Thursday, May 28, 2009

Mind Maps

    In 70’s Tony Buzan coined the term of Mind Map for his visual tool based on “radiant thinking” principle, cataloguing it as a “powerful graphing technique”, “expression of radiant thinking” or “a natural function of human mind”. He made public the concept in his first book on Mind Maps that appeared in 1974, “Use Your Head”, one year later appearing “The Mind Map Book”, over the years, if we give credit to [3], the number of books reached 85, being sold over 5 millions copies worldwide, in 100 countries and translated in 30 languages. Quite impressive, isn’t it?!

    A Mind Map is centred on a single idea (in some sources referred as topic, subject, theme or question), other ideas being associated to it in a radial fashion, resulting in the end a Map of ideas, from here the alternative denomination of Idea Map. “Idea” is maybe a too general term because it can represent a thought, concept or a statement in which multiple concepts are used. In most of the Mind Maps met, ideas are expressed in the form of Key-Words, and sometimes of symbols or images, especially on digital Maps. A Key-Word is supposed to encapsulate “a multitude of meanings in as small a unit as possible” [1], thus ideas reach to be expressed as single words, each word being the label in a hierarchical network. Maybe an example will make some light, so supposing that “Happiness” is the central idea, we can associate to it words that we relate in our mind to Happiness: “family”, “good job”, “free time”, “money”, “love”, “vacation”, etc. Each of these ideas can be further extended with other associations, “family” could be associated for example with the name of “wife”/”wives”, “husband(s)”, “kid(s)”, “dog(s)”, “parents” and “grandparents”, “cat(s)” and any other pats we consider to be part of the family. A “good job” presumes “good remuneration”, “appreciation”, “good boss”, “nice colleagues”, “nice environment”, “potential”, etc. “Free time” could include all the activities somebody likes to have in his/her free time; same exercise can be done for each idea included in the Map, ideas can be associated over and over again with other ideas. It seems like a never ending story… when do we stop then? Most probably when the paper ends or we get bored, these are two possible answers too, in the end it’s up to each person, how detailed he wants the Map, what he/she wants to achieve, etc.

Happiness – Mind Map created with FreeMind Happiness – Mind Map created with FreeMind

    A Mind Map can be regarded as a tree, in which the trunk represents the topic, the labelled leaves represent ideas, the forked branches themselves supporting the whole structure of the tree, their multiple forking representing the degree of detail the Map holds. The comparison with a tree is not accidental, tree-like drawings has been used since Antiquity to encode meaning (e.g. Tree of Life, Tree of Love), moreover representational purpose can be given also to the roots of the tree for example to represent base or fundamental ideas on which the whole foundation is built. Unlike trees, it could happen for example that two ideas from different braches can be associated too, for example “money” with “good job” resulting cross links between ideas. With each cross-links added the structure of the Map changes, becoming more like a network, though still relying on previous radial structure which becomes the Map’s backbone. Network-like Maps are more natural to represent knowledge, as knowledge has a networked rather than hierarchical structure.

    A Map can go through multiple stages, iterations if you want, some ideas are deleted, others added, new associations are made, techniques are improved, and so on. Therefore such Maps are evolutional, they can change over time as people identify new associations, acquire new information or knowledge, change their values, change themselves and even their way of thinking…Excepting the radial disposition of ideas there are theoretically no other constraints, people can use their imagination and built all kind of Maps. Moreover, people can use visual rhythm, patterns, colour or spatial awareness (dimension and gestalt) to make Mind Maps easier to read, understand or navigate. Somebody can use his artistic talent and make a kind of piece of art from a Map, with a little imagination and skill a 2D Map can become 3D. In T. Buzan’s books you can find lot of propaganda for the use of Mind Maps and the benefits of its various characteristics together with references to (important) studies concerning learning and brain/mind theories.

    A Map generally can be created by multiple people, the addition of ideas can be done independently or through consensus, the collective work can start from an idea, an already existing Map or the augmentation of all involved people’s Maps. Such collective or collaborative Maps can be used for example in learning or brainstorming, consensus playing an important role, and for example in a digital Map can be seen how the Map itself evolved and eventually also how the consensus was reached. [2] considers that there are 250 million Mind Mappers all over the world, jumping over the basis used for this consideration, even if their number raises up to several millions, that’s quite a number. Many Mind Mappers buy rich-functionality software tools for drawing digital Mind Maps, others resume to less rich functionality but free tools, they integrated the technique in everyday life, learning, teaching, presentations, decision-making, etc. It’s a form of knowledge representation, though the creation of Mind Maps is mainly for personal use, even if many Maps are available already in the public domain.

