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A System Design for the Dynamic Cognitive Mapping of Wiki Articles
By
Daniel Pettus
A MASTER OF ENGINEERING REPORT
Submitted to the College of Engineering at
Texas Tech University in
Partial Fulfillment of
The Requirements for the
Degree of
MASTER OF ENGINEERING
Approved
______________________________________
Dr. A. Ertas (Chair)
______________________________________
Dr. T. Maxwell (member)
___________________________________
Dr. M. Tanik (member)
______________________________________
Dr. J. Woldstad (COE Representative)
October 25, 2008
1
ACKNOWLEDGEMENTS
I would like to thank Dr. Atila Ertas, the Department of Mechanical Engineering at Texas
Tech University, the entire Texas Tech staff, and guest speakers for their role in organizing the
Master of Engineering program for Raytheon employees.
I would like to thank my fellow students in the Master of Engineering program for their
support in helping me accomplish my goals.
I would like to thank my coworkers and management for accommodating a class
schedule and deadlines that often did not synch well up with the schedule and deadlines of my
professional career.
I would like to thank my family and loved ones for offering their support, understanding,
enthusiasm, and sacrifice during this time.
Most of all, I would like to thank Minh “Michele” Luong, who encouraged me to join this
program and who provided me with her confidence and support throughout. I would not have
accomplished so much without her.
2
TABLE OF CONTENTS
ACKNOWLEDGEMENTS ......................................................................................................... 1
DISCLAIMER............................................................................................................................... 5
ABSTRACT ................................................................................................................................... 6
LIST OF FIGURES ...................................................................................................................... 7
LIST OF TABLES ........................................................................................................................ 9
CHAPTER I
INTRODUCTION....................................................................................................................... 10
CHAPTER II
BACKGROUND ......................................................................................................................... 13
2.1 The Background of Wikis 13
2.2 The Background of Cognitive Mapping 14
2.2.1 Concept Mapping 14
2.2.2 Mind Mapping 15
2.2.3 Dialogue Mapping 18
CHAPTER III
ANALYSIS OF TOOLS ............................................................................................................. 19
3.1 Cognitive Mapping Tools 19
3.1.1 Concept Mapping 19
3.1.1.1 CmapTools 19
3.1.2 Dialogue Mapping 19
3.1.2.1 Compendium 19
3.1.3 Mind Mapping 20
3.1.3.1 MindManager 20
3.1.3.2 FreeMind 20
3.1.3.2.1 FreeMind Flash Browser 20
3.1.4 Cognitive Mapping Conclusion 21
3.2 Wikis 21
3.2.1 Platypus Wiki 21
3.2.2 MediaWiki 22
3.2.2.1 Semantic MediaWiki 22
3.2.3 Wiki Conclusion 22
3.3 Source Parsing Tools 23
3.3.1 Natural Language Processing 23
3.3.2 Structure Parsing 23
3.3.3 Source Parsing Conclusion 23
CHAPTER IV
WIKI-POWERED CONCEPT MAP DESIGN ....................................................................... 24
4.1 Scope 24
4.2 Design Process 24
4.2.1 Requirements 24
4.2.2 System Architecture 25
3
4.2.2.1 Contextual 25
4.2.2.1.1 Interrogative Data 26
4.2.2.1.1.1 Why does the work need to be done? (Goals) 26
4.2.2.1.1.2 Who are the participants? (Stakeholders) 26
4.2.2.1.1.3 What information and entities are used? (Data / Entities) 26
4.2.2.1.1.4 How do they operate? (Processes) 26
4.2.2.1.1.5 Where do they operate? (Geography) 27
4.2.2.1.1.6 When are the various actions taken? (Timeline) 27
4.2.2.1.1.7 Relationship Matrix (Why vs. Who) 27
4.2.2.1.2 Context Diagram 28
4.2.2.1.3 Scope and Boundaries 28
4.2.2.1.3.1 Deliverables 28
4.2.2.1.3.1.1 External 29
4.2.2.1.3.1.2 Functionality 29
4.2.2.1.3.1.3 Data 30
4.2.2.1.3.1.4 Technical Structure 30
4.2.2.1.4 Quality Attributes 30
4.2.2.2 Operational 32
4.2.2.2.1 Operational Concept 32
4.2.2.2.2 Key Scenarios 33
4.2.2.2.3 Actors 33
4.2.2.2.4 Use Cases 33
4.2.2.2.5 Activity Diagram 37
4.2.2.3 Logical 37
4.2.2.3.1 Functional Decomposition 38
4.2.2.3.2 Logical Solution 38
4.2.2.3.3 Logical Block Diagram 39
4.2.2.3.4 Data Flow Diagram 39
4.2.2.3.5 Sequence Diagrams 40
4.2.2.3.5.1 Search and View Wiki Mind-map 40
4.2.2.3.5.2 Browse Wiki Mind-map 40
4.2.2.3.5.3 View Wiki Mind-map Source 41
4.2.2.3.6 Evaluation 41
4.2.2.4 Physical 41
4.2.2.4.1 Physical Components 42
4.2.2.4.1.1 Hardware 42
4.2.2.4.1.2 Software 42
4.2.2.4.1.3 Data 42
4.2.2.4.1.4 Interface 42
4.2.2.4.2 Physical Approach 43
4.2.2.4.3 Static View of Physical System 43
4.2.2.4.4 Trade of approaches to quality attributes 43
4.2.2.4.4.1 Usability 43
4.2.2.4.4.2 Robust 44
4.2.2.4.4.3 Reliability 44
4
CHAPTER V
SYSTEM MOCKUP ................................................................................................................... 46
5.1 Search and View Wiki Mind-map 46
5.1.1 Opening Page 46
5.1.2 Search and View Results 47
5.1.3 Search the Contents of the Map 48
5.2 Browse Wiki Mind-map 49
5.2.1 Expand the Nodes 49
5.3 View Wiki Mind-map Source 51
5.3.1 View Main Topic 51
5.3.2 View Categories 53
5.3.3 View Linked Topic 55
5.3.4 View External Page 57
CHAPTER VI
SUMMARY AND CONCLUSIONS ......................................................................................... 59
REFERENCES ............................................................................................................................ 60
APPENDIX A
ACRONYM LIST ....................................................................................................................... 61
APPENDIX B
RESOURCE LIST ...................................................................................................................... 62
5
DISCLAIMER
The opinions expressed in this report are strictly those of the author and are not necessarily those
of Raytheon, Texas Tech University, nor any U.S. Government agency.
