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Knowledge Cartography: Software tools and mapping
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Okada, Alexandra; Buckingham Shum, Simon and Sherborne, Tony eds. (2008). Knowledge Cartogra-
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Knowledge Cartography: Preface
The eyes are not responsible when the mind does the seeing.
Publilius Syrus (85-43 BC)
Maps are one of the oldest forms of human communication. Map-making, like paint-
ing, pre-dates both number systems and written language. Primitive peoples made
maps to orientate themselves in both the living environment and the spiritual worlds.
Mapping enabled them to transcend the limitations of private, individual representa-
tions of terrain in order to augment group planning, reasoning and memory. Shared,
visual representations opened new possibilities for focusing collective attention, re-
living the past, envisaging new scenarios, coordinating actions and making deci-
sions.
Maps mediate the inner mental world and outer physical world. They help us make
sense of the universe at different scales, from galaxies to DNA, and connect the
abstract with the concrete by overlaying meanings onto that world, from astrological
deities to signatures for diseases. They help us remember what is important, and
explore possible configurations of the unknown. Cartography — the discipline and
art of making maps — has of course evolved radically. From stone, wood and ani-
mal skins, we now wield software tools that control maps as views generated from
live data feeds, with flexible layering and annotation.1
“Foundational concept, fragmented thinking, line of argument, blue skies re-
search, peripheral work”: we spatialise the world of ideas all the time with such
expressions. Maps can be used to make such configurations tangible, whether
sketched on a napkin or modelled in software. In this book we bring together many
of the leading researchers and practitioners who are creating and evaluating such
software for mapping intellectual worlds. We see these as new tools for reading and
writing in an age of information overload, when we need to extract and construct
meaningful configurations, around which we can tell different kinds of narrative.
For a visual generation of children who have never known a world without ubiqui-
tous information networks, we might hypothesise that knowledge maps could have
particular attraction as portals into the world of ideas. Moreover, the network is not
only dominant when we think about our social and technical infrastructures, but
almost an ontological stance in postmodernity, where we hold our viewpoints to be
precisely that: always partial and contextualised. Weaving connections between
nodes in the network is the most flexible way to bring ideas and information into
locally coherent relationships with each other, knowing that there is always another
viewpoint on the validity of these patterns. Modelled in software, the vision is that
intellectual continents, islands and borders can be invoked and dissolved at different
scales, as required.
1 Our sister volume in this series, The Geospatial Web, explores the convergence
of spatial data, mapping tools and the social web (Scharl and Tochtermann, 2006).
2 Okada, Buckingham Shum and Sherborne
Knowledge Cartography can be defined as:
• the art, craft, science, design and engineering of different genres of map to
describe intellectual landscapes — answering the question how can we cre-
ate knowledge maps?
• and the study of cartographic practices in both beginners and experts as
they make and use such maps — answering the question how effective are
knowledge maps for different kinds of user?
The particular focus of the authors in this volume is on sensemaking: the process
by which externalising one’s understanding clarifies one’s own grasp of the situa-
tion, as well as communicates it to others — literally, the making of sense (Weick,
1995: p.4). While “sense” can be expressed in many ways (non-verbally in gesture,
facial expression and dance, and in prose, speech, statistics, film…), knowledge
cartography as construed here places particular emphasis on digital representations
of connected ideas, specifically designed to:
I. Clarify the intellectual moves and commitments at different levels.
(e.g. Which concepts are seen as more abstract? What relationships are le-
gitimate? What are the key issues? What evidence is being appealed to?)
II. Incorporate further contributions from others, whether in agreement or not.
The map is not closed, but rather, has affordances designed to make it easy
for others to extend and restructure it.
III. Provoke, mediate, capture and improve constructive discourse.
This is central to sensemaking in unfamiliar or contested domains, in which
the primary challenge is to construct plausible narratives about how the
world was, is, or might be, often in the absence of complete, unambiguous
data.
Our intention with this book is to provide a report on the state of the art from lead-
ers in their respective fields, identify the important challenges as they are currently
seen in this relatively young field, and inspire readers to test and extend the tech-
niques described — hopefully, to think more critically and creatively. Many of the
tools described are not sitting in research labs, but are finding application in diverse
walks of life, with active communities of practice. These communities represent the
readership we hope for: learners, educators, and researchers in all fields, policy
analysts, scenario planners, knowledge managers and team facilitators. We hope that
practitioners will find new perspectives and tools to expand their repertoire, while
researchers will find rich enough conceptual grounding for further scholarship.
Preface 3
Genres of knowledge map
A range of mapping techniques and support tools has evolved, shaped by the prob-
lems being tackled, the skill of mappers, and the sophistication of software available.
We briefly characterise below the main genres of map. The appendix summarises at
a glance which mapping approaches and software tools are presented in each chap-
ter.
Mind Mapping was developed by Tony Buzan in the early 1970s when he pub-
lished his popular book “Use Your Head.” Mind Mapping requires the user to map
keywords, sentences and pictures radiating from a central idea. The relatively low
constraints on how elements can be labelled or linked makes it well suited for visual
notetaking and brainstorming.
