31 December 2010

Meta-Blogging: The Web of Knowledge – Past, Present and Future

Introduction (common to both blogs)

Even if I started to blog 3-4 years ago, only this year (still 2010) I started to allocate more time for blogging, having two blogs on which I try to post something periodically: SQL Troubles and The Web of Knowledge plus a homonym Facebook supporting group (for the later blog). As a parenthesis, the two blogs are approaching related topics from different perspective, the first focusing on data related topics, while the second approaching data from knowledge and web perspective; because several posts qualify for both blogs, I was thinking to merge the two blogs, though given the different perspectives and types of domains that deal with them, at least for the moment I’ll keep them apart. Closing the parenthesis, I would like to point out that I would love to allocate more time though I have to balance between blogging, my professional and personal life, and even if the three have many points in common, some delimitation it’s necessary. Because it’s the end of a year, I was thinking that it’s maybe the best time to draw the line and analyze the achievements of the previous year and the expectations for the next year(s), for each of the two blogs. So here are my thoughts:


Past and Present

As I highlighted long time before, I started this blog from the desire of learning and fantasizing more about Knowledge Representation, Knowledge Management, Semantic Web and other knowledge or Web-related topics. Unfortunately, from several reasons, the other blog monopolized most of my blogging time, so I can’t say I was too active in here, preferring to use the little time I had more for researching and reading on the above mentioned topic. I arrived thus to build myself a small library of books and papers, however the depth of the topics requires more study, time I’ll hopefully have in the near future. Step by step I’ll arrive also there!

If I’m looking at the posts from this year, most of them were on Knowledge Representation tools, starting a set of posts on Knowledge Maps, following to post additional material during the coming year(s). The material is basic and has a low degree of abstraction, this also because is not so easy to conceptualize my ideas and anchor them in existing theories. In addition, despite the several decades of research literature on this topic (actually some important steps were made starting the 70’s), there are many ideas and attempts, but it looks like everybody’s trying in vain to come with the next big thing. Most probably the following quote describes the best the current state of art even if it refers only to AI it  could be applied by extension to the whole Web ecosystem:

“[…] the crux for AI is that no one has been able to formulate in a reasonable way the problem of finding the good representaon, so that it can be tackled by an AI system” (Newell, 1982)

Anyway, that’s less important as long the topic fascinates me. For the moment it’s of interest especially the learning connotation attributed to KR tools, following with time to place them in Web context. Following the same goals, more recently I started to be more active in the Facebook homonym supporting group, posting quotes, links and thoughts on related topics, attempting to build a community around the blog, get more feedback and harness the knowledge of its members. It’s a long way to go, though in everything there is a start.

 

Future
In what concerns the Web and its future versions, the future looks great even if we see it more though its potentiality. As for me, I hope I’ll have more time allocated for this blog, hopefully arriving to reach an average of 1 post every two weeks. The topics will remain the same, in a first phase attempting to write more on the various tools used for KR, until today arriving to find out about more than 60 tools used for this purpose, plus many other techniques used in various domains (IT in general, and Project Management in particular). 

There is more to write about Knowledge Management, which in theory is nothing more than an extension of Data Management topic, which I attempt to approach in my other blog. I’m intending to dive also in the theory of complex networks, systems, ecologies, logic, semantics, etc. As I highlighted in a similar post from the other blog, I’ll attempt to post also my notes on the respective topics - that won’t be easy, though not impossible. Let’s not go too far and take one piece at a time.

Note:
   Probably some of the readers ask themselves why I’m studying so much about knowledge when the primary intended topic for this blog was supposed to be “the knowledge on the Web”. The point is that we need to understand the various types of knowledge available, the way knowledge could be represented offline and online, and then probably we could make most of the process, and build the tools that will allow us to harness the collective knowledge and intelligence.


   I close here, hoping that the coming year (2011) will be much better than the current one. I wish to all of you, a Happy New Year!