6
ABSTRACT
In recent times wikis have become an important tool for online collaboration and information
dissemination in both the public, academic, and enterprise arenas.
“A wiki is a collection of web pages designed to enable anyone who accesses it to contribute or
modify content, using a simplified markup language. Wikis are often used to create collaborative
websites and to power community websites. For example, the collaborative encyclopedia
Wikipedia is one of the best-known wikis. Wikis are used in businesses to provide affordable and
effective intranets and for Knowledge Management.” [Wikipedia/Wiki, 2008]
Any user can very easily add content to a wiki by means of their markup languages. The
underlying hypertext, like HTML, is loosely structured. This allows for each author or authors to
individually or collectively determine how to organize, display, and reference content. Because of this
loose structure, wikis run the risk of disorientation. Structure and style may be inconsistent and a reader
may not understand the relevance of the material within the overall context.
Cognitive mapping can be a solution to this issue. Cognitive mapping considers thinking as a
self-organizing information system, i.e. a cognitive map will maintain the relevance of information
regardless if new information is added or existing information is modified or removed. Cognitive maps
are graphical representations of the structure of this information. They can give the necessary structure to
a wiki in order to aid in understanding.
The human brain typically identifies visual patterns more easily than non-visual. Visualization
tools such as cognitive maps are also less restricted to barriers such as language. Using techniques to
visualize information helps to communicate and clarify ideas, reveal hidden patterns and relationships,
and gain insight to new ideas.
In this paper, we shall discuss some of the issues with wikis and describe a system that uses
cognitive mapping to visualize the structure of information within wiki articles in an attempt to address
these issues, and to utilize the brain’s ability to comprehend through visualization.
7
LIST OF FIGURES
Figure 1 The Problem with Wikipedia 11
Figure 2 Sample Concept Map 15
Figure 3 Sample Mind Map 17
Figure 4 Sample Dialogue Map 18
Figure 5 Context Diagram 28
Figure 6 Activity Diagram 37
Figure 7 Functional Decomposition Breakdown 38
Figure 8 Logical Block Diagram 39
Figure 9 Data Flow Diagram 39
Figure 10 Sequence Diagram - Search and View Wiki Mind-Map 40
Figure 11 Sequence Diagram - Browse Wiki Mind-Map 40
Figure 12 Sequence Diagram - View Wiki Mind-Map Source 41
Figure 13 Physical System 43
Figure 14 Mockup Opening Page 46
Figure 15 Mockup Search and View Results 47
Figure 16 Mockup Search the Contents of the Map 48
Figure 17 Mockup Expand the First Level Node 49
Figure 18 Mockup Expand Second Level Node 50
Figure 19 Mockup Select Main Topic 51
Figure 20 Mockup View Main Topic 52
Figure 21 Mockup Select Category 53
Figure 22 Mockup View Category 54
Figure 23 Mockup Select Linked Topic 55
Figure 24 Mockup View Linked Topic 56
8
Figure 25 Mockup Select External Page 57
Figure 26 Mockup View External Page 58
9
LIST OF TABLES
Table 1 System Requirements 24
Table 2 Relationship Matrix 27
Table 3 External Deliverables 29
Table 4 Functionality Deliverables 29
Table 5 Data Deliverables 30
Table 6 Technical Deliverables 30
Table 7 Quality Pugh Chart 31
Table 8 Use Case - Search for wiki articles 33
Table 9 Use Case - Render mind-map of wiki article 34
Table 10 Use Case - Browse linked wiki articles 35
Table 11 Use Case - View original wiki article 35
10
CHAPTER I
INTRODUCTION
Bo Leuf and Ward Cunningham, developers of the first wiki, asked the following question,
“What is the main limit of current network-based collaboration models?” [Leuf and Cunningham, 2001]
They were not satisfied by the current models of the day, i.e. e-mail exchange and mailing lists, shared
repositories, and interactive content update systems employing version control techniques. These models
all suffer from a high degree of redundancy and the difficulty of writing in collaboration with others.
In the 1990’s wikis became a more convenient and popular collaboration model. Some of the
reasons that wikis became popular are as follows:
• It is very easy to add content to a wiki by means of their simple markup languages
• A wiki’s underlying markup language is not tightly structured, so that people can decide
collectively how to organize their content
• Any user can add or organize content in a wiki
• Wikis actively allow for and encourage collaboration
Although wikis clearly have their benefits, they also have their limitations. Wiki contributors add
to a wiki topic using their own dialect. The use of such general-purpose, or natural, language makes it
easy for these users, in their own fashion, to contribute to the knowledge sharing effort in a wiki.
Conversely, the use of natural language restricts the possible set of knowledge providers and consumers
to people who comprehend the language. Such restrictions place limits on the level of collaboration that
these systems were meant to enhance.
The loose structure of wikis is both a benefit and a limitation. The starting phase of a wiki article
is crucial in determining its success. Although a loose structure encourages content generation, if the
structure of the article is not well defined at the onset, then further additions by others will amplify the
initial problem. There is no taxonomy previously decided on by the wiki community. Information in the
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article may often grow organically. When this occurs, there eventually will become a moment by which
it becomes necessary to restructure the article to put everything in order. This is often not an easy task.
A third limitation is the fact that links within an article are often unidirectional, i.e. the linked
topic has no knowledge of the referrer. To understand a topic a reader may begin to follow the included
links to gain further insight. Unfortunately, within a few levels of indirection, the reader is now reading
topics that have little or nothing to do with the original material.
Figure 1 The Problem with Wikipedia
When you combine these limitations with the fact that structure between distinct topics is usually
inconsistent, the risk of disorientation is high.
Throughout the course of human evolution, the brain has had a MUCH longer time to develop the
skills to recognize, understand, and recall visual patterns than it has had for the development of formal
languages, spoken or written. As a result, the human brain recognizes shapes and drawings more easily
than understanding words and numbers.
12
Barriers introduced by the use of natural language can be overcome by the use of a visual
representation of the information within the article. Disorientation due to poor structure is also overcome
by the mind’s ability to easily comprehend visual information. Visual representation can also provide
authors a way to see relationships between concepts, allowing them to be aware of the inner structure of
what they are writing.
This paper will define a light-weight and convenient system that shall utilize cognitive mapping
techniques as a solution to overcome the aforementioned limitations of the wiki model through visual
representation. This newly defined system aims to clarify relationships between concepts written in wikis
articles. It will highlight the structure of the wiki article to in turn allow the user to more easily identify,
recognize and further understand the content written within.