Figure1. Mind Map created with Buzan’s iMindmap
Concept Mapping was developed by Joseph Novak around 1972, based on
Ausubel’s theory that meaningful learning only takes place when new concepts are
connected to what is already known. Concept maps are hierarchical trees, in which
concepts are connected with labelled, graphical links, most general at the top. Novak
and many others have reported empirical evidence of the effectiveness of this tech-
nique, with an international conference dedicated to the approach.
4 Okada, Buckingham Shum and Sherborne
Figure2. Concept Map created with CMap Tools
Argument and Evidence Mapping was first proposed by J.H. Wigmore in the early
1900s to help in the teaching and analysis of court cases. The objective is to expose
the structure of an argument, in particular how evidence is being used, in order to
clarify the status of the debate. Still used in legal education today, the idea has been
extended, formalised (and reinvented) in many ways (Buckingham Shum, 2003;
Reed et al., 2007), but all focused on elements such as Claims, Evidence, Premises
and supporting/challenging relations.
Figure3. Argument Map created with Rationale
Preface 5
Issue Mapping derives from the “Issue-Based Information System” (IBIS) devel-
oped by Horst Rittel in the 1970s to scaffold groups tackling “wicked” socio-
technical problems. IBIS structures deliberation by connecting Issues, Positions and
Arguments in consistent ways, which can be rendered as textual outlines and graphi-
cal maps. “Dialogue Mapping” was developed by Conklin (2006) for using IBIS in
meetings, extended as “Conversational Modelling” by Sierhuis and Selvin (1999) to
integrate formal modelling and interoperability with other tools.
Figure4. Issue Map created with Compendium
Web Mapping appeared relatively recently as a result of the rapid growth of the
internet. Software tools provide a way for users to capture, position, iconify, link and
annotate hyperlinks in a visual space as they navigate, creating a richer trail which
comes to have more personal meaning than a simple bookmark list.
Figure5. Web Map about mapping tools with Nestor Web Cartogrpaher
6 Okada, Buckingham Shum and Sherborne
Thinking Maps as defined by Hyerle (Chapter X) contrasts all of the above with a
set of abstract visual conventions designed to support core cognitive skills. Hyerle’s
eight graphic primitives (expressing basic reasoning about, e.g. causality, sequence,
whole-part) are designed to be combined to express higher order reasoning (e.g.
metaphor, induction, systems dynamics).
Figure6. Thinking Maps created with Thinking Maps © tool
Finally, a note on what we might term Visual Specification Languages, which are
designed for software interpretation by imposing constraints on how links and often
nodes are labelled and combined. This is a huge field in its own right, with schemes
such as Unified Modeling Language (UML) supporting user communities far larger
than any of the others listed here, plus innumerable other notations and tools that
exploit the power of visualization for modelling processes, ontologies and organiza-
tions. These are not, however, heavily represented in this book (though see Chapters
X[sierhuis] and Y[basque]) for the simple reason that this book’s interest in sense-
making focuses on the analytical work required at the upstream phases in problem
solving, or in domains where formal modelling is contentious because of the as-
sumptions it requires. Once the problem, assumptions and solution criteria are
agreed and bounded, there is a clearer cost/benefit tradeoff for detailed modelling.
Overview of the book
This book has 17 chapters organised in two parts, defined by whether the primary
application is in formal learning or the workplace. However, while this distinction
reflects two large audiences, readers will find ideas cross-fertilising healthily be-
tween chapters. The first half, Knowledge Maps for Learning and Teaching, focuses
Preface 7
on applications in schools and universities. We start with tools for learners, opening
with a literature survey, followed by examples of different approaches (concept
mapping, information mapping; argument mapping). Attention then turns to the
kinds of maps that educators need. In the second half we broaden the scope to
Knowledge Maps for Information Analysis and Knowledge Management, examining
the role that these tools are playing in professional communities—but with great
relevance also to more formal learning contexts. We start with an analysis of the
knowledge cartographer’s skillset, followed by three case studies around issue map-
ping, one on evidence mapping, concluding with case studies on two additional
approaches.
1. Suthers, in “Empirical Studies of the Value of Conceptually Explicit Nota-
tions in Collaborative Learning” reports on a series of studies which show
that differences of notations or representational biases can lead to differences in
processes of collaborative inquiry. The studies span face-to-face, synchronous
online and asynchronous online media in both classroom and laboratory set-
tings.
2. Canas and Novak present “Concept Mapping Using CmapTools to Enhance
Meaningful Learning”. After briefly introducing the pioneering concept map-
ping approach and CmapTools software, they provide an update to what is
probably the world’s largest systematic deployment of concept mapping, the
“Proyecto Conéctate al Conocimiento” in Panama, reflecting on their experi-
ences introducing concept mapping in hundreds of schools to enhance meaning-
ful learning.
3. Marriott and Torres, in “Enhancing Collaborative and Meaningful Language
Learning Through Concept Mapping" describe how concept mapping can
help develop students’ reading, writing and oral skills as part of a blended
methodology for language teaching called LAPLI. Their research was first im-
plemented with a group of pre-service students studying for a degree in English
and Portuguese languages at the Catholic University of Parana (PUCPR) in
Brazil.
