2. Our Vision: Data, computing, and
identity services at unlimited scale
3. Historical Perspective
In similarly audacious projects
(Human Genome Project,
HapMap, ENCODE, TCGA, …)
… Information technology been
a critical enabler …
… It has also been a regular
source of tension, frustration,
and unexpected expense…
A “Cray 2” supercomputer on display
at the national cryptographic
museum. This model of system were
the fastest computers in the world
until 1990. By one measure of raw
performance, the Cray 2 is
comparable to a single iPhone
4. 2018 Enablers
Machine learning / AI
• Many real-world examples
• Domain expertise still matters
• No free lunch
Blockchain
• Enables trust without a central authority
• Most data should never be “on-chain”
• Try to see past the cryptocurrency hype
• Does not change “everything”
Devops / SRE / Agile Design
• Progress in how we build robust, scalable
digital technologies within scientific R&D
• Still challenging to get right
• Doubly so in academic environments
A 100Gb/sec uplink
connects Manhattan
institutions to a high
performance research and
engineering network.
5. 2018 Challenge / Focus Areas
Identity and Authorization
• Need flexibility / simplicity
• Without sacrificing trust and accountability
Information security, privacy, and appropriate
usage
• Effective governance for GDPR / HIPAA /
other compliance
• Practical InfoSec
• Clear chain of custody / ownership for
commercialization
Data gravity, cloud skew
• There is no single best provider for data
storage and computing.
• Cloud providers impose both technical and
financial lock-in.
• We must plan for a multi-cloud environment.
Even in 2018, some labs
still use FedEx as a high
throughput, high latency
data transfer protocol
6. Working Group:
Jason Bobe Personal Genomes
Brian Bot Sage Bionetworks
Jack Collins Frederick National Laboratory
Chris Dwan* Bridgeplate
Nancy Kelley NJK Associates
Amy Schwartz NJK Associates
Nam Pho NYU Langone Health
Bruce Wilson Oak Ridge National Laboratory
*: Chairperson