13
CHAPTER II
BACKGROUND
2.1 The Background of Wikis
In 1994, a man by the name of Howard G “Ward” Cunningham designed and implemented a
system for authoring and linking web pages using a web browser only. This software was titled
WikiWikiWeb, or Wiki for short. The term “WikiWiki” was chosen because he remembered once when
he was told to take the Wiki Wiki Shuttle at the Honolulu International Airport. The word “wiki” in
Hawaiian means “fast” and Cunningham thought the word would accurately reflect his system. He
describes a wiki to be “the simplest online database that could possibly work.” [Leuf and Cunningham,
2001]
In 1995 Cunningham deployed his wiki as an add-on to the Portland Pattern Repository, a site
hosted by Cunningham’s company, C2, where topics on software development patterns are discussed.
Since then, the wiki concept has found wide acceptance, first within other technical and academic
communities and then within the general population. The most well-known example, Wikipedia,
currently contains “over 10 million articles in 253 languages” [Wikipedia/Wikipedia, 2008], and is
arguably the most accessed resource of information online today.
The essence of the wiki idea has been summarized on many occasions. For the sake of the
argument of this paper, we are condensing the wiki concept as follows:
• “Wiki is a piece of server software that allows users to freely create and edit Web page content
using any Web browser. Wiki supports hyperlinks and has a simple text syntax for creating new
pages and crosslinks between internal pages on the fly.” [Wiki.org/WhatIsAWiki, 2008]
• “Wiki is unusual among group communication mechanisms in that it allows the organization of
contributions to be edited in addition to the content itself.” [Wiki.org/WhatIsAWiki, 2008]
• “Like many simple concepts, "open editing" has some profound and subtle effects on Wiki usage.
Allowing everyday users to create and edit any page in a Web site is exciting in that it encourages
democratic use of the Web and promotes content composition by nontechnical users.”
[Wiki.org/WhatIsAWiki, 2008]
14
2 .2 The Background of Cogni t ive Mapping
Cognitive maps are a means by which we can organize and store knowledge spatially in order to
allow us to conceptualize information in a visual manner. Cognitive mapping may be defined as a
“process composed of a series of psychological transformations by which an individual acquires, codes,
stores, recalls, and decodes information about the relative locations and attributes of phenomena in their
everyday spatial environment.” [Downs and Stea, 2005] Cognitive maps can be represented by various
methods and for our system we shall consider the following three: Concept Maps, Mind Maps, and
Dialogue Maps.
2.2 .1 Concept Mapping
Initiated by J. D. Novak 1960 at Cornell University and based on theories of David Ausubel,
Novak concludes that “Meaningful learning involves the assimilation of new concepts and propositions
into existing cognitive structures.” [Novak and Gowin, 1984] His work culminates in the creation of
concept mapping.
Concept mapping is a type of cognitive map, in this sense, representing “a structured process,
focused on a topic or construct of interest, involving input from one or more participants, that produces an
interpretable pictorial view (concept map) of their ideas and concepts and how these are interrelated.”
[Social Research Methods/Concept Mapping, 2008] Nodes in the map represent concepts. Links
between the nodes represent relationships between concepts. These relationships are labeled on the link.
Links can be one-way, two-way, or non-directional. A set of concepts representing a specific category
may be grouped and labeled as such. The map may express temporal or causal relationships between
concepts.
The following example is a concept map on the topic of “Avionics”. This map was made
available from the IHMC (Institute for Human and Machine Cognition).
15
Figure 2 Sample Concept Map
2 .2 .2 Mind Mapping
Mind mapping is another type of cognitive mapping, sometimes referred to as semantic mapping,
idea mapping, or word webbing. It describes a variety of strategies designed to show how key words or
concepts are related to one another through graphic representations. Mind mapping techniques have been
used for centuries as a device to aide in brainstorming, visual thinking, and problem solving. Although
several people are currently credited with the creation of the modern mind map, Dr. Allan Collins is
widely know and credited through is work in the early 1960’s with mind mapping of semantic networks
of natural languages developed in the late 1950’s. Mind maps are structured around a central key word.
Like concept maps, relationships fork from this key word, but mind maps are typically more radial in
structure and concepts are arranged by order of importance. Each branch represents a conceptual
grouping of concepts for the topic. The non-linear structure of mind maps is said to promote non-linear
16
thought and encourage brainstorming and the realization of new ideas. Unlike concept maps, mind maps
do not distinguish between concepts (nodes) and the relationships between them (links). In mind maps
nodes and links are the same and are non-directional.
The following example is a mind map generated from a Wikipedia article on “Avionics”.
17
Figure 3 Sample Mind Map
18
2.2 .3 Dialogue Mapping
Dialogue Mapping is a visual representation of group communication. As the group’s discussion
of a particular topic unfolds, the map grows. This tool is to be used in a collaborative environment where
each participant can view a representation of the discussion so far. The map serves as a “group memory,”
to convey the discussion threads and dialogue paths used to make a decision on a particular topic.
The following example is a dialogue map regarding the “School Budget Decision”. This map
was made available from the Compendium Institute.
Figure 4 Sample Dialogue Map
19
CHAPTER III
ANALYSIS OF TOOLS
3 .1 Cogni t ive Mapping Tools
For each of the three different cognitive mapping paradigms discussed afore, there exists a wide
array of applications for which to use. We will not go into detail on every tool available; instead, we will
discuss the more popular ones for each type and choose the best tool and map for the system. For a list of
these resources, see Appendix B.
3.1 .1 Concept Mapping
3 .1 .1 .1 CmapTools
CmapTools is a freely downloadable software toolkit that facilitates the creation and
manipulation of Concept Maps. The toolkit is made available by the IHMC (Institute for Human and
Machine Cognition), a not-for-profit research institute affiliated with the Florida University System. The
toolkit is well designed and very intuitive, but it lacks the ability to import raw data types, like RDF
(Resource Description Framework), and does not provide an API (Application Programming Interface)
for interfacing via other software.