20 November 2010

Cognitive Science: Collaboration at Work - The IMD Contest

Yesterday a good friend of mine asked me to help her get votes in a contest launched by IMD, so after doing that I arrived to join the contest too, and not only for the prizes totalizing a number of 9 iPads to which, for the first two places, adds also a place within IMD OWP Program, respectively 3 World Competitiveness Packages, whatever they mean. What is interesting in this contest is that in a total of three steps, excepting the first step comprising a set of 20 general questions related to politics and business, and the third step, in which people have to match a set of image pairs representing pioneers in a field and their discovery, the second step involves a collaborative task. Namely, people have to compose a statement of maximum of 300 characters with the subject “Imagine you could be someone else for one week.  Who would you be and why”.  The collaboration resides in mobilizing your friends and acquaintances to vote you, they could vote you once per day, the vote being anonym so no need for them to login or join the contest, unless they really want to.

Even more interesting is the fact that not only the individuals are competing but also the groups/communities they are belonging to are competing against each other, and could happen that two or more members of a group compete against each other, stirring a conflict of interests and eventually some divisions with the group, but that’s less important for this post. To use a mathematical syntagm I learned during the course of Linear Programming done in university, I was wondering what’s the optimum solution in this case. Unfortunately there are a few years gone since University and the few classes on Game Theory and Linear Programming done in school are somewhere in a dick fog. So, I tried to approach the problem logically: what’s the best choice for a given group of groups to win the 9 prices?!

 Intuitively it seems that the best win-win situation is when all the winners are belonging to the same group, and let’s say that the group contains only 9 members. Each day each member will receive 9-1=8 votes (a person can’t vote for himself), which for the next 75 days of contest cumulates to 600 votes, which I bet will be more than some of the winners of the prices will win in the end currently. Why 9 members and not more? Because each member added to a group, means that one member of the group will not win, and as I suppose that all the people want to win, the conflict of interests could lead people to sabotage the voting. On the other side several members could sacrifice themselves for the sake of their friends and let’s say they will vote daily without taking part in the contest, thus resulting (n-1) votes for each of the 9 members, each day.  It’s quite a simple formula:

Total number of votes = number of days * (number of members-1)
Voters
The numbers are ideal ignoring the situations in which one of the members won’t vote and don’t include the additional votes added by other people, external to the group, who like the quote.

A special case of such type of group in which the number of members is greater than the number of winners could be formed for example by the families of the people winning the contest, thus if each family would comprise two members, let’s say husband and wife, the number of votes would be then multiplied again by 9 (just multiply the above numbers by 9). This is the perfect scenario because once a family wins the contest, both husbands will take eventually advantage of the won iPad. There are more variations on this subject, for example when also the members of the family of the competitor participate, in such case the winning group would be ideal when the family of its members is as bigger as it gets.

I wonder how many of competitors use any of the above approaches. I have several reasons to believe that this won’t happen, but who knows?! Anyway, you are free to join the contest and even vote my quote (here), if you like it. Any vote counts and it’s more than appreciated!

PS: The funny thing about voting contests on Internet is that the participants could easily break the rules voting more times per day by using dynamic IP addresses combined with other techniques. On the other side, the trickery could be found if the organizers are having the adequate mechanisms in place. If I remember correctly, there were such cases in the past when surveys or contests were in this way tricked, in several cases the trickery was discovered. Be careful, after the deed, and retribution!

Web x.0: The Wisdom of the Crowds (Part I - Is there any Wisdom?)

I haven’t managed to read until today “The Wisdom of the Crowds”, James Surowiecki’s well mediatized book, though it’s almost impossible to read an article or book on collaboration without meeting at least a small reference to it, if not a quote from it. Through the quotes met on the web I arrived to grasp a little from Surowiecki’s philosophy, and even if I it’s not the same as the read itself, I decided to write this post before reading the book, attempting to see how much my ideas changed after reading it.

I have the feeling that many have misunderstood maybe what knowledge and wisdom is about, how things are harnessed and evolve in life. Many bloggers, reputed writers and philosophers, believe that the crowds, sometimes referred as the masses or the mob, can’t be wise but rather stupid, thus appeared terms like stupidity of the masses, madness of the masses, etc. They are not so far away from the truth, especially when they are referring to the uneducated masses or to the panic-like effects, however the reality is that even a simple person who worked the land all his life or any did any other type of work and had no time for school could have more wisdom than a phony intellectual who spent all his life on the banks of schools without achieving a grain of wisdom or even knowledge. 

