform to the FAIR principles
• E.g. Find – have early stage indexing engine – Biocaddie
• Like Vegas – what happens in the Commons stays
in the Commons and is shared

5. Implications
• Potentially more cost effective
• Potentially increases productivity
• Credits model
– Driving competition into the market place
– Only pay for what is used
• Know what is being used when
• Can make informed decisions re sustaining
data