3.1 .2 Dialogue Mapping
3 .1 .2 .1 Compendium
Compendium is a software tool used to “provide a flexible visual interface for managing the
connections between information and ideas.” [Compendium, 2008] It is provided freely by the
Compendium Institute for non-commercial use. The application’s focus is on Dialogue Mapping,
specifically “visualizing the connections between people, ideas, and information at multiple levels, in
mapping discussions and debates, and what skills are needed to do so in a participatory manner that
20
engages all stakeholders.” [Compendium, 2008] In light of this, the dialogue mapping paradigm and its
tools, does not seem to be a good fit for the type of information we wish to convey for our system.
3.1 .3 Mind Mapping
3 .1 .3 .1 MindManager
MindManager, formerly MindMan, is an enterprise level mind mapping software application
commercially developed by Mindjet Corporation. MindManager is marketed for use as a commercial
application to provide services that allow teams to collaborate in real time. MindManager provides for its
license holders an open API for reading in data from RSS feeds or COTS applications such as Microsoft
Excel and Outlook. Although the MindManager API would be convenient for our needs, its cost and
focus towards corporate collaboration makes it prohibitive for our system.
3.1 .3 .2 FreeMind
FreeMind is a freely available, open source, mind mapping application licensed under the GNU
Public License. It is written in Java and its source code is available for download. These factors allow
FreeMind to be used and enhanced for our system via the Java API. Since it is written in Java, it can run
on any system via the Java Runtime Environment or be easily ported as an application accessible from a
web browser. The application provides multiple export formats and already integrates with most of the
popular wiki engines, including MediaWiki, the engine behind Wikipedia.
3.1 .3 .2 .1 FreeMind Flash Browser
Since FreeMind is open source software and is licensed under the GNU Public License (GPL),
developers are free to modify the code and publish their work. In fact, a group of artists and developers
have created a Flash browser for FreeMind and have released it under the GPL. Acting as a mini
browser, it handles browser events, such as clicking hyperlinks for navigation, allowing navigation
21
forward and back in history, and copying results to the clipboard. Map specific events are also handled,
such as the ability to unfold and fold all nodes, pan and zoom, and opening links in a new window. Since
it uses Flash as the container instead of Java, users can interface it via the Adobe Flash plugin, rather than
a more heavyweight Java applet running in a Java Runtime Environment. Its API is accessible via
JavaScript, allowing for easy integration to the View component of the system we are designing.
3.1 .4 Cogni t ive Mapping Conclus ion
“A Mind Map is a diagram used to represent words, ideas, tasks, or other items linked to and
arranged radially around a central key word or idea.” [Wikipedia/Mind-map, 2008] This is the paradigm
that fits best with the information we wish to convey, and of the three types of cognitive maps, a mind
map is the fastest and easiest to use. The FreeMind Flash browser is a very convenient, powerful, and
flexible tool for rendering cognitive maps from a given data source. For these reasons we shall use a
mind map as the model for the cognitive map and use the FreeMind Flash browser for its rendering.
3.2 Wikis
3 .2 .1 Platypus Wiki
Platypus Wiki is “a project to develop an enhanced Wiki Wiki Web with ideas borrowed from the
Semantic Web.” [Platypus, 2008] The Platypus Wiki software directs authors to encode semantic data
within wiki pages using RDF and Web Ontology Language (OWL). This is beneficial because articles
written for a Platypus Wiki will already have a semantic description of the underlying information
defined. This highly structured information can easily be rendered as a cognitive map without the need
for parsing the source text. Unfortunately, the model for the information in the article is established via
the inclusion of formal notation to the source by the authors. This action must occur manually upon the
creation, or update, of the article. At this time, this action cannot be performed programmatically after
the fact though many researchers are looking into this. Relying on the semantic information at this time
22
limits the scope and flexibility of our system. Only new articles written for this wiki could be used, thus
preventing the users of our system from having access to the millions of other wiki articles already
written elsewhere.
3.2 .2 MediaWiki
MediaWiki is “a free software wiki package originally written for Wikipedia. It is now used by
several other projects of the non-profit Wikimedia Foundation and by many other wikis.” [MediaWiki,
2008] MediaWiki provides a rich feature set and provides a mechanism for users to develop extensions
for additional functionality. Rich text content is also supported, allowing for the rendering of
mathematical formulas, graphs, musical notation, and foreign language notation. Such extensive features
and ease of use have made MediaWiki one of the most popular wiki software applications today, most
notably, through its use by Wikipedia.
3.2 .2 .1 Semantic MediaWiki
Semantic MediaWiki is an extension to MediaWiki. Semantic MediaWiki allows for the addition
of semantic annotations to wiki articles. Much like Platypus Wiki, these annotations need to be added to
the articles source to be used. Most available MediaWiki articles are not created using the Semantic
MediaWiki extension, so we face the same issues as discussed with Platypus Wiki.
3.2 .3 Wiki Conclusion
Due to the enormous volume of topics already published in Wikipedia and other popular wikis
that are also running MediaWiki, our system would be mostly beneficial if we target MediaWiki,
specifically Wikipedia, as the source material for our system. Almost none of these topics contain the
semantic annotations used by Semantic MediaWiki. This implies that in order to process these articles we
would require the system to have a means of parsing the wiki source text in a fashion that can be used for
rendering the topic in a mind map.
23
3.3 Source Pars ing Tools
3 .3 .1 Natural Language Process ing
One method we can apply to generate structure for our mind map would be to employ Natural
Language Parsing algorithms. Natural language parsing (NLP) is “a subfield of artificial intelligence and
computational linguistics. It studies the problems of automated generation and understanding of natural
human languages.” [Wikipedia/NLP, 2008] Using defined lexicons of a given language, NLP can process
the text of an article into an OWL ontology. This ontology can then be processed for its semantic
relationships and rendered by the mind mapping software.
3.3 .2 Structure Pars ing
Another method for parsing the content could be to ignore the semantic meaning of the text
altogether. If we were to consider that the main concepts of a well laid out article can be represented by
the structure of the article itself and its references to outside sources, then we can apply a simple
algorithm to parse this structure and describe the topic with a mind map regardless of the meaning of its
content.
3.3 .3 Source Pars ing Conclusion
The use of Natural Language Parsing is a science that can be written about extensively on its
own. Unfortunately, the complexities involved place it beyond the scope of the system we are defining
here. Additionally, this technology is difficult to deploy for the multiple languages prevalent in the wiki
communities and NLP cannot understand words that it has never seen before. A statistical based
language parser can help resolve this, but NLP based on statistics is less accurate and does not understand
words. The universal and light weight nature of the structure parsing approach makes it the best fit for the
process of parsing the wiki source text.