Again, with the risk of repeating myself, and as many have stressed, data is not information, information is not knowledge, and knowledge is not wisdom, the scale in this order implying a refinement and evolution of the thought process. Wisdom is a Holy Grail, and this not only in respect to spiritual life, but also to daily professional life, as it implies going above the knowledge existing in a certain field, either managerial, engineering, a simple job that pays the rent or any other activity. A simple person could hold his own grain of wisdom valid in his world, and with the eyes of an open mind and some chunk of knowledge from other domains, he might see the patterns a more educated person can’t grasp. For sure such a statement can’t be digested by researchers, especially when it’s almost impossible to express and measure wisdom, being more like a Morgan le Fay. It seems that is more important to touch the rays of wisdom, however it’s difficult to delimit where ends knowledge and begins wisdom, plus the various facets of the two, and from here the almighty confusion.  

Even if it’s difficult to believe that wisdom could be found at the fingertips of everybody, in definitive each person brings a different range of experiences, data, information and knowledge, different perspective of the same story, different cultural, social, geographical and cognitive aspects, in other words diversity of a wide range and richness. So on one side we are having the wisdom of the individual, even if it doesn’t fit the academic benchmarking for wisdom, but there is still some wisdom in there, and we have a network of people between each exists different grades of relationship (blood relation, friends, co-workers, neighbors, readers of the same material, etc.) with about 6 or less degrees of connectivity. 

An old English proverb says that "two’s a company, three’s a crowd", and above its relevant meaning, it’s actually more important its value as output of masses’ wisdom. Sayings, stories, verses, songs and other type of cultural manifestation of the crowds, are examples of wisdom, condensed wisdom I might say. Somebody was saying that all the great ideas of mankind were thought with many ages before, nothing more truly, and we are just rediscovering them now through the advances of modern techniques and thought.

People might be illiterates but could be masters in manual work or in any field that doesn’t involve writing, people might be shy but find incredible creative force when they are talking about or expressing their passions, they could come with unexpected solutions to complex problems when the problems are broken down to their language. Sometimes only by having a real partner of discussion or having somebody to address to, a person arrives to discover new perspectives in the process of externalizing knowledge, come with a new idea or find the solution to a problem. As Mark Zuckerberg remarks, "people have really gotten comfortable not only sharing more information and different kinds, but more openly and with more people - and that social norm is just something that has evolved over time". And very important, people are willing to give their knowledge free if the right context is met, but how do we achieve that?

Coming back to the before mentioned proverb, it gives a minimal definition for what it means a company, with direct and figurative meaning, an association of two people, respectively a crowd, as an association of at least three people. Witty definition in common sense language, much less than the definitions given by the academic literature, isn’t it? It is necessary to say that here the meaning of association is quite rich, implying any type of association made between people who come in contact in a form or another – organizations, ways of transportation, in queue lines, in chat rooms, forums or within the boundaries of a social network, in fact any place in which some type of communication occurs.

Communication is the backbone on which our society is based, and there are so many aspects, but what is important to retain, is the sharing of ideas which occurs between two or more people, the mode in which the communicated data, information or knowledge shape us. There is a micro scale, in which the communication happens between any two people of a group, and a macro scale, in which the communication is regarded as a whole, though the interactions between all the members of a group. In both cases is important how the input is transformed, loosing or gaining content, what each person retains or contributes.  

Researching the exchange of information occurred at multiple levels in our society is almost impossible, we only observe its effects, how markets change, how fast we receive important or irrelevant information, how meaning is changed voluntarily or involuntarily, altruistically or looking for profit. I’m mentioning this, because without understanding the whole process of communication and all its aspects we can’t use adequately the communication channels and harness the skills of people.