    On the other side researchers occupy their time by building more or less complete ontologies, above their other characteristics, they imply consensus and quite an effort and coordination. Why not take advantage of the impressive number of Mind/Knowledge Mappers, give them rich and free software tools, and allow them to make explicit their knowledge or map the knowledge available on the Web?! Is the idea plausible?! How many of you haven’t underlined words or phrases of interest in a book or article creating thus bookmarks?! How many of you tried to built a mental image (Map) of how they fit together or into the existing knowledge? If we consider the “success” of folksonomies, of Knowledge Maps themselves, the increasing number of Web Sites and blogs on this topic, I am strongly convinced that the transition from folksonomies to Maps will happen pretty soon, once the Web Technologies in particular and Web’s evolution in general will allow that.

[1] Buzan, T. (1991). Speed Reading. Ed: 3rd Plume. ISBN: 978-0452266049
[2] Buzan, T., Buzan, B. (2007). The Mind Map Book. BBC ACTIVE. ISBN: 978-1-406-6102
[3] (2008). Tony Buzan. [Online] Available from: (Accessed: 29 May 2009)

Sunday, May 17, 2009

Utilizing Mind Maps as a Structure for Mining the Semantic Web

    In the past 2 and half years I followed the Online Masters Programme of University of Liverpool, it was intriguing, fun, time consuming and quite an effort as energy, money and personal life, and I hope it will pay back in time, the sooner the better. The modules were quite entertaining, I learn lot of new stuff and two years passed fast and slower than expected, then the dissertation came and things got pretty tough as I wanted to make it useful for me, to learn something meaningful on which I can built in the future and not something that will rot in a corner of the brain. I was not sure what to choose and frankly not even what I supposed to do.

    During the last modules I had the chance to read some material on Tony Buzan’s Mind Maps and it looked intriguing, I wish I had have read that stuff long time ago, but in the end better later than never. Why I found Mind Maps intriguing? First because they allow taking notes in a radiant fashion rather than using the old fashioned linear approach, by starting with a single idea (also referred as concept, subject, question) and built around it a whole Map using associations. In Mind Maps Key-Words are used to encapsulate a variety of meaning in smallest possible units, this step allowing some information filtering and processing, “obligating” the brain to actually integrate the new information in existing knowledge and represent already existing knowledge, identifying missing links, triggering other questions, etc. Thus on a piece of paper or in a electronic document, somebody can represent how concepts in a read material link to each other, making the subject clearer and I think easier to memorize and recall. Mind Maps can be also used to give life to own mental representations, as we all have created, voluntarily or involuntarily and map of the world we live in. Secondly, Mind Maps use symbols and graphical images, visual rhythms and patterns, colour and spatial awareness (dimension and gestalt), allowing people to take advantage of a broader set of cortical skills.

    Given these characteristics, Mind Maps seems to be perfect tools for Knowledge Representation in particular and Knowledge Management in general. During the Web Applications module I tangentially learned about XTM (eXtensible Topic Maps) and ontologies for Knowledge Representation, though ontologies call for experts and come with many issues, while XTM is a standard for Knowledge Interchange and targets internal representation in computers. On the other side digital Mind Maps are more flexible than ontologies, target a broader range of users, have the potential of harnessing the Collective Intelligence, one of Web 2.0’s competences, by allowing users to map their knowledge or the knowledge existing on the Web in documents. This is how appeared the title of my Dissertation paper, “Utilizing Mind Maps as a Structure for Mining the Semantic Web”.

    While diving in the subject, I found out that Mind Maps are just one of the Knowledge Maps used for various tasks, a search trough the literature revealing about 50 terms used to designate various types of Maps: argument maps, brace maps , bridge maps, bubble maps, causal maps, circle maps, cluster maps, cluster vee diagrams, clustering, cognitive maps, concept circle diagrams, concept maps, conceptual graphs, congregate maps, diagnostic maps, double bubble maps, dynamic cognitive maps, ecological maps, extended fuzzy cognitive maps, flow maps, frames, fuzzy cognitive maps, fuzzy relational maps, group maps, historical maps, idea maps, knowledge maps, mental maps, mind maps, multi-flow maps, neural cognitive maps, neutrosophic cognitive maps, node-link mappings, ontology, oval maps, probability fuzzy cognitive maps, rule-based fuzzy cognitive maps, semantic maps, semantic nets, semantic networks, shared maps, social maps, social mess maps, spider maps, strategy maps, taxonomy, text graphs, thinking maps, tree maps and virtual maps. Actually, the list might be much bigger, I expect I left out by mistake several terms, while on others I haven’t came across them until now.

