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A Library Love Triangle? An analysis of the relationship between data, information and knowledge ine Library and Information Studies - James Atkinson
1. A Library Love Triangle? : An analysis of the relationship between
data, information and knowledge in Library and Information Studies
(or, Pullman’s Dust : A new model for data, information and
knowledge).
James Atkinson
City, University of London (MSc Library Science and Information Assistant)
@jamesatkinson81 / james.Atkinson.1@city.ac.uk
2. What I shall be covering today
■Why?
■Findings: Definitions, Models, Points of
Agreement and Disagreement
■The Relationship within Information Literacy
■My Own Model
■Conclusions
4. Issues
■Knowledge merely an end product of
using information?
■Are ideas too reliant on other
disciplines?
■Surely LIS must have an answer!
5. The Three Definitions of Data
■Ancient: From the Latin word datum – “the given”
■Modern: anything fed into a computer (Machlup 1983)
■Future: Datasets – will Shera’s quote (prophecy) become
yet truer?
6. The Multitude Definitions of Information
iSquares showing
Information
represented as
books (Hartel 2014)
■communication
■physical
■non-physical
■sign
■signal
■human phenomenon
■common to all creatures
■discipline-free
7. The Multitude Definitions of Information
“Information mean news or facts about something.”
Cookie Monster (Losee 1997 and MarshalGrover 2008)
8. The Different Definitions of Knowledge
■Personal or Held across society?
■Physical or Just In Our Heads?
■A human construction?
■Importance of Context
■Importance of Understanding
“What is knowledge?
The question sounds simple, but the
answer is difficult.”
Qvortrup (2006)
9. Relationships between Data, Information and Knowledge:
Linear Views
Above: A Representation of
Shannon’s Ideas (Shannon and
Weaver 1949/1969)
[see also: H = -Σ p(i) log p(i)]
Bertie Brookes’ Fundamental Equation of
Information Science:
K[S] + ∆ I = K[S+ ∆S]
Left: The DIKW hierarchy
shown as a pyramid
(Rowley 2007)
10. Relationships between Data, Information and Knowledge:
More Complex Views
Above: Brookes’ Information-
Knowledge Relationship
from Todd (1999)
Left: Information
passing between a
sender and receiver
(Farradane 1980)
11. Relationships between Data, Information and Knowledge:
More Complex Views
Thellefsen, Sørensen and Thellefsen (2014)
12. Other Discussion Points
■D-I-K is a process, but how does it work?
■The Importance (or Otherwise) of Truth
■Where should knowledge be?
■Computers vs Humans
■Work from other disciplines, or is everyone only in it for
themselves?
14. Data-Information-Knowledge within LIS Fields
“Information Literacy is defined as the ability to know when
there is a need for information, to be able to identify, locate,
evaluate, and effectively use that information for the issue or
problem at hand.”
- American Library Association (1989
from Bawden and Robionson 2012)
16. My Own Model
Pullman’s Dust
“Dust is only a name for what happens when matter
understands itself. Matter loves matter.
It seeks to know more about itself, and Dust is formed.”
Balthamos in The Amber Spyglass (Pullman 2000/2011)
18. My Own Model
“Knowledge and information are separate but interacting
entities; we transform one into the other constantly… the
transformation of information into knowledge and knowledge
into information, forms the basis for all human learning and
communication.”
Elizabeth Orna (from Bawden 2001)
19. Conclusions
“As was concluded in a previous essay on Information Theory
(Atkinson 2014), this will be a never-ending debate. “An
exploration of information runs into immediate difficulties,”
said Buckland (1991) and the same is true of its relationship
with data and knowledge.
However, we can try, and we must, to get closer to the truth.”
Atkinson (2016)
20. References
For references, see full dissertation at:
https://docs.google.com/document/d/17SsEWGCyTSxda3pfN
BO_T6_TcvkTPRd1f6lEvyeYyqg/edit?usp=sharing
22. City, University of London
Northampton Square
London
EC1V 0HB
United Kingdom
T: +44 (0)20 7040 5060
E: department@city.ac.uk
www.city.ac.uk/department