24
CHAPTER IV
WIKI-POWERED CONCEPT MAP DESIGN
4 .1 Scope
This system is being designed as an academic proof of concept. Its goal is to utilize established
standards and techniques in the field of knowledge modeling in a new and resourceful way. This initial
phase will interface COTS, Commercial Off-The-Shelf, products via their APIs using the Java
programming language.
Future phases will focus on limiting the use of COTS in favor of developing new algorithms to
have capabilities that further realize the goals of the system. Such capabilities may be the application of
natural language processing and the processing of additional data sources, such as raw text. Engines for
the rendering of other cognitive maps may also be developed for processing multiple types of content.
4.2 Des ign Process
The design for this system was performed using an object oriented approach. Analysis was
performed by identifying the use cases and detailing the flow of events for each. The Contextual,
Operational, Logical, and Physical aspects of the architecture are derived and explained in detail below.
4.2 .1 Requirements
Since this system is an academic proof of concept, there are no formal customer requirements;
therefore, all requirements have been derived though the analysis of the design. These requirements are
provided as follows:
Table 1 System Requirements
ID Description Search Engine Parser Map Browser
1 Any MediaWiki, including Wikipedia, shall be
searchable
X
2 Search wildcards shall be supported X
25
3 Multiple search results shall be handled X
4 MediaWiki disambiguation pages shall be handled X
5 NULL search results shall be handled X
6 MediaWiki error messages shall be handled X X
7 MediaWiki articles shall be processed
X
8 Mind maps shall be dynamically rendered
X
9 Mind maps shall be imbedded
X
10 Mind maps shall be exportable
X
11 Mind maps shall be browsable
X
12 Mind maps shall be bookmarked
X
13 Mind maps shall be panned
X
14 Mind maps shall be zoomed
X
15 Mind maps shall be refreshed
X
16 Mind maps shall be recentered
X
17 Mind maps shall link to source content
X
18 Mind maps shall collapsible
X
19 Mind maps shall expandable
X
4.2 .2 System Archi tecture
4 .2 .2 .1 Contextual
In this section, we shall perform the following:
• Purpose: Define the area of interest and its interactions
• Activities: Gather information, identify gaps and overlaps, resolve conflicts, set scope,
boundaries and quality attributes
26
• Artifacts:
o Interrogatives
o Context Diagrams
o Lists
4.2 .2 .1 .1 Interrogat ive Data
Scope the context of the architecture via interrogatives: why, who, what, how, where and when.
4.2 .2 .1 .1 .1 Why does the work need to be done? (Goals )
The work needs to be done because currently the concepts within the content of wiki articles are
loosely coupled and the relevance of the material and overall context is easily lost.
4.2 .2 .1 .1 .2 Who are the part ic ipants? (Stakeholders)
The participants of the system are the data analysts using the system to mine for pertinent
information and the content authors for whose data the system will interact.
4.2 .2 .1 .1 .3 What information and ent i t ies are used? (Data / Ent i t ies )
The data the system uses is the content of the bodies of the articles published to the wiki. The
articles in the wiki shall be accessible online for processing by the system.
4.2 .2 .1 .1 .4 How do they operate? (Processes )
A content processing component shall use algorithms to process the content of the wiki article
and produce a model of its structure.
A mapping component shall then render the structural data into a visual representation
corresponding to the layout of a mind map.
A browser component shall display the map and handle user driven events, such as refresh, zoom,
pan, and click.
27
4.2 .2 .1 .1 .5 Where do they operate? (Geography)
The system is web based, so by definition it is geographically agnostic. The cognitive mapping
system and the wiki server may reside on the same host or exist on separate systems. If on separate
systems, the two hosts must be able to communicate within their representative network.
4.2 .2 .1 .1 .6 When are the various act ions taken? (Timel ine)
An author publishes a wiki page in accordance to the markup language. They reference other
wiki articles or external sources and imbed media such as images, video, and audio. The user of the
system will perform a search on a particular topic of interest. The user will then select from the search
results. Each search result corresponds to a published wiki article. Upon selecting the search result, the
user is presented with a mind map of the content of the article. The user can select nodes in the map and
follow relationships to other content. The user can also choose to view the source content from which the
map was derived.
4.2 .2 .1 .1 .7 Relat ionship Matrix (Why vs . Who)
The analyst will want to discover relationships and relevance of the subject they are researching.
The author may wish to know that they have established the relationships they wish to present, but they
already believe their content is relevant, so would not use such a system to determine this.
Table 2 Relationship Matrix
Analyst Author
Display Relationships X X
Display Relevance X
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4.2 .2 .1 .2 Context Diagram
Scope the players involved in the architecture
Figure 5 Context Diagram
4 .2 .2 .1 .3 Scope and Boundaries
Define the attributes that identify the system’s scope and boundaries, i.e., the data and services
that will be provided by the system, and the ones that will be externally required. Define the scope and
boundaries from multiple viewpoints via an in/out list.
4.2 .2 .1 .3 .1 Del iverables
Define the outline of the system so that it is clear whether entities and actions near the perimeter
of the system are “in” or “out”.
29
4.2 .2 .1 .3 .1 .1 External
Table 3 External Deliverables
Topic In Out
Software license agreement X
Wiki Concept Map System software executables X
Wiki Concept Map System software source code X
User Documentation X
Requirements specification X
API documentation X
4.2 .2 .1 .3 .1 .2 Funct ional i ty
Table 4 Functionality Deliverables
Topic In Out
Interface any wiki X
Dynamically render mind-maps X
Cache maps in database X
Cache wiki articles in database X
Cache wiki data in database X
Support HTTPS (port 43) X
Support processing of non-English content X
Imbedded mind-map user interface X
Bookmark maps X
Deploy to any web server X
30
4.2 .2 .1 .3 .1 .3 Data
Table 5 Data Deliverables
Topic In Out
Process textual data X
Process imbedded media X
Process non-ASCII text X
Import external data from files X
Export to image X
Export to various mind-map COTS formats X
4.2 .2 .1 .3 .1 .4 Technica l S tructure
Table 6 Technical Deliverables
Topic In Out
Allow for remote wiki server X
Allow Wiki Concept Map System server and Wiki server (with database) on
same host
X
Server to be customer furnished X
4.2 .2 .1 .4 Qual i ty Attr ibutes
Support the evaluation and enhancement of the architecture in areas of key importance by
defining the properties which the architecture’s quality will be judged by the stakeholders.