4. Hyerle, in “Thinking Maps®: a Visual Language for Learning” summarises a
graphical language comprising eight cognitive maps called Thinking Maps®
and Thinking Maps® Software. These tools have been used from early grades
to college courses to foster cognitive development and content learning, across
all disciplines
5. Zeiliger and Esnault, in “The Constructivist Mapping of Internet Informa-
tion at Work with Nestor”, present the Nestor Web Cartographer software and
the constructivist approach to mapping Internet information. They analyze a
case study in Lyon School of Management (EM LYON), to show how the fea-
tures of the software, such as a hybrid representational system, visual widgets
and collaboration, help in constructing formalised knowledge.
8 Okada, Buckingham Shum and Sherborne
6. Rider and Thomason, in “Cognitive and Pedagogical benefits of Argument
Mapping: L.A.M.P. Guides the Way to Better Thinking”, show that in dedi-
cated Critical Thinking courses “Lots of Argument Mapping Practice” (LAMP)
using a software tool like Rationale considerably improves students’ critical
thinking skills. They present preliminary evidence and discussion concerning
how LAMP confers these benefits, and call for proper experimental and educa-
tional research.
7. Okada, in “Scaffolding School Pupils’ Scientific Argumentation with Evi-
dence-Based Dialogue Maps” reports pilot work investigating the potential of
Evidence-based Dialogue Mapping to foster young teenagers’ scientific argu-
mentation. Her study comprises multiple data sources: pupils’ maps in Com-
pendium, their writings in science and reflective comments about the uses of
mapping for writing. Her qualitative analysis highlights the diversity of ways,
both successful and unsuccessful, in which dialogue mapping was used by these
young teenagers to write scientific explanations.
8. Rowe and Reed, in “Argument Diagramming: The Araucaria Project” de-
scribe the software package Araucaria, which allows textual arguments to be
annotated to create argument diagrams conforming to different schemes such as
Toulmin or Wigmore diagrams. Since each of these diagramming techniques
was devised for a particular domain or argumentation, they discuss some of the
issues involved in translating between the schemes.
9. Sherborne, in his chapter “Mapping the Curriculum: How Concept Maps
can Improve the Effectivness of Course Development” argues that ‘curricu-
lum development’ is a process that naturally lends itself to visualisation
through concept mapping. He reviews the evidence for how mapping can help
curriculum developers and teachers, by promoting more collaborative, learner-
centric designs.
10. Conole, in “Using Compendium as a Tool to Support the Design of Learn-
ing Activities”, reports work to help multimedia designers and university aca-
demics create and share e-learning activities, by creating a visual language for
learning design patterns. She discusses how learning activities can be repre-
sented, and how the maps provide a mechanism to supporting decision making
in creating new activities.
11. Opening the second half, Selvin, in “Performing Knowledge Art: Under-
standing Collaborative Cartography” focuses on the special skills and con-
siderations involved in constructing knowledge maps with and for groups. He
provides concepts and frameworks useful in analysing collaborative practice, il-
lustrating them with a case study.
Preface 9
12. Buckingham Shum and Okada, in “Knowledge Cartography for Controver-
sies: The Iraq Debate”, use the debate around the invasion of Iraq to demon-
strate a knowledge mapping methodology to extract key ideas from source ma-
terials, in order to classify and connect them within and across a set of
perspectives. They reflect on the value of this approach, and how it can be ex-
tended with finer-grained argument mapping techniques.
13. Ohl, in “Computer Supported Argument Visualisation: Modelling in Con-
sultative Democracy around Wicked Problems”, presents a case study where
a mapping methodology supported the analysis and representation of the dis-
course surrounding the draft South East Queensland Regional Plan Consulta-
tion. He argues that argument mapping can help deliver the transparency and
accountability required in participatory democracy.
14. Sierhuis and Buckingham Shum, in “Human-Agent Knowledge Cartography
for e-Science: NASA Field Trials at the Mars Desert Research Station”, de-
scribe the sociotechnical embedding of a knowledge cartography approach
(Conversational Modelling) within a prototype e-science work system. They
demonstrates how human and agent plans, data, multimedia documents, meta-
data, discussions, interpretations and arguments can be mapped in an integrated
manner, and successfully deployed in field trials which simulated aspects of
mission workload pressure.
15. Lowrance et al., in “Template-Based Structured Argumentation” present a
semi-automated approach to evidential reasoning, which uses template-based
structured argumentation. These graphical depictions convey lines of reasoning,
from evidence through to conclusions. Their structured arguments are based on
a hierarchy of questions (a tree) that is used to assess a situation. This hierarchy
of questions is called the argument template (as opposed to the argument, which
answers the questions posed by a template)
16. Vasconcelos, in “An Experience of the Use of the Cognitive Mapping
Method in Qualitative Research”, analyzes concept mapping as a tool for
supporting qualitative research, particularly to carry out literature reviews, con-
cept analysis and qualitative data examination. He uses his own experience in
applying CmapTools software to understand the concept of partnership.