We could say that we are having the potentiality of crowds’ wisdom, but it depends how we harness it. Harvesting doesn’t resume in the ultimate action of taking the results of nature’s work, you have to invest some time in cultivating the seeds, take care of the plants, providing water and the needed care, the right temperature and fertilizer, consider the appropriate time for performing each action in the process. In addition you have to come also with some additional knowledge about the plants themselves, but also about the context, which is the best soil, what it takes to be in agriculture, to build an infrastructure for optimal work, etc. Who says that the same doesn’t apply to individuals and groups too?!

Individuals and groups need to be brought to the required level of education and knowledge in order to rise to the level of the demands. Wisdom involves some degree of knowledge and implicitly of information, the volume depending on the nature of the task at hand. Same you educate a kid upbringing him to a certain level of autonomy by repetitive task increasing in difficulty, upon its degree of understanding and pace, the same should apply to a group too, based on its intrinsic qualities and requirements. In the past years have been attempted to use the masses in order to solve several types of tasks, some with positive, but also many with negative results. 

If the masses can’t solve a certain type or types of problems, this doesn’t mean that they are dumb and posses no wisdom. An example of such a “failure” is the attempt to predict the trends of the various types of markets by using the masses, though it’s hard to think that such experiments could come with positive results as long there are too many interests and people who want to make profit by influencing the masses. This aspect stresses especially the need for independence, which adds to autonomy and diversity, other two characteristics that needs to be met by the crowds.

It’s also important to address a problem to the right community. I doubt, for example, that a complex problem of physics could be solved by addressing it to a group of sportives, excepting the cases when you talk about sportive physicists. Mentioning people who have knowledge coming from two or more domains, they are quite important, but not necessarily the most important. Depending on the problem at hand, the group should have a set of given properties that would allow it to approach and solve a problem.

There are many more aspects that need to be considered in relation to the crowds, hopefully I will manage to develop the ideas in a series of other posts.

13 November 2010

Cognitive Science: On Crowds (Quotes)

"We are more wicked together than separately. If you are forced to be in a crowd, then most of you should withdraw into your self." (Seneca , cca. 65 AD) 

"The vulgar crowd always is taken by appearances, and the world consists chiefly of the vulgar." (Niccolò Machiavelli, "The Prince", 1513)

"The crowd plays the tyrant, when it is not in fear." (Baruch Spinoza , 1677)

"Public is a ferocious beast: one must chain it up or flee from it." (Voltaire , 1748)

"Every numerous assembly is mob, let the individuals who compose it be what they will." (Lord Chesterfield , 1751) 

"The pretence of collective wisdom is the most palatable of all impostures." (William Godwin, 1793)

"It is easy in the world to live after the world’s opinion; it is easy in solitude to live after our own; but the great man is he who in the midst of the crowd keeps with perfect sweetness the independence of solitude." (Ralph  Emerson, 1840)

"Men, it has been well said, think in herds. It will be seen that they go mad in herds, while they only recover their senses slowly, and one by one." (Charles Mackay, "Extraordinary Popular Delusions and the Madness of Crowds", 1841)

"A mob is a society of bodies voluntarily bereaving themselves of reason." (Ralph W Emerson , 1841) and 

"The nose of a mob is its imagination. By this, at any time, it can be quietly led." (Edgar A Poe, "The Works of Edgar Allan Poe", 1849)

"Those who know that they are profound strive for clarity. Those who would like to seem profound to the crowd strive for obscurity. For the crowd believes that if it cannot see to the bottom of something it must be profound. It is so timid and dislikes going into the water."(Friedrich Nietzsche, "The Gay Science: With a Prelude in Rhymes and an Appendix of Songs", 1882)

"The larger the mob, the greater the apparent anarchy, the more perfect is its sway. It is the supreme law of unreason." (Sir Francis Galton, 1889)

"Good sense travels on the well-worn paths; genius, never. And that is why the crowd, not altogether without reason, is so ready to treat great men as lunatics." (Cesare Lombroso, "The Man of Genius", 1891) 

"If there is a look of human eyes that tells of perpetual loneliness, so there is also the familiar look that is the sign of perpetual crowds." (Alice Meynell, "The Spirit of Place, and Other Essays", 1899)