Possible Attributes:
• Modular
• Open
31
• Standards Compliant
• Loosely Coupled
• Robust to Errors
• Functional
• Performance
• Maintainability
• Testability
• Reliability
• Efficiency
• Adaptability
• Usability
Table 7 Quality Pugh Chart
Modula
r
Open
Sta
ndard
s C
om
plia
nt
Loosely
Couple
d
Robust
to E
rrors
Functional
Perf
orm
ance
Main
tain
abili
ty
Testa
bili
ty
Relia
bili
ty
Eff
icie
ncy
Adapta
bili
ty
Usable
Ra
nk
Modular < ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ 1
Open ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ ^ 0
Standards Compliant < ^ ^ ^ ^ ^ ^ ^ ^ ^ 3
Loosely Coupled ^ ^ ^ ^ ^ ^ ^ ^ ^ 2
Robust to Errors < < < < ^ < < < 11
Functional < < < ^ < < ^ 9
Performance < < ^ < < ^ 8
Maintainability < ^ < ^ ^ 6
Testability ^ ^ ^ ^ 4
Reliability < < ^ 11
Efficiency ^ ^ 5
Adaptability ^ 7
Usable 11
32
Based on the results of the Pugh analysis of the set of attributes determined to be important to the
stakeholders, the top quality attributes (in no particular order) are:
• Robust to Errors
• Reliability
• Usable
4.2 .2 .2 Operat ional
In this section, we shall perform the following:
• Purpose: Describe the work that the system must do
• Activities: Identify actors and actions and describe their interactions
• Artifacts:
o Scenarios
o Use cases
o Activity Diagrams
4.2 .2 .2 .1 Operat ional Concept
• Mission: Construct cognitive map of a wiki article
• Capabilities: Contextual processing, Establish cognitive relationships, Automated layout
rendering engine, Interactive map interface
• Scenario: The user of the system will perform a search on a particular topic of interest. The
user will then select from the search results. The user is presented with a mind map of the
content of the article. The user can select nodes in the map and follow relationships to other
content or choose to view the source content from which the map was derived.
• Use Case: See below
33
4.2 .2 .2 .2 Key Scenarios
• Search for wiki articles
• Render mind-map of wiki article
• Browse linked wiki articles
• View original wiki article
4.2 .2 .2 .3 Actors
• Analyst
• Wiki
• Wiki Article
• Wiki Concept Map System
4.2 .2 .2 .4 Use Cases
Table 8 Use Case - Search for wiki articles
Description Search for wiki articles
Goal Return article or articles whose content matches the search criteria
Actors Analyst, Wiki, Wiki article, Wiki Concept Map System
Preconditions Wiki is accessible and contains published articles
Triggers N/A
Flows Basic: Browse to Wiki Concept Map System, enter search criteria in search
field, receive search results
Alternate: Browse to Wiki Concept Map System, enter search criteria in
search field, receive message indicating no results found
34
Exception: Browse to Wiki Concept Map System, enter invalid search
criteria in search field, receive error message from the system
Post Conditions N/A
Supplemental
Requirements
N/A
Table 9 Use Case - Render mind-map of wiki article
Description Render mind-map of wiki article
Goal Display the mind-map for a particular wiki article
Actors Analyst, Wiki, Wiki article, Wiki Concept Map System
Preconditions Wiki is accessible and contains published articles. Wiki search has returned
result(s).
Triggers N/A
Flows Basic: Select entry in the search results, view mind-map of selected wiki
article
Alternate: Select browser favorite (bookmark) of previously viewed map,
view mind-map of selected wiki article
Exception: Select entry in the search results, receive error message from
the system
Post Conditions N/A
Supplemental
Requirements
N/A
35
Table 10 Use Case - Browse linked wiki articles
Description Browse linked wiki articles
Goal Analyst can navigate from the current map to a linked article
Actors Analyst, Wiki, Wiki article, Wiki Concept Map System
Preconditions Wiki is accessible. Analyst is viewing the map of a published article. The
wiki article references other wiki article(s).
Triggers N/A
Flows Basic: Select linked article in mind map, receive mind map of linked article
Alternate: N/A
Exception: Select linked article in mind map, receive error message from
the system regarding page not found.
Post Conditions N/A
Supplemental
Requirements
N/A
Table 11 Use Case - View original wiki article
Description View original wiki article
Goal Analyst can view the original contents of the article from which the current
map is rendered
Actors Analyst, Wiki, Wiki article, Wiki Concept Map System
Preconditions Wiki is accessible. Analyst is viewing the map of a published article.
Triggers N/A
Flows Basic: Select center node of current mind-map, receive source wiki article
36
in current browser page
Alternate: Select center node of current mind-map while selecting hotkey
for a new tab, receive source wiki article in a new browser tab.
Exception: Select linked article in mind map, receive error message from
the system regarding page not found.
Post Conditions N/A
Supplemental
Requirements
N/A
37
4.2 .2 .2 .5 Act iv i ty Diagram
Model the logic captured by the use cases.
Figure 6 Activity Diagram
4 .2 .2 .3 Logical
In this section we shall perform the following:
• Purpose: Relate the structure of the solutions to the structure of the work to be done
• Activities: Decompose, aggregate and allocate, identify patterns
• Artifacts:
38
o Functional Decomposition Tree
o Logical Block diagrams
o Data flow diagrams
o Sequence diagrams
4.2 .2 .3 .1 Funct ional Decomposi t ion
Break down of the functional components of the system
Figure 7 Functional Decomposition Breakdown
4 .2 .2 .3 .2 Logica l Solut ion
The sequence of interactions required to use the system
1. Search wiki
2. Select search result
3. View mind-map
4. Select linked article
5. View wiki article
39
4.2 .2 .3 .3 Logica l Block Diagram
Logical relationships of the functional components of the system
Figure 8 Logical Block Diagram
4 .2 .2 .3 .4 Data Flow Diagram
Flow of data within the system
Figure 9 Data Flow Diagram
40
4.2 .2 .3 .5 Sequence Diagrams
Possible sequence of events in the system
4.2 .2 .3 .5 .1 Search and View Wiki Mind-map
Figure 10 Sequence Diagram - Search and View Wiki Mind-Map
4 .2 .2 .3 .5 .2 Browse Wiki Mind-map
Figure 11 Sequence Diagram - Browse Wiki Mind-Map
41
4.2 .2 .3 .5 .3 View Wiki Mind-map Source
Figure 12 Sequence Diagram - View Wiki Mind-Map Source
4 .2 .2 .3 .6 Evaluation
In evaluating the results of the logical breakdown against the quality attributes from the above
section, we see no indication that the logical model will not result in a system that is reliable, usable, and
robust to errors.
