An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

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eXascale Infolab

Conference talk at ISWC 2011 for the award winning outrageous ideas track, October 2011, Bonn, Germany

Tecnología Educación

An
Integrated
Socio-‐Technical

Crowdsourcing
Pla8orm
for

Accelera;ng
Returns
in
eScience

Karl
Aberer,
Alexey
Boyarsky,

Philippe
Cudré-‐Maurox,
Gianluca

Demar-ni,
and
Oleg
Ruchayskiy

Science

Yesterday
Today

GiIed
Individuals
Collabora;ve
Eﬀort

OPERA
Collabora;on

Scien;st-‐Computer
Symbiosis

•  A
single
scien;st
has
no
more
the
capacity
to

process
all
the
informa;on

– High
complexity
of
systems
and
workﬂows

– Various
ﬁelds
of
exper;se
involved

•  New
discoveries
will
emerge
from

community-‐based
socio-‐technical
systems

Community-‐based
Socio-‐technical
Systems

•  Such
pla8orms
will
be
useful

– Locally
to
the
scien;st

– By
extrac;ng
knowledge
used
globally

•  They
will
enable
cross-‐pollina;on

– All
ar;facts
need
to
be
interoperable

– Higher
order
logic
to
combine
them

Science

Tomorrow

Collec;ve
Intelligence

What
do
we
need?

•  Highly-‐expressive
machine-‐readable
formats

– Ontologies
of
unprecedented
quality

– Implicit
knowledge
available
in
the
head
of
the

experts

•  Understanding
concepts,
assump;ons,

phenomena,
abstrac;ons

•  Create
a
mental
map
of
a
research
ﬁeld

•  Understand
analysis
methods

A
Giant
Crowdsourcing

Conceptualiza;on
Machine

Towards
Self-‐Awareness

•  A
Scien;fic
infrastructure

– Complex
ontological
networks

– Capture
the
scien;fic
process

– Automate
rou;ne
opera;ons

– Share
scien;fic
ar;facts

•  Experts
will
train
the
system
with
their
daily

ac;vi;es

An
“entropy-‐reduc;on”
machine

•  Relate
en;;es

•  Provide
lineage
informa;on

•  Discriminate
conﬂic;ng
informa;on

•  Reason
and
infer
new
data

The
Web:
a
Collec;ve
Intelligence
engine

•  Informa;on
systems
are
not
instruments

•  A
catalyst
for
the
scien;ﬁc
progress

•  Reason
and
combine
scien;ﬁc
ar;facts
at
very

large
scale

•  Individual
scien;st
will
not
be
able
to
fully

appreciate
models
and
methods

Scien;ﬁc
progress

Time

Now

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In this session, we will delve into strategic approaches for optimizing knowledge management within Microsoft 365, amidst the evolving landscape of Copilot. From leveraging automatic metadata classification and permission governance with SharePoint Premium, to unlocking Viva Engage for the cultivation of knowledge and communities, you will gain actionable insights to bolster your organization's knowledge-sharing initiatives. In this session, we will also explore how to facilitate solutions to enable your employees to find answers and expertise within Microsoft 365. You will leave equipped with practical techniques and a deeper understanding of how there is more to effective knowledge management than just enabling Copilot, but building actual solutions to prepare the knowledge that Copilot and your employees can use.

Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...

Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...

Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...

GenAI Risks & Security Meetup 01052024.pdf

GenAI Risks & Security Meetup 01052024.pdf

GenAI Risks & Security Meetup 01052024.pdf

MySQL Webinar, presented on the 25th of April, 2024. Summary: MySQL solutions enable the deployment of diverse Database Architectures tailored to specific needs, including High Availability, Disaster Recovery, and Read Scale-Out. With MySQL Shell's AdminAPI, administrators can seamlessly set up, manage, and monitor these solutions, ensuring efficiency and ease of use in their administration. MySQL Router, on the other hand, provides transparent routing from the application traffic to the backend servers in the architectures, requiring minimal configuration. Completely built in-house and supported by Oracle, these solutions have been adopted by enterprises of all sizes for their business-critical applications. In this presentation, we'll delve into various database architecture solutions to help you choose the right one based on your business requirements. Focusing on technical details and the latest features to maximize the potential of these solutions.

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

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Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving

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Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

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Tata AIG General Insurance Company - Insurer Innovation Award 2024

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TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery

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2024: Domino Containers - The Next Step. News from the Domino Container commu...

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HTML Injection Attacks: Impact and Mitigation Strategies

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Exploring the Future Potential of AI-Enabled Smartphone Processors

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Data Cloud, More than a CDP by Matt Robison

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Boost PC performance: How more available memory can improve productivity

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GenAI Risks & Security Meetup 01052024.pdf

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Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...

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An Integrated Socio/Technical Crowdsourcing Platform for Accelerating Returns in eScience

1. An Integrated Socio-‐Technical Crowdsourcing Pla8orm for Accelera;ng Returns in eScience Karl Aberer, Alexey Boyarsky, Philippe Cudré-‐Maurox, Gianluca Demar-ni, and Oleg Ruchayskiy

2. Science Yesterday Today GiIed Individuals Collabora;ve Eﬀort

3. OPERA Collabora;on

4. Scien;st-‐Computer Symbiosis •  A single scien;st has no more the capacity to process all the informa;on – High complexity of systems and workﬂows – Various ﬁelds of exper;se involved •  New discoveries will emerge from community-‐based socio-‐technical systems

5. Community-‐based Socio-‐technical Systems •  Such pla8orms will be useful – Locally to the scien;st – By extrac;ng knowledge used globally •  They will enable cross-‐pollina;on – All ar;facts need to be interoperable – Higher order logic to combine them

6. Science Tomorrow Collec;ve Intelligence

7. What do we need? •  Highly-‐expressive machine-‐readable formats – Ontologies of unprecedented quality – Implicit knowledge available in the head of the experts •  Understanding concepts, assump;ons, phenomena, abstrac;ons •  Create a mental map of a research ﬁeld •  Understand analysis methods

8. A Giant Crowdsourcing Conceptualiza;on Machine

9. Towards Self-‐Awareness •  A Scien;fic infrastructure – Complex ontological networks – Capture the scien;fic process – Automate rou;ne opera;ons – Share scien;fic ar;facts •  Experts will train the system with their daily ac;vi;es

10. An “entropy-‐reduc;on” machine •  Relate en;;es •  Provide lineage informa;on •  Discriminate conﬂic;ng informa;on •  Reason and infer new data

11. The Web: a Collec;ve Intelligence engine •  Informa;on systems are not instruments •  A catalyst for the scien;ﬁc progress •  Reason and combine scien;ﬁc ar;facts at very large scale •  Individual scien;st will not be able to fully appreciate models and methods

12. Scien;ﬁc progress Time Now