"Where there had been only jeers or taunts at first, crowds come to listen with serious and sympathetic men." (Edward Carpenter, "My days and dreams: being autobiographical notes", 1916)

"The masses […] neither should nor can direct their personal existence, and still less to rule society in general." (José Ortega y Gasset , 1930) 

"When everything is connected to everything in a distributed network, everything happens at once. When everything happens at once, wide and fast moving problems simply route around any central authority. Therefore overall governance must arise from the most humble interdependent acts done locally in parallel, and not from a central command.A mob can steer itself, and in the territory of rapid, massive, and heterogeneous change, only a mob can steer. To get something from nothing, control must rest at the bottom within simplicity. " (Kevin Kelly, "Out of Control: The New Biology of Machines, Social Systems and the Economic World", 1995)

"Crowds can push the merely good to unearned fame, but they’ll rarely get wholeheartedly behind the terrible." (Albert-László Barabási, "The Formula: The Universal Laws of Success", 2018)

"Beauty is not defined by the masses but by the opinion of the individual." (Rune Leknes)

"Business today consists in persuading crowds." (T.S. Eliot)  

"Crowds are somewhat like the sphinx of ancient fable: It is necessary to arrive at a solution of the problems offered by their psychology or to resign ourselves to being devoured by them." (Gustave Le Bon)

"Educate and inform the whole mass of the people [...] they are the only sure reliance for the preservation of our liberty." (Thomas Jefferson)

"I much prefer the sharpest criticism of a single intelligent man to the thoughtless approval of the masses." (Johann Kepler) 

"In solitude the lonely man is eaten up by himself, among crowds by the many." (Friedrich Nietzsche)

 "It is proof of a base and low mind for one to wish to think with the masses or majority, merely because the majority is the majority. Truth does not change because it is, or is not, believed by a majority of the people." (Giordano Bruno) 

 "If it has to choose who is to be crucified, the crowd will always save Barabbas." (Jean Cocteau)

"In almost every act of our lives whether in the sphere of politics or business in our social conduct or our ethical thinking, we are dominated by the relatively small number of persons who understand the mental processes and social patterns of the masses. It is they who pull the wires that control the public mind." (Edward L. Bernays)

"[It] is impossible for us to establish a living vital connection with the masses unless we will work for them, through them and in their midst, not as their patrons but as their servants." (Gandhi)

 "Men whose counsels you would not take as individuals lead you with ease in a crowd." (Cato)

 "Non-cooperation is an attempt to awaken the masses, to a sense of their dignity and power. This can only be done by enabling them to realize that they need not fear brute force, if they would but know the soul within." (Gandhi)

 "Observe the masses and do the opposite." (James Caan)

"Only those who leisurely approach that which the masses are busy about can be busy about that which the masses take leisurely." (Lao Tzu)

 "Opinions are formed in a process of open discussion and public debate, and where no opportunity for the forming of opinions exists, there may be moods, moods of the masses and moods of individuals, the latter no less fickle and unreliable than the former, but no opinion." (Hannah Arendt)

 "Quotes are empty and meaningless. It is how they are used that gives them purpose, how the person repeating those words gives them meaning. Good quotes do not offer the author immortality. Instead, they give the author limitless rebirths on the tongues of the masses." (Andy Clark) 

 ‎"Two’s a company, three’s a crowd" (saying)

 "The adjustment of reality to the masses and of the masses to reality is a process of unlimited scope, as much for thinking as for perception." (Walter Benjamin)

 "The average man's opinions are much less foolish than they would be if he thought for himself." (Bertrand Russell) 

‎ "The only certainty about following the crowd is that you will all get there together." (Mychal Wynn)

"The man who follows the crowd will usually get no further than the crowd. The man who walks alone is likely to find himself in places no one has ever been." (Alan Ashley-Pitt)

"The mob has many heads but no brains." (Thomas Fuller)

"The wisdom of the masses is not always [...] wise [...]" (Jon Stewart) 