17. Basque et al., in “Collaborative Knowledge Modelling with a Graphical
Knowledge Representation Tool MOT: A Strategy to Support the Transfer
of Expertise in Organizations”, present a strategy for collaborative knowledge
modelling between experts and novices in order to support the transfer of exper-
tise within organisations. They use an object-typed knowledge modelling soft-
ware tool called MOT, to elaborate knowledge models in small groups com-
posed of experienced and less experienced employees.
10 Okada, Buckingham Shum and Sherborne
Towards human-machine knowledge cartography
To summarise, Knowledge Cartography is a specific form of information visualiza-
tion, seeking to represent spatially intellectual worlds that have no intrinsic spatial
properties. We have emphasised the challenge of helping analysts craft maps of
information resources, concepts, issues, ideas and arguments as an intrinsic part of
their personal and collective sensemaking. As with all artistry and craft, the process
and product should interweave: the discipline required to craft a good map should
clarify thinking and discourse in a way that augments the analytic task at hand, and
the emerging map should in turn provoke further reflection on the rigour of the
analysis. We are interested in mapping the structure of physical phenomena (e.g. a
biological process), of intellectual artifacts (e.g. a curriculum), and intellectual
processes of inquiry (e.g. a meeting discussion, or a scientific or public debate).
This orientation complements the work that has emerged in recent years in Do-
main Visualization within the information retrieval community, and Meeting Cap-
ture from the multimedia analysis community. In Domain Visualization (e.g. Chen,
2003; Shiffrin and Börner, 2004), “maps of science” are generated from the analysis
of text corpora and related scientometric indices (e.g. co-citation patterns in litera-
ture databases), with the analyst then able to tune parameters to expose meaningful
patterns (e.g. emerging research fronts; turning points in the literature), and interac-
tively navigate the visualization as they browse trails of interest. In Meeting Capture
research (e.g. the European AMI and US CALO Projects), the analogous goal is to
extract significant moments from audio and video meeting records (e.g. decisions;
action items; disagreements), including generating argument maps (e.g. Rienks, et
al. 2006) in order to index the meeting and support follow-on activity.
We envisage that human and machine knowledge mapping will eventually con-
verge. Software agents will work continuously in the background and on demand,
generating maps and alerts that expose potentially significant patterns in discussions
and publications (e.g. term clusters; hub nodes; pivotal papers; emerging research
fronts; supporting/challenging evidence; candidate solutions). Analysts will assess,
further annotate, and add new interpretive layers. While some of the authors in this
book focus on mapping domains where objective, ‘hard’ science data can be used to
decide whether a map is correct or not, other authors are interested in how maps can
support modes of interpretation and discourse across “softer” disciplines within the
arts and humanities, and for teams confronted with wicked problems in policy delib-
eration and strategic planning, where there is no single, knowable solution.
The layers that analysts will add to machine generated maps will, therefore, also
reflect the community’s deliberations—whether in meetings or the literature—
adding important connections and summaries that are not in the source docu-
ments/datasets. Human and machine mapping should be synergistic. Machines will
play a critical role by filtering the data ocean, extracting increasingly higher level
patterns, and acting on those semi-autonomously. People will, however, sense con-
nections between experiences and ideas, and constantly read new connotations into
their physical and information environments, in ways that are hard to imagine in
machines. Crafting maps by hand will, in this view, continue to be an important
Preface 11
discipline for sensemaking, even as our tools expand exponentially in computational
power. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
We are confronted today by ever more complex challenges at community, national
and global levels. As we learn almost daily of new, unexpected connections between
natural and designed phenomena, we have to find ways to teach these rich, multilay-
ered webs to our children. More than ever, we need to find ways to build common
ground between diverse groups as they seek to make sense of the past, the immedi-
ate challenges of the present, and possible futures. It would trivialise the dilemmas
we face to declare a technological silver bullet. However, we cautiously propose that
rigour and artistry in Knowledge Cartography has a significant role to play in shap-
ing how stakeholders, young and old, learn to think, listen and debate.
Alexandra Okada, Simon Buckingham Shum and Tony Sherborne
Milton Keynes, October 2007
Companion website with supplementary resources:
kmi.open.ac.uk/books/knowledge-cartography
References
AMI: Augmented Multimodal Interaction project: publications.amiproject.org
Bowker, G. and Star, S.L. (2000). Sorting Things Out: Classification and Its Conse-
quences. MIT Press
Buckingham Shum, S. (2003). The Roots of Computer Supported Argument Visu-
alization. In Visualizing Argumentation, (Eds.) P. Kirschner, S.Buckingham
Shum and C. Carr. Springer-Verlag: London
CALO: Cognitive Assistant that Learns and Organizes: caloproject.sri.com
Chen, C. (2003) Mapping Scientific Frontiers. Springer, London, 2003.
Conklin, J. (2006). Dialogue Mapping. Wiley: Chichester
Reed, C., Walton, D. and Macagno, F. (2007). Argument Diagramming in Logic,
Law and Artificial Intelligence. The Knowledge Engineering Review, 22 (1), pp.