4.2 .2 .4 Physica l
In this section, we shall perform the following:
• Purpose: Define the physical attributes and organization of the system
• Activities: Allocate, partition, define interfaces, select technical approaches
• Artifacts:
o Block diagrams
o Weighted matrices
o Interface definitions
o Data schema
42
4.2 .2 .4 .1 Phys ica l Components
4 .2 .2 .4 .1 .1 Hardware
• System Server
• Wiki Server
• Server Rack
• Server Room
• Workstation
• Network Infrastructure
4.2 .2 .4 .1 .2 Sof tware
• Application Server
• Browser
• Adobe Flash browser plugin
• System Executables
• Java Runtime Environment
• FreeMind Flash browser
• MediaWiki Application
4.2 .2 .4 .1 .3 Data
• Published Wiki Articles
4.2 .2 .4 .1 .4 Interface
• HTTP Protocol
43
4.2 .2 .4 .2 Phys ica l Approach
The physical approach is to connect a physical web server to the same network that has access to
the wiki. The server may be installed in a rack in a server room in order to handle high traffic volume, or
run on a workstation for limited individual use. The system may or may not be installed to the same
physical server as the wiki. It is required that the network infrastructure be in place for the system server
to communicate with the wiki server. Users shall access the system via a workstation.
4.2 .2 .4 .3 Stat ic View of Physica l System
Figure 13 Physical System
4 .2 .2 .4 .4 Trade of approaches to qual i ty at tr ibutes
4 .2 .2 .4 .4 .1 Usabi l i ty
IEEE defines usability as, “the ease with which a user can learn to operate, prepare inputs for, and
interpret outputs of a system or component.” [IEEE, 1990]
The architecture provided allows for the presentation layer to be customizable to the extent that
the resulting map is understandable and navigable. Language is derived from the source content and
should be considered clear and simple in respect to the context of the subject. The presentation layer shall
44
provide the mechanisms to allow the user to navigate within the map, or follow relationships to other
subjects.
4.2 .2 .4 .4 .2 Robust
As defined in Wikipedia, a robust architecture “is said to be one that exhibits an optimal degree of
fault-tolerance, backward compatibility, forward compatibility, extensibility, reliability, maintainability,
availability, serviceability, usability, and such other quality attributes as necessary and/or desirable.”
[Wikipedia/SA, 2008]
IEEE defines robustness as, “the degree to which a system or component can function correctly in
the presence of invalid inputs or stressful environment conditions.” [IEEE, 1990]
Data for the system is derived from published wiki articles. Maps of such articles are rendered
dynamically. In the event that a search does not return any results, no map based on the users search
criteria will be rendered. Search results in the system are dependent on information published to the wiki.
If for any reason the data is unsearchable; the system could not be used. Certain methods to remove this
coupling may include the pre-processing and caching of wiki articles. Such a design introduces additional
requirements for increased storage and synchronization. Resolution of these issues shall be considered in
future phases.
4.2 .2 .4 .4 .3 Rel iabi l i ty
IEEE defines reliability as “the ability of a system or component to perform its required functions
under stated conditions for a specified period of time.” [IEEE, 1990]
For this system, the biggest factor of reliability is that when a user selects a link, either in the
search results, or navigating the mind-map, that the system responds with pertinent information. The
W3C (World Wide Web Consortium) states that, “successful link traversal generally means finding a
resource with perfect precision and recall, and retrieving an authentic representation of the resource in a
45
timely fashion, i.e. with sufficiently low latency.” [W3C, 2008] In a web application, successful link
traversal correlates to the application’s reliability.
Successful link traversal within the system is dependent on the validity of the information
published to the wiki. If for any reason the linked data is unreachable; the system could not be used.
Certain methods to remove this coupling may include the implementation of a web crawler to validate
links within source material. Such a design introduces additional requirements for increased processing.
Resolution of these issues shall be considered in future phases.
46
CHAPTER V
System Mockup
5 .1 Search and View Wiki Mind-map
5 .1 .1 Opening Page
As defined in the architecture, the system is accessed via a web browser and is configured to
search a particular wiki, in this example Wikipedia. The interface to the system may appear like the
mockup below. A simple Google-like form is presented containing a single text field to enter search
criteria.
Figure 14 Mockup Opening Page
47
5.1 .2 Search and View Resul ts
For our case, we have entered a search for the topic “Avionics”. Using the MediaWiki API, we
submit our search criteria to Wikipedia and receive the topic page as a result. Internally, the context
parser processes the source text and submits the information to the FreeMind Flash browser which is
imbedded in page below the search form. The FreeMind Flash browser constructs the mind map from the
data and displays it to the user within the browser.
Figure 15 Mockup Search and View Results
48
5.1 .3 Search the Contents of the Map
The integrated FreeMind Flash browser allows us to search within the map itself. A text field is
provided where the search criteria is entered. Upon submitting the criteria, the first field that matches the
criteria is highlighted. Resubmitting the search will result in the next match being highlighted, etc.
Figure 16 Mockup Search the Contents of the Map
49
5.2 Browse Wiki Mind-map
The integrated FreeMind Flash browser allows us to navigate the map. Functions for pan, and
zoom are provided.
5.2 .1 Expand the Nodes
The initial map presented by the browser has all branches of the nodes fully collapsed. This
presents to the user the main structure of the article. The user can then expand all the nodes or choose to
drill down a particular path. Selecting the “+” will expand the next level below the selected node. In our
example “Main categories” has been expanded and all the child nodes are presented.
Figure 17 Mockup Expand the First Level Node
50
Nodes can contain other nodes or be leaf nodes that can no longer be expanded. In our example,
we further drill down by expanding the node “Aircraft avionics”. This node represents one of the many
main categories within the article. All of the child nodes within “Aircraft avionics” are leaf nodes and
cannot be further expanded.
Figure 18 Mockup Expand Second Level Node
51
5.3 View Wiki Mind-map Source
5 .3 .1 View Main Topic
As with all mind-maps, the topic of the map, the term that we searched by, is signified by the
center node. This correlates to the top level, or main topic, of the wiki article. If we wish to view the
contents of the article starting at the top level, simply select the node in the browser.
