*A Dialog on the Informational as the 4th Great Domain of Science*
*Moisés André Nisenbaum & Ken Herold*
*/PART 1: /**/Informational as the 4th Great Domain of Science/*
(Moisés André Nisenbaum)
To classify is human (BOWKER & STAR 2000). The organization of
scientific knowledge is concern of scientists long ago. It started as a
matter of librarianship and has evolved over time using various tools
like enumerative classification, faceted classification, universal
classification, controlled vocabulary, thesaurus, ontologies, Semantic
Web. But how Information Science should organize scientific knowledge
taking into account the dynamic behavior of disciplines and multi, inter
and trans-disciplinary science of the twenty-first century (Information
Rosenbloom (2012) proposed a model in which four great Scientific
Domains - Physical (P) Life (L), social (S) and Computing (C) - can be
combined to form any discipline
The first three (P, L and S) are "well known" domains and he proposes
that the 4th is Computing. The small number of domains (compared with 10
of DDC and UDC) is offset by dynamic
between domains that can be written by Metascience Expression Language
Although the prerequisites of a Great Scientific Domain has been well
developed, Rosenbloom does not explain why they are in number of four or
why these specific four domains.
NAVARRO, MORAL and Marijuan (2013) propose that the 4th Great Scientific
Domain is the Informational (I) instead of Computing. However, the
biggest proposal is that the Information Science needs to be rethought
to support theoretically and methodologically this 4th Great Scientific
Domain. At the end of the article, the authors propose the insertion of
the four Great Scientific Domains
High-Resolution Map of Sciences (Bollen at all, 2009)
The problem is that all this is still in its "philosophical field" and
miss a more pragmatic approach. When I observed this map, I just thought
about how to measure these four domains and, even without even knowing
exactly how to do this, I asked Bollen the raw data of his research. My
initial idea was to identify every scientific discipline by a
mathematical entity, for example a digital 4x4 matrix representing
quantitatively the four Great Scientific Domain components and their
relationships. The problem how to establish the criteria (bibliometric)
that would define the matrix elements. Once created, we can check if the
matrices really come together as expected.
BOWKER, Geoffrey C.; STAR, Susan Leigh. Sorting things out:
Classification and its consequences. MIT press, 2000.
ROSENBLOOM, Paul S. On computing: the fourth great scientific domain.
MIT Press, 2012.
NAVARRO, Jorge; MORAL, Raquel del; MARIJUÁN, Pedro C.. The uprising of
informational: towards a new way of thinking Information Science.
Presented at 1st International Conference in China on the Philosophy of
Information, Xi'an, China, 18 October 2013.
BOLLEN, Johan et al. Clickstream data yields high-resolution maps of
science. PLoS One, v. 4, n. 3, p. e4803, 2009.
PART 2: Comments from Ken Herold/*
I appear to be a fringe observer of the history of information science
from within my professional (since 1984) domain of librarianship and
information studies.  For a broader example, Chaim Zins conducted a
multi-year study of information science internationally from 2003-2005.
 My own edited works  in 2004 and 2015 reprise various works
going back to Machlup from 1962 .
I am somewhat skeptical of the suggestion that recombining knowledge is
new or previously critically not examined. The international
documentation movement, predecessor to information science, has been
shown by Buckland and Rayward  among others to be exactly the rich
response to the global growth of knowledge 100 years ago.
Bioinformatics should and does clarify and extend our perspectives, but
I hesitate to accept its equivalence with von Neumann architecture or
cultural heritage. Nevertheless, all the right questions are being
asked in my opinion.
Rosenbloom's interminable references to Wikipedia are off-putting, I am
afraid. Also, he takes a rather narrow historical view of information
science in chapter 1. Again, the trend seems correct to me as to the
importance of computing. I just do not place as much value on an ad hoc
relational approach with few links to the massive peer-reviewed
I suppose I could best serve as the devil's advocate in this round?
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