With the digital revolution the provision of scientific information is fully entered in a new mode of operation.
The fast advances of technologies is transforming the way of providing information towards scientists and opening new opportunities.
Data and Information storage has moved from a paper-based, manual affair to an activity in which computers are necessary.
As a result, a vast amount of scientific information is being daily produced and collected, a research organization has not enough resources to collect everything.
With emphasizing data-intensive thinking e-Science is moving towards data Intensive technologies and is becoming a new technology driver and requires the re-thinking of infrastructure architecture components, solutions and processes for Scientific Information Provision.
A new systematic approach for tackling the challenges of data-intensive computing, providing scientists and decision makers with practical tools for dealing and exploring the needed data and information.
Similar to IC-SDV 2019: Semantic e-Science - The Future of Information Provision in the Digital Age - Aleksandar Kapisoda (Boehringer Ingelheim, Germany )
Similar to IC-SDV 2019: Semantic e-Science - The Future of Information Provision in the Digital Age - Aleksandar Kapisoda (Boehringer Ingelheim, Germany ) (20)
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IC-SDV 2019: Semantic e-Science - The Future of Information Provision in the Digital Age - Aleksandar Kapisoda (Boehringer Ingelheim, Germany )
1. Semantic e-Science
The Future of Information Provision in the Digital Age
Aleksandar Kapisoda
IC-SDV 2019
France, Nice - 9th April 2019
2. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 2
1895 - we don't live in that kind of world
Paul Otlet
3. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 3
2019 - we do live in that kind of world
Aleksandar Kapisoda
4. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 4
1895 - Universal Information structure
https://s-media-cache-ak0.pinimg.com/736x/7d/71/0f/7d710ffe8ad97234ebc4867546d68a28.jpg
He is one of several people who have been considered the father of
information science, a field he called "documentation".
was imagining his universal information structure by making
'symbolic links' from document to document.
started to think about a system that could represent the multiple
networked relations between objects of various formats with various
objectives.
designed explicitly mapped multiple relations between multi-media
objects
(so not just books) and allowed for constant transformation and
modification.
Paul Otlets vision - The Book of the Books
In 1934, Paul Otlet laid out this vision in
what he called “Radiated Library” vision
5. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 5
2019 - Universal Information Structure
https://s-media-cache-ak0.pinimg.com/736x/7d/71/0f/7d710ffe8ad97234ebc4867546d68a28.jpg
He is one of several people who have been considered the father of
information science, a field he called "documentation".
was imagining his universal information structure by making
'symbolic links' from document to document.
started to think about a system that could represent the multiple
networked relations between objects of various formats with various
objectives.
designed explicitly mapped multiple relations between multi-media
objects
(so not just books) and allowed for constant transformation and
modification.
Paul Otlets vision - The Book of the Books
In 1934, Paul Otlet laid out this vision in
what he called “Radiated Library” vision
Terminologies & Ontologies
Linked Data
Domain Expertise
making 'symbolic links' from
document to document.
World Wide Web
6. Boehringer Ingelheim & Blockchain
6
2018 | 2019 – Technology
https://www.boehringer-ingelheim.ca/en/press-release/boehringer-ingelheim-canada-ltd-and-ibm-canada-announce-first-its-kind-collaboration?
Built Digital Infrastrucure for e-Science
Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda
9. • It describes computationally intensive science, or science requiring new computational
tools to manage massive amounts of heterogeneous, distributed data that must be
efficiently stored, processed, analyzed and visualized.
• eScience enhances science by maximizing the potential scientific output
from literature, patents, databases and data et. through the optimal use/deployment
of emerging technologies and their infrastructures.
• Semantic e-Science is connecting the dots between Data, Ontologies
with BigQuery Data Analytics with Googles engine
Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 9
What is e-Science?
11. • How to manage research data?
• How to transform data to knowledge?
• How to generate knowledge from data?
• How is new knowledge obtained from data?
• How is the knowledge shared and managed?
Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 11
Managing Research Data
12. http://research.microsoft.com/en-us/collaboration/fourthparadigm 12
2009 - The Fourth Paradigm (by Jim Gray)
Experimental
Theoretical
Data Intensive
Computational
Jim Gray (Microsoft):computing is fundamentally transforming the practice of science. He called the shift a "fourth paradigm."
Data-Intensive Scientific Discovery
13. 13
Disovery Research is getting complex
More & Larger data
More details, types, scales
More Bytes
Sophisticated technology
Data analysis no longer possible by “eye”
Involves various experts
More Complex
Fast advances of technologies
Infrastructure
for tackling the challenges of
data-intensive computing
Services
14. 14
Complexity of our Enviroment
is being daily producedand collected, a
research organization has not enough
resources to collect everything.
Result - vast amount of scientific information
is moving towards data Intensive
technologiesand is becominga new
technologydriver and requires the re-
thinking of infrastructure architecture
components, solutions and processes
for Scientific Information Provision.
With emphasizing data-intensive
thinking
for tackling the challenges of data-intensive
computing,providing scientists and decision
makers with practical tools for dealing and
exploring the needed data and information
New systematic approach
of Data and Information storage has moved from
a paper-based, manually affair to an activity in
which computers are necessary.
Disruption
is transforming the way of
providinginformationtowards
scientists and openingnew
opportunities.
Fast advances of technologies
provision of scientific information is
fully entered in a new mode of
operation.
Digital Revolution
15. Personalized Information like Personalized Medicine
The goal of this concept is to make licensed and public
information resources accessible to researchers in a smart and
clear way.
Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 15
Founding Idea – Personlized Information
Platform
16. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 16
Personalizing the UI
describes a single-tiered software
application in which the user interface
and data access code are combined into
a single program from a single platform.
1980
Monolithic Search
Application
are managing this deluge by tailoring the
information
which will be presented to
individual users or user groups.
2018 Information Mart concept of
Boehringer Ingelheim
Personalized
Information Marts
improves search accuracy by
understanding the searcher's intent
and the contextual meaning of terms
as they appear in the searchable
dataspace, to generate more relevant
results.
1990’s
Semantic Search
Application
Information Experts & Trained Scientists Scientists
17. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 17
Recipe for Personalized Information Marts
Queries
Toolbox
Services
through a "toolbox" that allows domain experts to
ask different and complex questions.
Development of a toolbox for
Ad-hoc Analytics
speed up the process
of scientific discovery in
Information Resources
Redefinition of Services
Diversity of Queries & Questions
Tailored Toolbox
18. An ontology based data analytics platform for personalized information
licensed
& open access
Databases, Literature,
Patents, Grants´,
clinical trials…
Diseases, Targets, Biomarker and
many more…
Linking & Connecting
Extracted Concepts with Ontologies
External Information
Resources
Ontologies
Technology: BigQuery Data Analytics with Googles engine
Digital Infrastructure for Smart Data
19. Information Extraction from the Public Domain & Licensed Data Sources
Patents
Normalization
with
Content Annotation
Text Analytics
Entity Recognition
&
Knowledge Extraction
Personalized
With
specific Visualizations
21. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 21
Connecting Researcher to Meaningful Data
Researcher
Insights
from Data
Infrastructures
Techniques
Concepts
Services
connect analysed
22. Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 22
Outcome
Connecting the dots between
Data, Ontologies with
BigQuery Data Analytics with Googles engine
Smart Data
Gaining Insights from Information towards Knowledge
Knowledge
Using art-of-state technology
Big Query and creating a ontology based data analytics platform
Technology
23. Conclusion
• provide
customized information
strictly focused & tailored towards the
information needs of R&D project teams.
• support knowledge discovery
of scientists with pro-actively push project-
”specific” information
• break down data silos
and follow F.A.I.R. principles for external data
with our Knowledge Discovery Solution we
23
24. • S.I.C, TransMed, R&D colleagues
• Dr. Weber – OntoChem
• Dr. Sonja Müller & Klaus Kater – DeepSearch9
Semantic e-Science, France, Nice - 9th April 2019, Aleksandar Kapisoda 24
Acknowledgement