87-109
Rienks, R., Verbree, D. and Heylen, D. (2006). First Steps Towards Automatic Con-
struction of Argument-Diagrams from Real Discussions. Proc. COMMA’06: 1st
Int. Conf. on Computational Models of Argument, Liverpool, September 2006.
IOS Press: Amsterdam
Scharl, A. and Tochtermann, K. (2006). The Geospatial Web. Springer: Berlin
Selvin, A., Supporting Collaborative Analysis and Design with Hypertext Function-
ality. Journal of Digital Information, 1999. 1 (4), Article No. 16, 1999-01-14.
Shiffrin, R.M. and Börner, K. (2004). Mapping Knowledge Domains. Proc. Na-
tional Academy of Sciences, 101, pp. 5183-5185. (Special Issue Editorial)
Weick, K.E. (1995). Sensemaking in Organizations. Sage Publications: Thousand
Oaks
12 Okada, Buckingham Shum and Sherborne
Appendix: Mapping approaches and software by chapter
Part 1: Knowledge Maps for Learning and Teaching
Chapter Tool Technique Use Context
01 Empirical Studies of the
value of Conceptually Ex-
plicit Notations in Collabora-
tive Learning
Belvedere Argument
Mapping Undergraduate
Science
02 Concept Mapping Using
CmapTools to Enhance
Meaningful Learning
CmapTools Concept Mapping
Schools
03 Enhancing Collaborative
and Meaningful Languages
Learning Through Concept
Mapping
CmapTools Concept Mapping
Undergraduate
Language
04 Thinking Maps®: A Visual
Language for Learning Thinking
Maps Thinking Maps Schools
05 The Constructivist Mapping
of Internet Information at
Work with Nestor
Nestor Web Mapping Web Learners
06 Cognitive and Pedagogical
Benefits of Argument Map-
ping: L.A.M.P. Guides the
Way to Better Thinking
Rationale Argument
Mapping Undergraduate
Philosophy
07 Scaffolding School Pupils’
Scientific Argumentation
with Evidence-Based Dia-
logue Maps
Compendium Dialogue Mapping Schools
08 Argument Diagramming:
The Araucaria Project Araucaria Argument
Mapping Undergraduate
Philosophy
09 Mapping the curriculum:
how concept maps can im-
prove the effectiveness of
course development
CmapTools
Mind
Manager
Concept Mapping
Mind Mapping Schools
10 Using Compendium as a
Tool to Support the Design
of Learning Activities
Compendium Mind Mapping Learning
Designers
Preface 13
Part 2: Knowledge Maps for Information Analysis and Knowledge Management
Chapter Tool Technique Use Context
11 Performing Knowledge Art:
Understanding Collaborative
Cartography
Compendium Conversational
Modelling e-Science and
other mission
operations
12 Knowledge Cartography for
Controversies: The Iraq
Debate”
Compendium Dialogue
Mapping Policy Analy-
sis
13 Computer Supported Argu-
ment Visualisation: Model-
ling in Consultative Democ-
racy Around Wicked
Problems
Compendium Modelling Map-
ping Government
Public Consul-
tation
14 Human-Agent Knowledge
Cartography for e-Science:
NASA Field Trials at the
Mars Desert Research Sta-
tion
Compendium Conversational
Modelling e-Science for
space explora-
tion
15 Template-based Structured
Argumentation SEAS Evidence Map-
ping Intelligence
and other
Evidence
Analysis
16 An Experience of the Use of
the Cognitive Mapping
Method in Qualitative Re-
search
CmapTools Concept Mapping Postgraduate
Research
17 Collaborative Knowledge
Modelling with a Graphical
Knowledge Representation
Tool MOT: A Strategy to
Support the Transfer of
Expertise in Organizations
MOT Conceptual
Modelling Organizational
Knowledge
Sharing
14 Okada, Buckingham Shum and Sherborne
Author Biographies
Josianne Basque is professor in educational technology at Tele-universite, Mont-
real, a French Canadian distance university. She designed online courses in the
fields of learning and cognitive science, technology in education and instructional
design. She is also a researcher at the LICEF Research Center, dedicated to re-
search in the field of Cognitive Informatics and Learning Environments. Her cur-
rent research interests include knowledge modeling applied to learning, knowledge
management and instructional design, the design of e-learning scenarios, collabo-
rative learning and self-evaluation of competencies.
Email: basque.josianne@teluq.uqam.ca
Homepage: www.teluq.uqam.ca/~jbasque
Simon Buckingham Shum is Senior Lecturer at the Knowledge Media Institute,
Open University. B.Sc. Pyschology University of York. M.Sc. in Ergonomics from
University College London and Ph.D. from the University of York. He is inter-
ested in technologies for sensemaking, specifically, which structure discourse to
assist reflection and analysis.
Email: sbs@acm.org
HomePage: http://kmi.open.ac.uk/people/sbs/
Tom Boyce is an Emeritus Consultant in the Representation and Reasoning Pro-
gram at SRI International’s Artificial Intelligence Center. He has an engineering
degree from Stanford and an MBA from Santa Clara University. He is interested
in using AI software for corporate business intelligence applications, such as creat-
ing and tracking future scenarios. He has a long standing involvement in complex
project management applications as well.
