information and information structures
David E. Wojick
dwojick at HUGHES.NET
Mon Apr 9 12:50:27 EDT 2007
Dear Loet,
I will look into this with interest. For my part, I agree that most
of the information structures I am talking about can be represented
as matrices, although I prefer to visualize them as linear, tree-like
or network-like arrays, depending on the case. Each structure is
defined by some relation or set of relations among the pieces of
information. So far so good.
Given my definition of information, each piece of information is
theoretically an atomic proposition. However, since the number of
atomic propositions in a sentence is typically roughly equal to half
the number of words, we usually work at a courser scale. Pieces of
information may be sentences, whole documents, or even collections of
documents.
As I explain, pieces of information can be related according to their
propositions, their physical expressions, their referents (what the
propositions are about), or a combination. For any given body of
information there will usually be a large number of important
relation types, so there are in fact many matirices of interest. And
yes many of these change over time. In this context the matrices all
exist, whether we know it or not. That is, how the information is
related is a fact about the information, independent of our analysis.
Important relations (or matrices) in common use range from
alphabetical order applied to some aspect of the expression, to the
so-called topic, which is usually an aspect of what the information
is about. Many popular categorization schemes merge and confuse what
are actually different relations.
Probability does not enter into it so far as I can tell, so I am
interested how this may relate to your matrices? Perhaps that has to
do with the change over time?
Best wishes, David
Dear David,
In reaction to your paper entitled "Outline of a new model of
information contents and structure," let me shortly react.
I would be inclined to think about information and information
structures in terms of the dimensionality of the probability
distribution. For example, a structure requires a network and thus a
two-dimensional matrix can contain this information. An information
system would additionally require that the structure is extended
along the time axis and this would lead to matrices at each moment of
time and thus a three-dimensional cube of information would be
required. Unstructured information can be considered as a vector. One
can extend beyond a three-dimensional array towards a hyper-cube of
information.
In <http://www.leydesdorff.net/evolcomm/index.htm>The Evolution of
Communication Systems, Int. J. Systems Research and Information
Science 6 (1994) 219-30. I elaborated this scheme as follows:
Table I Organization of concepts in relation to degrees of freedom in
the probability distribution
first second third
fourth
dimension dimension dimension dimension
operation variation selection stabilization
self-organization
nature entropy; extension; localized
identity or
disturbance network trajectory regime
character probabilistic; deterministic; reflexive; globally
of uncertain structural reconstructiv organized;
operation resilient
appearance instantaneous spatial; historically
hyper-cycle in
and volatile multi-variate contingent space and time
unit of change in latent stabilities virtual
observation terms of positions during
expectations
relations history
type of descriptive multi-variate time-series non-linear
analysis registration analysis analysis dynamics
The complexity of the declared information system (the data) thus
determines the type of analysis which is possible. (In my book The
Sociology of Communication (2003), this scheme is discussed on pp. 99
ff.)
With best wishes,
Loet
Loet Leydesdorff
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam
Tel.: +31-20- 525 6598; fax: +31-20- 525 3681
<mailto:loet at leydesdorff.net>loet at leydesdorff.net ;
<http://www.leydesdorff.net/>http://www.leydesdorff.net/
From: ASIS&T Special Interest Group on Metrics
[mailto:SIGMETRICS at listserv.utk.edu] On Behalf Of David E. Wojick
Sent: Sunday, April 08, 2007 7:12 PM
To: SIGMETRICS at listserv.utk.edu
Subject: Re: [SIGMETRICS] The communication of meaning in social
systems; preprint version available
Dear Loet,
It is delightful to get something like this on a holiday. I take it
this is what the phenomenology of meaning looks like these days. Not
that I pretend to understand phenomenology, so please correct me if I
am wrong. I also take it that the interpretation of the parameters in
the very interesting equations, as well as the technical concepts
being used, is to be found in the cited references.
Since I have also presented a theory of the nature of information
here, I thought it appropriate that I speculate upon the difference
between this body of work and my own.
CF:
http://www.bydesign.com/powervision/Mathematics_Philosophy_Science/information.html
My work derives from the tradition of analytical philosophy and
mathematical logic begun by Russell and Wittgenstein. I suggest that
it is looking at meaning in a very narrow sense, as exemplified by
the atomic proposition. The phenomenological tradition is looking at
meaning in a very broad sense, what it is to be meaningful if you
like.
The human condition is rich enough to accommodate both approaches and
so I do not see any disagreement here between us. The question is if
there is any connection?
Best regards,
David
<http://www.leydesdorff.net/meaning0704/index.htm>The communication
of meaning in social systems
<http://www.leydesdorff.net/meaning0704/meaning0704.pdf> pdf-version
Abstract
The sociological domain is different from the psychological one
insofar as meaning can be communicated at the supra-individual level
(Schütz, 1932; Luhmann, 1984). The computation of anticipatory
systems enables us to distinguish between these domains in terms of
weakly and strongly anticipatory systems with a structural coupling
between them (Maturana, 1978). Anticipatory systems have been defined
as systems which entertain models of themselves (Rosen, 1984). The
model provides meaning to the modeled system from the perspective of
hindsight, that is, by advancing along the time axis towards possible
future states. Strongly anticipatory systems construct their own
future states (Dubois, 1998a and b). The dynamics of weak and strong
anticipations can be simulated as incursion and hyper-incursion,
respectively. Hyper-incursion generates “horizons of meaning”
(Husserl, 1929) among which choices have to be made by incursive
agency.
Loet Leydesdorff & Sander Franse
Amsterdam School of Communications Research (ASCoR)
Kloveniersburgwal 48, 1012 CX Amsterdam
Tel.: +31-20- 525 6598; fax: +31-20- 525 3681
<mailto:loet at leydesdorff.net>loet at leydesdorff.net ;
<http://www.leydesdorff.net/>http://www.leydesdorff.net/
Now available:
<http://www.universal-publishers.com/book.php?method=ISBN&book=1581129378>The
Knowledge-Based Economy: Modeled, Measured, Simulated. 385 pp.; US$
18.95
<http://www.universal-publishers.com/book.php?method=ISBN&book=1581126956>The
Self-Organization of the Knowledge-Based Society;
<http://www.universal-publishers.com/book.php?method=ISBN&book=1581126816>The
Challenge of Scientometrics
--
"David E. Wojick, Ph.D." <WojickD at osti.gov>
Senior Consultant -- The DOE Science Accelerator
http://www.osti.gov/innovation/scienceaccelerator.pdf
http://www.osti.gov/innovation/
A strategic initiative of the Office of Scientific and Technical
Information, US Department of Energy
(540) 858-3150
391 Flickertail Lane, Star Tannery, VA 22654 USA
http://www.bydesign.com/powervision/resume.html provides my bio and
client list.
http://www.bydesign.com/powervision/Mathematics_Philosophy_Science/
presents some of my own research on information structure and
dynamics.
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