Figure 19 Mockup Select Main Topic
The FreeMind Flash browser handles the event and in a new browser window displays the wiki
page at the location of the node selected, in this case the top level.
52
Figure 20 Mockup View Main Topic
53
5.3 .2 View Categories
Any node in the map can be selected in the browser to show the content. Nodes in the map
surrounded by a border correspond to distinct sections in the Wikipedia article. For example, selecting
the node “Aircraft avionics” will present to us, in a new window, the Wikipedia article at the
corresponding category, or chapter.
Figure 21 Mockup Select Category
The FreeMind Flash browser handles the event and in a new browser window displays the wiki
page at the location of the node selected, in this case “Aircraft avionics”.
.
54
Figure 22 Mockup View Category
55
5.3 .3 View Linked Topic
Not all nodes correspond to sections in the article matching the topic. Links within the source
article that link to other Wikipedia topics are also rendered as nodes in the mind map. These nodes are
indicated on the map by a green double-arrow icon. For example, selecting the node “direct current / DC”
will present to us, in a new window, the Wikipedia article matching that topic.
Figure 23 Mockup Select Linked Topic
The FreeMind Flash browser handles the event and in a new browser window displays the wiki
article for the node selected, in this case “Direct Current”.
56
Figure 24 Mockup View Linked Topic
57
5.3 .4 View External Page
Not all links in Wikipedia link to other Wikipedia topics. Links to external sites are also rendered
as nodes in the mind map. External links are identified by the system by noting that the domain in the
link’s URL (Uniform Resource Locator) is different than the domain of the wiki in which we are
searching. External links can be distinguished by the icon of an arrow pointing away from a page. For
example, selecting the node “400Hz Electrical Systems” will present to us, in a new window, the external
page referenced by the link in the article.
Figure 25 Mockup Select External Page
58
The FreeMind Flash browser handles the event and in a new browser window displays the
external page linked in the Wikipedia article, in this case the site referenced by the link having the label
“400Hz Electrical Systems”.
Figure 26 Mockup View External Page
59
CHAPTER VI
SUMMARY AND CONCLUSIONS
Mind mapping is a technique for visually organizing and working with information. It is used as
a tool to aid in creativity, organization, productivity, and memory. Mind mapping can help capture ideas,
organize, prioritize, and visualize complex information. This technique can be used to work with both the
big picture and the details of a specific topic. It can reveal potential connections and where there is a
need for additional information. Mind mapping is a useful tool for any project involving large amounts of
information, including, research, writing, brainstorming, and project planning and management. One area
that many of these fields describe, and where mind maps can be particularly beneficial, is the analysis of
published wiki articles.
Traditionally mind maps were created by hand on a piece of paper. Naturally this process has
been enhanced through the use of commercial software such as MindManager, or open source software
such as FreeMind. Although very useful, these tools still require us to manually construct the mind map.
This paper describes a design for a light weight system, using existing technologies, that automatically
generates mind maps from a given data source, specifically Wikipedia articles.
As technology continues to progress in the fields of cognitive mapping and language processing,
it is certain that ideas such as those presented here will be further expanded upon. Future versions may
include the integration of natural language processing such that the relationships within the granularity of
individual lexicons can be derived and mapped. The relationship between a text and its map may even
become bi-directional, where not only does text generate a mind map, but modifications to the map also
modify the source text. Systems such as this will help automate the visualization of complex information
and eventually play a role in its organization and publication, thus facilitating the spread of information.
60
REFERENCES
1. [Wikipedia/Wiki, 2008] Wikipedia Website: http://en.wikipedia.org/wiki/Wiki.
2. [Wikipedia/Mind-map, 2008] Wikipedia Website:
http://en.wikipedia.org/wiki/Mind_map.
3. [Wikipedia/RDF, 2008] Wikipedia Website:
http://en.wikipedia.org/wiki/Resource_Description_Framework.
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Computer Glossaries. (New York, NY: 1990).
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http://en.wikipedia.org/wiki/Systems_architecture.
6. [W3C, 2008] The World Wide Web Consortium (W3C) Website:
http://www.w3.org/Propagation/reliable-links.html.
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Bo Leuf andWard Cunningham, Publisher: Addison-Wesley, Boston, 2001.
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10. [Downs and Stea, 2005] Image and Environment: Cognitive Mapping and Spatial
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Novak and D. Bob Gowin, Publisher: Cambridge University Press, Cambridge, 1984.
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http://compendium.open.ac.uk/institute/.
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15. [MediaWiki, 2008] MediaWiki Website: http://www.mediawiki.org/wiki/MediaWiki.
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http://en.wikipedia.org/wiki/Natural_language_processing.
61
APPENDIX A
ACRONYM LIST
Acronym Definition
ASCII American Standard Code for Information Interchange
API Application Programming Interface
COTS Commercial Off-The-Shelf
GNU GNU’s Not Unix
GPL GNU Public License
HTML HyperText Markup Language
HTTP HyperText Transfer Protocol
HTTPS HTTP over SSL
IEEE Institute of Electrical and Electronics Engineers
IHMC Institute for Human & Machine Cognition
JRE Java Runtime Environment
NLP Natural Language Processing
OWL Web Ontology Language
RDF Resource Description Framework
RSS Really Simple Syndication
SSL Secure Socket Layer
URL Uniform Resource Locator
W3C World Wide Web Consortium
62
APPENDIX B
RESOURCE LIST
• Adobe Flash Plugin: http://www.adobe.com/products/flashplayer/
• Compendium Institute: http://compendium.open.ac.uk/institute//index.htm
• FreeMind: http://freemind.sourceforge.net/wiki/index.php/Main_Page
• FreeMind Flash Browser: http://www.efectokiwano.net/mm/
• IEEE: http://www.ieee.org/portal/site
• IHMC CMapTools: http://cmap.ihmc.us/Index.html
• Java Runtime Environment: http://www.java.com/en/
• MediaWiki: http://www.mediawiki.org/wiki/MediaWiki
• Mindjet MindManager:
http://www.mindjet.com/products/mindmanager_pro/default.aspx
• Platypus Wiki: http://platypuswiki.sourceforge.net
• Semantic MediaWiki: http://semantic-mediawiki.org/wiki/Semantic_MediaWiki
• W3C: http://www.w3.org
• Wikipedia: http://en.wikipedia.org/wiki/Main_Page
• WikiMindMap: http://www.wikimindmap.org
• WordNet: http://wordnet.princeton.edu/