Email: boyce@ai.sri.com
Homepage: http://www.ai.sri.com/people/boyce/
Alberto J. Cañas is Co-Founder and Associate Director of the Institute for Human
and Machine Cognition – IHMC. Bachelors Degree in Computer Engineering from
the Instituto Tecnologico de Monterrey, Mexico, and a Masters Degree in Com-
puter Science and a Ph.D. in Management Science, both from the University of
Waterloo, Canada. He is interested in the theoretical aspects and in the implemen-
tation details of concept mapping in education. His research includes uses of com-
puters in education, knowledge management, and human-machine interface.
Email: acanas@ihmc.us
HomePage: http://www.ihmc.us/users/acanas
Gráinne Conole is Professor of e-Learning at the Open University. BA. Chemis-
try PhD. X-Ray Crystallography at North London University. Her interests are in
the use, integration and evaluation of Information and Communication Technolo-
gies and e-learning and impact on organisational change.
Preface 15
email: g.c.conole@open.ac.uk
homepage: http://iet.open.ac.uk/pp/g.c.conole/biography.cfm
Liliane Esnault is Associate Professor in Information Systems management, e-
Business and Project Management at E.M.Lyon. B.Sc.and Doctorate in Fundamen-
tal Molecular Physics from Ecole Supérieure de Physique et Chimie de Paris
(ESPCI). She is currently involved in the European Research project PALETTE
(Integrated Services for Communities of Practice), after several other European
projects in the same area.
HomePage: NONE L I'm ashamed! The home page for EM LYON is
http://www.em-lyon.com
Email : esnault@em-lyon.com
Ian Harrison is a Senior Computer Scientist with the Representation and Reason-
ing Program at SRI International's Artificial Intelligence Center. He received his
Ph.D. in Engineering Rock Mechanics from Imperial College of Science, Technol-
ogy, and Medicine, University of London, and his MSc. in Artificial Intelligence
from the University of Edinburgh. His research interests have primarily focused on
the development and deployment of software tools to aid intelligence analysts.
Email: harrison@ai.sri.com
Homepage: http://www.ai.sri.com/~harrison/
David Hyerle is the Developer of the Thinking Maps® model and the Founding
Director of Thinking Foundation, a nonprofit research organization supporting
participatory research on models for facilitating cognitive processes and critical
thinking in schools. B.A. English Literature on literacy. M.Ed. Urban Education
and Ed.D. Curriculum and Instruction at U.C. Berkeley and Exchange Scholar at
Harvard College. His research focuses on the areas of thinking, learning, and lead-
ership.
Email: designs.thinking@valley.net
HomePage: http://www.thinkingfoundation.org
Michel Léonard is a professional researcher at the LICEF Research Center. He
worked in many areas: hospitals, industrial maintenance, video and audio RF, as a
technician, coordinator, test and development engineer, production engineer and
manager. Since January 1994, he has contributed to the development and valida-
tion of instructional design methods and support systems. He also contributed to
the development of the knowledge modeling software MOT. He is involved in the
preparation and the delivery of training sessions on knowledge modeling and on
instructional engineering with tools and methods developed at the LICEF.
Email: leonard.michel@licef.teluq.uqam.ca
John Lowrance is the Director of the Representation and Reasoning Program at
SRI International's Artificial Intelligence Center. He received his A.B. in Com-
puter Science and Mathematics from Indiana University, and M.S. and Ph.D. in
Computer and Information Science from the University of Massachusetts. His re-
16 Okada, Buckingham Shum and Sherborne
search interests have primarily focused on evidential reasoning, a methodology for
representing and reasoning from evidence (i.e., information that is potentially un-
certain, incomplete, and inaccurate). His most recent work attempts to make evi-
dential reasoning accessible to practicing analysts and decision makers.
Email: lowrance@ai.sri.com
Homepage: http://www.ai.sri.com/people/lowrance/
Rita de Cassia Veiga Marriott is a Language Tutor at the University of Birming-
ham / UK and a member of the Research Group on Education, Communication
and Technology at the Catholic University of Parana (PUCPR) / Brazil. She was a
lecturer in English as a Foreign Language and Meaningful and Collaborative
Learning Online at the Postgraduate Education course at the Pontifical Catholic
University of Paraná (PUCPR), where she attained her MA in Education. She was
responsible for teacher development programmes related to Computer Assisted
Language Learning (CALL) providing support for the implementation of Distance
Learning Courses at the Language Centre at the Federal University of Parana
(UFPR) in Brazil. She is interested in methodologies for language teaching /
learning, e-learning, collaborative learning and concept mapping.
Email: r.marriott@bham.ac.uk
Janet Murdock is a Computer Scientist in the Artificial Intelligence Center at SRI
International. She holds B.S. and M.S. degrees in Chemical Engineering from
Purdue and Massachusetts Institute of Technology. She also holds M.S. and Ph.D.
degrees in Computer Science from Stanford University. Prior to coming to SRI
International, she worked in industry (Design Power, Inc., Praxis Engineers, Inc.,
and GE Power Systems) creating artificial intelligence applications that solve en-
gineering problems. Her research interests include representation and reasoning,
evidence management, and multimedia-based user interfaces.
