The document discusses the role of automation in accelerating scientific discovery. It outlines how automation has evolved from early mechanized devices to modern digital technologies. The current state of research still involves heavy manual work, but building a "digital overlay" that captures metadata can enable more intelligent automation. This would allow machines to automate routine tasks, freeing researchers to focus on higher-level work and gaining insights at a lower cost.

1. New Frontiers in Data
Science – the role of
automation in
accelerating scientific
discovery
Georges Heiter
BioData Congress, 4th Dec 2019

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AUTOMATION

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Foundation Technology Maturity Cycle
Insular Divergent Standardized Ubiquitous

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Mechanized Automation
18001739
Digesting Duck Automation
Jacques de Vaucanson (French)
WOW, he made this!
Draughtsman-Writer Automation
Henri Maillardet (Swiss)
1837
Programmable Computer
Charles Babbage (English)

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The steam engine enabled automation and mass production of goods
18021712
Atmospheric Engine
Thomas Newcomen (English)
Locomotive Steam Engine
Richard Trevithick (English)
transportation
Voilà!
1870

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Electricity brought automation into the mainstream
19301870
commercial power
generation was established
Now
>600 quadrillion
BTUs used
globally powering
almost everything
we do today
widespread adoption took until the 1930s, with electric
illumination and other electric appliances becoming common place
in households
Electrical Appliances
❖ Promised to be more efficient
❖ Less time consuming
❖ More manageable than servants
❖ Were called electrical servants

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Internet
19861969
ARPANET become
functional
1989 1995
NSF connects
NSFnet to
ARPANET and
becomes known
as the internet
TCP/IP
World wide web
created
Age of eCommerce
and social media has
begun
Now
Today more than
4.5 billion people
are online

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From steam to cyber, resulting automation impacts shape civilization
Electricity /
Oil / Gas
Energy abundance
Mass Production
Globalization of
Supply and Demand
Mechanization /
Steam Power
Mobility / Transportation
Mechanized Production
Factory Workers
Electronics /
Robotics / Internet
Online Services
Automated and
individualized on-
demand production
Labor Arbitrage
Foundation Automation Impact

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What’s next?
Foundation Outcome Impact
Digitalization Convergence between
physical and virtual
Teams of Human and
Machine Workers

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So where are we today?
Insular Divergent
?

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Humans are manually involved in every step of the research process
Bulk of energy is still spent on finding and preparing data for analysis
Metadata about digital assets and the operations upon them is mostly not being
captured
→ research not easily repeatable or automatable

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Digital Overlay

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The digital overlay is required for the machine actionable network
Enabling fabric

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Page ▪ 14
Knowledge network built from data and metadata is key to unlocking digital potential

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Databiology Approach
Federated Data Management
Knowledge Engine
App
1
App
n
App
2
Source
1
Source
2
Source
n
Process Orchestration
INFRASTRUCTURE
DATA
APPLICATIONS
PEOPLE,ORGS&POLICIES
Orchestration
Engine
Compute Site
Input Data
Application

16. Contextually Aware
Research Assistant
Delivers Intelligent Automation
Automatically routes to
and executes analysis
on the most suitable
infrastructure
Automatically extracts
insights and feeds them
back into the
knowledge network
Recognizes and suggests
analysis apps based on
contextual data
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Digital Research Environments
Data Commons
Digital Clinical Trials Platform
Patient Data Gateway
Metadata Management
Data Interoperation Platform
Intelligent Automation
Digital
Science
Digital
Foundation
Digital
Health

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What will the evolution of digitalization, mean for you?
How researchers spend their time
Design / Develop / DiscoverFind + Prepare Data Run Analysis
Today Future
Manual Intelligent Automation

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Automation will free researchers to focus on higher level tasks
Machines will take over manual labor intensive functions to allow researchers to focus on ideation and creativity
for LOWER COST PER INSIGHT

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SO WHAT?
BECAUSE IT IMPACTS YOU!
OR