"Truth happens to individuals, not to crowds." (Osho)

"We should not listen to those who like to affirm that the voice of the people is the voice of God, for the tumult of the masses is truly close to madness." (Alcuin, Letter to Charlemagne)

‎"What if the 'wisdom of crowds' turns out to be the ignorance of the masses? In fact, what if the Internet is a 'really bad thing' for the world and its population?" (Stephen Saunders)

 "When a hundred men stand together, each of them loses his mind and gets another one." (Friedrich Nietzsche)

"When distant and unfamiliar and complex things are communicated to great masses of people, the truth suffers a considerable and often a radical distortion. The complex is made over into the simple, the hypothetical into the dogmatic, and the relative into an absolute." (Walter Lippmann)

  

05 November 2010

Knowledge Representation: Knowledge Maps (Part VI: Patterns)

A pattern could be considered as a perceptual structure derived from observed similarities existing in the structures existing in a given layer. Following the DIKW pyramid, from data to information, knowledge and further to wisdom and beyond, could be observed various patterns that offer new insights at the respective levels, patterns that could categorize the findings in layers beyond the layers in which they are observed. We could discuss thus about data patterns referring to patterns existing in data, typically aggregated in form of information, information patterns referring to patterns existing in knowledge, typically aggregated in form of knowledge, knowledge patterns referring to patterns existing in knowledge, typically aggregated in form of wisdom and eventually wisdom patterns, referring to patterns existing in wisdom.

The K-map, as a graphical tool used to represent chunks of information/knowledge and the associations existing between them, is not only a container for patterns, but a pattern itself, and this because the various types of K-maps are attempting to address special patterns in knowledge and its representational layout: chained, clustered, hierarchical, radial or networked. Patterns could be observed in the smallest representational elements existing in K-maps, the way the chunks, called nodes, are associated together forming micro-patterns, and further aggregated in creating macro-patterns. Ignoring the content of each node, and the meaning of associations, but keeping for example the direction of the associations, could be observed several simple patterns:

 KM - Patterns 1

The above patterns are not necessarily representative, their scope being to provide an idea of what a pattern looks like: sequence (i), parallel sequences (ii), triangle (iii) & (iv), square (v), divergent (vi), convergent (vii) and any combination of them. For example the simplest pattern, the sequence, could be observed in all the other patterns excepting (xii) and (xiii) patterns, and it could include any numbers of nodes. Maybe more difficult to observe, the patterns (vi) and (vii) could be found in (viii) and (ix), in fact the number of emerging or emerging arrows from node could be greater than two. The number of such patterns could be in theory infinite, the nature offering a huge collection of such patterns, while many of the above patterns could be observed in K-maps too, the arrow playing the role of named or unnamed associations. Here are some variations of the above patterns based on concepts and the associations between them:

KM - Patterns 2

The concepts (“Concept i”, i=1, 2, 3, 4) from the above diagram stand as placeholders for any concepts that could fit in such patterns. For example “data”, “information”, “knowledge” and “wisdom” are forming a sequence based on same association which could be named “leads to”, “forms”, “aggregated in”, etc. Causality relations could be modeled with such sequences, for example “high data quality” leads to “accurate report”, which leads to “accurate analysis”, which leads to “better decisions”. However causality is more complex, witness being the various Causal Maps available on the Web, for example “theory”, “concept” and “grounding”, respectively “customer satisfaction”, “product quality”, “customer loyalty” and “brand strength” seems to “break” the sequence pattern. Please note that the associations don’t necessarily to be true, they could represent as well an opinion or be rooted in experiments that confirms them. The laws of causality, complexity and patterns are too complex to be debated in here, in fact each person accumulated in time knowledge that matches such patterns.
   KM - Patterns 3

In the above diagram, could be observed that the examples based on causality are situated at the top, respectively at the bottom of the diagram, in between different types of associations. Is it there any reasons for that? In the moment we asked ourselves such a question, we are already attempting to identify a spatial pattern referring to the positioning in a given area, in this case a diagram. Spatial patterns are at their turn quite complex patterns, we could see it in the world around us. Does the fact that the same distance exists between various points, that forms are contained one in the other or that the associations are dispersed radially from a common point tell us something? What do such patterns represent for us? 