Email: murdock@ai.sri.com
Homepage: http://www.ai.sri.com/people/murdock/
Ken Murray is a Senior Computer Scientist in the Representation and Reasoning
Program at SRI International's Artificial Intelligence Center. He holds a Bachelor
degree from the University of Iowa, and Masters and Ph.D.degrees from the Uni-
versity of Texas at Austin. His interests include the design, construction, and ap-
plication of large knowledge-based systems with particular focus on interactive
methods for knowledge acquisition and knowledge integration.
Email: murray@ai.sri.com
Homepage: http://www.ai.sri.com/people/murray/
Joseph D. Novak is Professor Emeritus at Cornell University and a Senior Scientist
at the Institute for Human and Machine Cognition, and President of the Joseph D.
Novak Knowledge Consultants, Inc. B.S. in Science and Mathematics, M.S. in
Science Education, Ph.D. at Science Education & Biology at the University of
Minnesota. His interests focus on meaningful learning and concept maps in educa-
tion and knowledge management.
Preface 17
Email: jnovak@ihmc.us
HomePage: http://www.ihmc.us/users/user.php?UserID=jnovak
Alexandra Okada is Researcher in Knowledge Mapping for Open Content Initia-
tive at the Knowledge Media Institute, Open University. Visiting Lecturer at the
Fundacao Getulio Vargas FGV Online and the Pontificia Universidade Católica
PUCSP COGEAE Online. B.Sc. Computer Science at the Instituto Tecnológico de
Aeronáutica – ITA, MA and PhD in Education at PUCSP. She is interested in
how knowledge maps can be used to facilitate research, investigation and learning.
Email: a.l.p.okada@open.ac.uk
HomePage: http://kmi.open.ac.uk/people/ale/
Ricky Ohl has gained broad experience from involvement in various businesses
over 30 years. He holds degrees in Business Management and in Commerce with
Honours. His earlier published research examined “The Implementation of an
Internet Management System into a Virtual Private Network.”, a pioneering pro-
ject with unknown risk factors. He is currently completing his PhD research on
“CSAV Modelling for Consultative Democracy around Wicked Problems.” His
teaching, in both advanced masters and undergraduate courses at Griffith Univer-
sity has focussed on areas including knowledge management, business manage-
ment, information visualisation, information systems, informatics and IT govern-
ance. He also performs corporate consulting in knowledge management, business
systems and web presence.
Homepage: http://rickonneblue.awardspace.com/
Email: rickyohl@gmail.com
Gilbert Paquette is professor at Tele-universite, Montreal, and the holder of the
Canada Research Chair in Tele-Learning in Cognitive Engineering. He founded
the LICEF Research Center in 1992 and initiated many strategic and large projects
on instructional engineering of e-learning environments and on knowledge man-
agement. He is the main designer of the knowledge modeling software MOT. He is
the author of three books and of hundreds of articles and communications in those
fields. He is presently the director of the cross-Canadian project LORNET (Learn-
ing Objects Repositories Network).
Email: paquette.gilbert@teluq.uqam.ca
Homepage: http://www.licef.teluq.uqam.ca/gp/
Béatrice Pudelko recently finished her doctoral studies in Cognitive Psychology at
the University Paris VIII. In her thesis, she examined, with a Vygotskian approach,
the epistemic mediations of a graphical knowledge representation tool during a
text comprehension activity. In the last years, she participated in many research
projects at the LICEF Research Center. She is also a tutor in an online course on
cognitive science and learning offered at Tele-universite. Her current research in-
terests are related to the use of knowledge modeling for learning and for knowl-
edge elicitation, to the development of cognitive skills and to artifact-mediated ac-
tivity.
18 Okada, Buckingham Shum and Sherborne
Email: pudelko.beatrice@licef.teluq.uqam.ca
Yanna Rider is Consultant and Trainer at Austhink. She holds a PhD in Philoso-
phy from The University of Melbourne. She is interested in the conceptual un-
derpinnings of Argument Mapping and its relationship to critical thinking, as well
as in applying Argument Mapping in professional contexts.
Email: yxr@austhink.com
Homepage: http://www.austhink.com
Andres Rodriguez worked as a Computer Scientist with the Representation and
Reasoning Program at SRI International's Artificial Intelligence Center until
2006. He is now an independent consultant. He holds a Bachelors in Computer
Science from the University of Los Andes and a Master of Science in Computer
Science from Stanford University. His research interests include machine-
learning, reasoning under uncertainty, and web enabled user interfaces.
Email: rodriguez@ai.sri.com
Homepage: http://www.ai.sri.com/~rodriguez/
Albert M. Selvin is a Director in the Information Technology Group at Verizon
Communications, USA, where he leads web design, software development and
business process redesign teams. His research interests are on the practice of con-
structing hypermedia representations, practice in participatory hypermedia con-
struction and collaborative hypermedia authoring. He is the original developer and
member of the ongoing core team for the Compendium approach and toolset and
has facilitated over 500 sessions for industry, academic, and public groups. He re-
ceived his B.A. in Film/Video Studies at the University of Michigan (1982), and
an M.A.. in Communication Arts from the University of Wisconsin (1984), and is
currently a PhD candidate at the Knowledge Media Institute, Open University,
UK.
