II Konferencja Naukowa : Nauka o informacji (informacja naukowa) w okresie zmian, Warszawa, 15-16.04.2013 r. Instytut Informacji Naukowej i Studiów Bibliologicznych, Uniwersytet Warszawski The 2nd Scientific Conference : Information Science in an Age of Change, April 15-16, 2013. Institute of Information and Book Studies, University of Warsaw

1. 1
The Yotta is not Enough!
The Need for Rethinking Information Science.
Dr Bruno Jacobfeuerborn
Telekom Deutschland GmbH
“Information Science in an Age of Change”, 2nd Conference
Institute for Information Science and Book Studies, University of Warsaw
Warsaw, April 15-16th, 2013

2. Yotta (Y)
=
1024 or 1 000 000 000 000 000 000 000 000
2© B. Jacobfeuerborn

3. Metric Prefixes (ISO)
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4. Dr. Bruno Jacobfeuerborn
- Moved to Deutsche Telekom in 1989.
- Head of Radio and Transmission Department in Hanover , 1991.
- Regional Director in Leipzig, 1991.
- Regional Director Technology and later Regional Director Business, responsible for Sales,
Marketing and Technology, Hanover, 1995.
- T-Mobile; the acquisition of the GSM license in Poland, 1996.
- Technical Director T-Mobile Netherlands and Member of the Management Board, 2002.
- Head of Service Management Europe in the T-Mobile International, 2004.
- Technical Director PTC and Member of the Management Board, 2007.
- Director and Management Board Member responsible for technology (fixed and mobile)
in Germany at Telekom Deutschland GmbH, 2009.
- Invited speaker to international conferences and coach of workshops.
- MOST Foundation General Assembly member.
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5. 5
Contents
─ Prologue
─ Thesis
─ Big Data
─ 4 Paradigms of Science
─ Data Science
─ Epilogue
New Scientific
Paradigm
Big Data
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Prologue.
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7. 7
Data is the raw material of the XXI century.
Credo
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8. 8
Thesis.
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9. 9
A new scientific paradigm emerges.
Information science has to face and cope with it!
Thesis
Source: Cartoonbank.com
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10. 10
Big Data.
© B. Jacobfeuerborn

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“Big data refers to datasets whose size is beyond the
ability of typical database software tools to capture,
store, manage, and analyze”.
--- McKinsey, 2011
Big Data
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13. How Big is Big?
Today: between Exabytes (1018) and Zettabytes (1021)
Tomorrow: over Zettabytes
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14. Big Data – the Flood
Walmart drags a million hourly retail transactions into a database that
long ago passed 2.5 petabytes; Facebook processes 2.5 billion pieces of
content and 500 terabytes of data each day; and Google, whose YouTube
division alone gains 72 hours of new video every minute, accumulates 24
petabytes of data in a single day.
− David Rowan, Editor, WIRED UK,
http://www.edge.org/response-detail/23859
“Each day, according to IBM,
we collectively generate 2.5
quintillion bytes—a tsunami of
structured and unstructured
data that's growing, in IDC's
reckoning, at 60 per cent a
year.
14© B. Jacobfeuerborn

15. 15
Four Paradigms of Science.
© B. Jacobfeuerborn

16. Scientific Revolutions
T.S. Kuhn
1922 - 1996
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Science has been developing
from idea-centricity to data-centricity.
Data leverage ideas!
My Addendum to Kuhn’s Claim
Data
Idea
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18. The School of Athens, Raphael, 1509
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19. 1. Platonic Approach
In the Greek language science means
knowledge. According to Aristotle and
Plato science/knowledge is:
universal, necessary, certain, and
timeless. Deduction is the only
allowed way of reasoning.
Mathematics is a prototype (model) of
science and a language of nature.
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20. 2. Baconian Approach
Francis Bacon’s new methodology of
science and knowledge, empiricism,
that relayed on observation,
collection of data, and experimenting,
along with accepting induction as a
legal inference method for scientific
endeavors can be characterized as
data-centric.
20© B. Jacobfeuerborn
Francis Bacon, 1561 - 1626

21. 3. Computers at Work (Simulation, Modelling)
−J.P. Rini
“The idea is to use a computer program
to perform lengthy computations, and to
provide a proof that the result of these
computations implies the given theorem.
In 1976, the four color theorem was the
first major theorem to be verified using a
computer program.”
http://en.wikipedia.org/wiki/Computer-assisted_proof
21© B. Jacobfeuerborn

22. 22
“It is a capital mistake to
theorize before one has
data.”
− Sherlock Holmes,
A Study in Scarlett
(Arthur Conan Doyle)
The Role of Data
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23. 23
“We can stop looking for models. We
can analyze the data without
hypotheses about what it might show.
We can throw the numbers into the
biggest computing clusters the world
has ever seen and let algorithms find
patterns where science cannot.”
–Chris Anderson
4. Big Data at Work
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24. 24
Data Science.
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Data science is a set of scientific theories, methods, tools, and best
practices (including hacking!) aimed to analyse and explore big
datasets in order to discover hidden knowledge thru inference.
Data Science
source: Data Science: An Introduction,
http://en.wikibooks.org/wiki/Data_Science:_An_Introduction
© B. Jacobfeuerborn
!

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27. 27
My Vision
Information
Science
Data
Science
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− Definitions of data, information, and knowledge.
− Data structures and databases.
− Big data and analytics trends.
− Elements of logics and non-standard inference mechanisms for big data.
− Assorted methods of knowledge representation.
− Elements of machine learning and artificial intelligence.
− Methods of browsing and retrieval of big data, with a focus on methods to fast delivery of the retrieved
hits.
− Methods and tools to create metadata.
− Data integration.
− Deep data analysis: statistics and data mining technologies.
− Architecture of scalable big data systems.
− Cloud computing; methods of physical storage of big data; virtualization technologies for sharing
processing power and memory.
− Security and privacy within big data infrastructures.
− Big data case studies (e.g. social networking, governance, marketing, health).
Data Science Curriculum for Information Science Students
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29. 29
Epilogue.
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30. 30
“With too little data, you won’t be
able to make any conclusions
that you trust. …
Big data isn’t about bits, it’s
about talent.”
–Douglas Merrill
http://www.forbes.com/sites/douglasmerrill/
2012/05/01/r-is-not-enough-for-big-data/
To Remember
© B. Jacobfeuerborn

31. Thank you for listening!