Sometimes we have to make abstraction of the associations and content and see the macro-forms created by clusters of such patterns in order to discern the patterns. Does it seem too complicated? It isn’t at all. Just look at a poem formed of 4 strophes and a common rhyme. We are ignoring in fact what the words represent, the letters of a word, or the points that form a letter, we consider just the form of the strophes and the endings, that’s such a pattern. In nature there are so many such patterns, some even more simple than we might think of, and here are some examples:
 KM - Patterns 4
The world of patterns doesn’t stop here, we could associate patterns related to all our senses, resulting thus olfactory, tactile, auditory or kinesthetic patterns. It seems that such patterns are moving beyond our representational sphere, doesn’t it? Not at all, everything could be reduced to a concept and the associations between them, the difficulty residing in how to choose the “best” pattern that reveals the represented knowledge.

02 November 2010

Knowledge Representation: Knowledge Maps (Part V: Propositions)

   Unfortunately the richness of natural language goes above the capabilities of the current representational tools, for example the temporal, spatial, causal and conditional associations, or the associations between whole propositions are not so easy to represent in many of the K-maps available. Given the rules of syntax, in natural language a proposition is formed typically at minimum of a triple, while a typical proposition could be expressed as one or more such triples. On the other side, a chunk of meaning could be represented as one, two or more triples that span within one or more propositions, same as from a whole text only 2-3 triples could be relevant. As chunks could spread along several propositions, it is necessary to identify the meaningful triples and recombine them in more complex constructs, such a construct being the knowlet.

   Because has been discussed in several occasions about chunks of meaning, some examples are necessary in order to understand what is meant by this construct. The simplest chunk of meaning is the concept itself, for example “collective”, “intelligence”, “collective intelligence” and “harnessing collective intelligence” are such chunks. The next logical type of chunk of meaning is a simple triple formed actually from three concepts, for example “harnessing collective intelligence is a web 2.0 principle” is based on “harnessing collective intelligence”, “is a” and “web 2.0 principle”. A minimum of 4 concepts could result in two triples, for example “web as platform and harnessing collective intelligence are web 2.0 principles”, the two triples could be split in different propositions. By adding one more concept we arrive to three triples, and the logic could be followed, resulting several types of patterns.

     Is the latest example still a chunk of meaning? Yes, it is because they share together the same object within the same proposition, enclosed in a definition-like clause. Definitions are typically examples of such unitary chunks of meaning, for example let’s consider the definition of K-mapping given by Dr. Ann Hylton:

    "Knowledge Mapping is the process of surveying, assessing and linking the information, knowledge, competencies and proficiencies held by individuals and groups within an organization." [1]

     Proposition’s structure could be represented in a K-map resembling a Concept Map as follows:

 KM - example 5 - KM definition concept map Knowledge Mapping definition - Concept Map

     The representational language depends from person to person and from one KM to another, for example the same proposition could be rewritten as follows:

KM - example 5 - KM definition KMKnowledge Mapping definition - Knowledge Map

  Here’s another example following a similar structure, this time based on  D. Hyerle’s definition for K-mapping:

     Knowledge Mapping is “a rich synthesis of thinking processes, mental strategies, techniques and technologies, and knowledge that enables humans to investigate unknowns, show patterns of information, and then use the map to express, build, and assess new knowledge” [2].

KM - example 7 
   Which KM is better is a matter of personal taste, in theory the radial/hierarchical structures are easier to understand and navigate than the networked structures, though the later category of structures is closer to the structure of knowledge, the way concepts are structured. On the other side it could be problematic to represent the two definitions in the same K-map. Here’s an attempt based on propositions’ structure, respectively by restructuring concepts and associations:

KM - example 9 

KM - example 8

   Each of the two approaches comes with its advantages and disadvantages, the first K-map being closer to initial definitions’ formulation, highlighting the concepts found closer to the subject, but more difficult to represent, while the second, more condensed, closer to the representation of knowledge as triples, but keeping less from the initial structure. The maps are not necessarily representative, and neither too elaborate, they represent just the raw representation of two definitions. It would be useful to include multiple definitions in the same K-map, attempting to represent all the attributes of a concept and most representative associations. The downside of such K-maps is that they are more complex and all the consequences deriving from it.

