Holistic sense‐making: conflicting opinions, creative ideas, and collective intelligence
| DOI | https://doi.org/10.1108/07378830710820907 |
| Published date | 11 September 2007 |
| Date | 11 September 2007 |
| Pages | 311-327 |
| Author | Chaomei Chen |
| Subject Matter | Information & knowledge management,Library & information science |
THEME ARTICLE
Holistic sense-making: conflicting
opinions, creative ideas, and
collective intelligence
Chaomei Chen
College of Information Science and Technology, Drexel University,
Philadelphia, Pennsylvania, USA
Abstract
Purpose – The purpose of this work is to introduce a generic conceptual and methodological
framework for the study of emergent social and intellectual patterns and trends in a diverse range of
sense-and decision-making activities.
Design/methodology/approach – Th e development of the framework is dri ven by three
motivating challenges: capturing the collective intelligence of science, fostering scientific
discoveries in science and e-Science, and facilitating evidence-based librarianship (EBL). The
framework is built on concepts such as structural holes and intellectual turning points, methodologies
and techniques for progressive knowledge domain visualization and differentiation of conflicting
opinions, and information integration models to achieve coherent transitions between different
conceptual scales.
Findings – Structural holes and turning points are detected and validated with the domain of
terrorism research as an example. Conflicting opinions are differentiated in the form of a decision tree
of phrases with the greatest information gains. Fundamental issues concerning the reliability of
common assumptions across multiple levels of granularity are identified. Knowledge diffusion is
studied in terms of information integration between a geographic space and an intellectual space.
Research limitations/implications – This study characterizes a holistic sense-making approach
with three exemplar themes. Future research is needed to develop theoretical foundations and
corresponding techniques to sustain additional themes.
Practical implications – The work contributes to the practice of improving our understanding of
the collective intelligence in science.
Originality/value – The value of the work is the conceptual and methodological contributions to
address various phenomena across micro- and macroscopic levels.
Keywords Knowledge sharing,Information, Visual media
Paper type Research paper
Introduction
Understanding conflicting opinions, creative ideas, and collective intelligence requires
a holistic sense-making approach. These common phenomena involve emergent
system-wide patterns as well as local details at lower levels of granularity. Some of the
most fundamental challenges are due to the wide spectrum of scales involved and
complexity of making sense signals and interpreting cues at various scales. Indeed, a
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/0737-8831.htm
The work is in part supported by the National Science Foundation under the Grant IIS-0612129.
Holistic
sense-making
approach
311
Received 27 February 2006
Revised 28 March 2007
Accepted 12 May 2007
Library Hi Tech
Vol. 25 No. 3, 2007
pp. 311-327
qEmerald Group Publishing Limited
0737-8831
DOI 10.1108/07378830710820907
common challenge is the need to construct a global picture from a large amount of
potentially conflicting local details. The goal of our research is to develop a practical
approach to address these challenges by facilitating sense-making tasks in this
context. The basis of our holistic sense-making approach is a generic conceptual and
methodological framework. In this paper, the author will identify the nature of key
challenges with reference to three motivating themes and illustrate how this approach
can be applied to these areas.
Motivating themes
Three kinds of ubiquitous intellectual activities are fundamental to the fulfillment of
increasingly demanding tasks, namely, making sense of a large volume of dynamic
information concerning an emergent social and intellectual community, decision
making over a wide range of conflicting views and seemingly contradictory evidence,
and fostering scientific discoveries in a volatile, fast-changing environment with
incomplete information and persistent uncertainty.
These activities and relevant challenges are discussed in the context of three
motivating themes:
(1) collective intelligence
(2) e-Science, and
(3) evidence-based librarianship (EBL).
These themes are used to demonstrate the nature of challenges and guide the
development of our holistic sense-making approach.
Collective intelligence
Collective intelligence is an emergent intelligence of a group or a community of
collaborative and competing individuals (Engelbart, 1995). The author will identify
some of the key challenges in this area and introduce a set of technologies that have
been developed for understanding the intellectual space of such communities.
As the first step towards understanding the collective intelligence of an intellectual
community, it is the sense-making need at a disciplinary level or a community level.
A community is defined in the context of studying collective intelligence in the
broadest sense. For example, a group of viewers who participated in an online debate
over the airing of a sniper video forms an invisible community. Such groups may
be small, but the dynamics of what the group collectively recognizes and debates about
is comparable to much larger sized communities. Members in such groups may
communicate with each other directly or indirectly. Examples of larger communities
include customers who shared their reviews of a book at Amazon.com, and scientists of
a specific field. The public who are interested in a common issue, such as global
warming, immigration issues, and Iraqi wars, also forms communities that are relevant
to the issue of collective intelligence.
It is important to distinguish the collective intelligence from the wisdom of crowds
(Surowiecki, 2005). Emphasis is on the emergent nature of the collective intelligence in
that the quality of the collective intelligence should be always better than individuals’
judgments and decisions. In contrast, it may not necessarily be the case with the
wisdom of crowds. The ultimate goal of our research in this area is to advance
the knowledge of how scientists make new discoveries and develop practical tools to
LHT
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