Email: alselvin@gmail.com
HomePage: http://kmi.open.ac.uk/people/selvin/
Tony Sherborne is Creative Director for the Centre for Science Education at Shef-
field Hallam University, curriculum developer and a NESTA Fellow Researcher.
B.Sc. and MA. in Science from Cambridge University. He is interested in using
maps to enhance teachers' creativity in the design of curricula and pedagogical
materials.
Email: tonysherborne@dsl.pipex.uk
HomePage: http://www.aunm22.dsl.pipex.com/CrackingScience/QwikiWeb2.htm
Maarten Sierhuis is Computer Scientist and Senior Researcher at RIACS/NASA
Ames Research Center. His research focuses on multi-agent systems and artificial
intelligence. His early work discusses about knowledge modelling and expert sys-
tems. His work area comprehends developing tools for modelling situated human
behavior in organizations.
E-mail: msierhuis@mail.arc.nasa.gov
Preface 19
HomePage: http://home.comcast.net/~msierhuis
Dan Suthers is presently Associate Professor in the Department of Information and
Computer Sciences at the University of Hawaii at Manoa, where he directs the
Laboratory for Interactive Learning Technologies and is chair of the interdiscipli-
nary Communication and Information Sciences Ph.D. program. He holds a B.F.A.
from Kansas City Art Institute, and an M.S. and Ph.D. in Computer Science from
the University of Massachusetts. His research focuses on the design of educational
technologies for collaborative learning and online learning communities.
Email: suthers@hawaii.edu
HomePage: http://lilt.ics.hawaii.edu/suthers/
Neil Thomason is Senior Lecturer in the Department of History & Philosophy of
Science at The University of Melbourne and holds a doctorate in the Philosophy of
Science from the University of California at Berkeley. He has taught Critical
Thinking at Reed, Vassar and The University of Melbourne. He is interested in
everything except professional sport.
Email: neilt@unimelb.edu.au
Homepage: http://www.hps.unimelb.edu.au/about/staff/neil_thomason/
Jerome Thomere is a Computer Scientist in the Representation and Reasoning
Program at SRI International's Artificial Intelligence Center. He holds a Masters in
Applied Mathematics from Ecole Centrale Paris and a Masters (DEA) in Artificial
Intelligence from Universite Aix Marseille. His research interests include the rep-
resentation of knowledge, techniques for approximate reasoning, and user interface
design.
Email: thomere@ai.sri.com
Homepage: http://www.ai.sri.com/people/thomere/
Patricia Lupion Torres teaches at the Masters and Research Degree Courses in
Education at PUCPR (Pontifical Catholic University of Parana/Brazil) whilst is the
Director of Distance Learning at the same institution. A Pedagogue, she is a Spe-
cialist in Psycho-pedagogy and in Sociological Theories, she holds a Master in
Education from PUCPR and a doctorate on Production Engineering from UFSC
(Federal University of Santa Catarina/Brazil). She is also the Pedagogical Coordi-
nator of the National Service on Rural Learning – SENAR-PR/Brazil. Her inter-
ests are e-learning, virtual universities, collaborative learning and concept map-
ping.
Email: patorres@terra.com.br
Mário Vasconcellos, is a Lecturer at University of Amazonia (Centre of Social and
Economic Studies) and Federal University of Pará (Centre of Environment), both
in Brazil. He holds a Mphil from the Centre of High Amazonian Studies, Federal
University of Pará (Brazil), and Phd from the Centre for Development Studies,
Swansea University (United Kingdom). His research focuses on development
management, local development and sustainable development in Amazonia.
20 Okada, Buckingham Shum and Sherborne
Emails: mariovasc@unama.br ; mariovasc@ufpa.br
Eric Yeh is a Software Engineer with the Representation and Reasoning Program
at SRI International's Artificial Intelligence Center. He holds a Bachelors in Com-
puter Science from the University of California at Berkeley. His interests lie in the
use of artificial intelligence techniques, including machine-learning and natural
language processing, to augment human decision making.
Email: yeh@ai.sri.com
Homepage: http://www.ai.sri.com/people/yeh/
Romain Zeiliger is Computer Scientist and Research Engineer at GATE Groupe
d'Analyse et de Théorie Economique at the Centre National de la Recherche Scien-
tifique (CNRS-GATE) and Université Lumière Lyon2. He is the author of the
Software Nestor Web Cartographer. He is also researcher at the European Re-
search project PALETTE. B.Sc. in Computer Science at University
Claude Bernard Lyon1. His interests are Navigation, CSCW and Web based
Learning.
Email: zeiliger@gate.cnrs.fr
HomePage: <http://www.gate.cnrs.fr/~zeiliger/>http://www.gate.cnrs.fr/~zeiliger/