    From several considerations, I preferred to treat the subject from the perspective of Knowledge Maps, so maybe a better title for my paper would have been “Utilizing Knowledge Maps as a Structure for Mining the Semantic Web”. As I found out later this cost me a huge amount of time and effort, I longed for more I could chew in the dedicated amount of time for a Dissertation paper, not having the time to bring the paper to the desired final form, letting out some research material and ideas. Anyway, now it’s over, good or bad the paper is finished and waiting for the final results. With this blog I’m hoping to bring into light some of the ideas I couldn’t put in the paper, help me do to further research into the subject and hopefully get also some feedback.

    I’m not sure yet whether I can put the paper in the public domain, therefore here is paper’s Table of Contents, with the mention that some of the topics (e.g. Fuzzy Cognitive Map) have only an informative character.

1. The Web
1.1 Introduction
1.2 Web 2.0
1.3 The Semantic Web
1.4 Semantic Web Problems
1.5 Beyond the Semantic Web
1.5.1 The Noosphere
1.5.2 Cognitive Machines
2. Philosophical Grounds
2.1 Introduction
2.2 From Meaning to Concept
2.3 Syntax, Semantics and Pragmatics
2.4 From data to wisdom
2.5 Types of Knowledge
2.6 Connectivism
2.6.1 Introduction
2.6.2 Chaos
2.6.3 Network
2.6.4 Complexity
2.6.5 Self-organization
2.7 Intelligence and Collective Intelligence
2.7.1 Intelligence
2.7.2 Collective Intelligence
2.7.3 Collective Web Intelligence
2.7.4 Web Technologies and Collective Intelligence
2.7.5 Offline Collective Intelligence
2.7.6. Collective Intelligence Forms
3. Knowledge Management
3.1 Introduction
3.2 Knowledge Representation
3.2.1 Introduction
3.2.2 Sub-conceptual level
3.2.3 Symbolic level Generalities The Frame Problem The Symbol Grounding Problem
3.2.4 Conceptual level
3.2.5 Associationist level
3.2.6 Semantic level
3.3 From Mental Models to Knowledge Representation Structures
3.4 Historical Overview
3.5 Vocabularies
3.5.1 Controlled Vocabularies Introduction Indexing Schemes Classification schemes Thesauri Taxonomies
3.5.2 Uncontrolled Vocabularies Introduction Folksonomies
3.6 Maps
3.6.1 Introduction
3.6.2 Semantic Nets
3.6.3 Frames
3.6.4 Mind Maps
3.6.5 Conceptual Graphs
3.6.6 Concept Maps
3.6.7 Neural Networks
3.6.8 Cognitive Maps
3.6.9 Fuzzy Cognitive Maps Fuzzy Cognitive Maps Rule-Based Fuzzy Cognitive Maps Extended Fuzzy Cognitive Maps Dynamic Cognitive Networks Neural Cognitive Map Neutrosophic Cognitive Maps Probability Fuzzy Cognitive Maps Fuzzy Relational Maps
3.6.10 Knowledge Maps
3.6.11 Topic Maps
3.6.12 Ontologies Ontologies Ontology Engineering
3.6.13 Other Knowledge Representation Structures
3.7 Analyzing Maps
3.7.1 Structural Comparison
3.7.2 Map Engineering
3.7.3 Mapping Tools
3.8 Harnessing Collective Intelligence for Knowledge Mapping
4. Data Mining the Semantic Web
4.1 Web Data Mining
4.2 Document Processing
4.3 The Case for Knowledge Representation Structures as Metadata
4.4. The Conceptual Knowledge Base
4.4.1 Introduction
4.4.2 Representational Elements of a Map
4.4.3 Operations with Maps
4.5 Mapping Descriptive Knowledge with Maps
4.5 Concepts in Documents’ classification
4.5.1 Introduction
4.5.2 Concept-Based Information Retrieval
4.5.3 Concept-Based Document Classification
5. Conclusions, Critics and Further Research
6 Appendix
6.2 References:

Tuesday, May 5, 2009

Network Theory Seminar with Tim Berners-Lee

    A must read seminar lecture with Tim Berners-Lee about Web, how it was born and evolved. It includes also a superb road map of the Web.
    The video is part of YouTube Edu, a collection of educational video, a more than welcomed initiative.