References:
[1] M. Jafari, P. Akhavan, A. Bourouni, R. H. Amiri, (2009). A Framework For The Selection Of Knowledge Mapping Techniques. Journal of Knowledge Management Practice, Vol. 10, No. 1, [Online] Available from: http://www.tlainc.com/articl180.htm (Accessed:16 October 2010)
[2] Hyerle, D. (2008). Thinking Maps®: A Visual Language for Learning. In: Thinking Maps®: A Visual Language for Learning, ISBN: 978-1-84800-149-7. [Online] Available from: http://www.springerlink.com/content/x57121720731381j/ (Accessed: 23 June 2009)

01 November 2010

Knowledge Representation: Knowledge Maps (Part IV: Associations)

Associations, in several contexts called relations, are links between concepts, and even if they are labeled or not, explicit or implicit, they have assigned a meaning too. The split between concepts and labels introduces  two perspectives:
1. Knowledge broken down to concepts in which some of the concepts function as associations between other concepts.
2. Represented knowledge broken down as labels in which some of the labels function as associations between other labels.

A simple example of association is the one implied by the object agent verb (OAV) construct, also called the object subject verb (OSV), that stands not only at the base of linguistics topology but also at the base of RDF triples (in this context referred as subject-predicate-object, concept-connection-concept or ‘entity-event-entity’) rooted in the linguistics topology. Such constructs are the “is-a” and “has-a” constructs, often used in knowledge representation. For example “whale is a sea mammal” could be expressed as (“whale”, “is-a”, “sea mammal”) and “whale has a tail” as (“whale”, “has-a’, “tail”) in (subject, predicate, object) notation, however representing knowledge as such triples is not an easy task, but the visual representation of such triples with nodes and links reduces the complexity to some degree.

 KM - example 1

The domain knowledge could be relatively expressed as such isolated triples, but in knowledge representation, in order to reduce the complexity of visualization and navigation, it’s simpler to join such triples when they have common concepts. Thus the two triples could be represented as follows:

KM - example 2
 
The arrow shows in this case the agent, the first label in the sequence being the subject, while the label in between being the predicate. There are maps that don’t make use of arrows, in some cases the radial flow expressing the direction like in the case of Mind Maps, and maps in which there is no direction implied or a bidirectional row implies a bidirectional association, as in the case of synonymy.

The use of arrows and adequate labeling boxes facilitates KM’s understanding, in what concerns the role of labels in a triple, and navigation, in what concerns the flow/direction. As can be seen from the last diagram a subject could be involved in multiple associations, in the same way an object or predicate could be involved in multiple associations too. In the next KM could be observed for example how the same predicated is involved in multiple associations describing the anatomy of a whale.

 

KM - example 3 whale
Whale Knowledge Map (adapted after whale anatomy)


The original representation could function as a K-map as well, though images are more difficult to process than the maps built with adequate software, the later offering also the possibility of conversion to a portable format that could be further processed. In addition the spatial disposition of concepts could play a role as well, in this case being correlated with the disposal within whale’s anatomy. In more complex KMs the use of “background” images is not always easy to embed, in addition the multitude of connections increasing the overall complexity. The form of representation could depend on each person’s preferences, the association could be explicit as well as implicit, and typically only one of them is use. Here are the same “has-a” associations represented with the help of circle map (implicit associations) and bubble map (explicit associations).

KM - whale - bubble map KM - whale - circle map
Bubble map Circle Map

The “is-a” and “has-a” associations are used in combination with any other types of associations, of importance being especially the causality (A causes B), synonymy (A is synonym of B) or antonymy (A is antonym of B), precedence (A precedes B) or concomitance (A occurs at the same time as B), etc. In fact any verb, substantive or even prepositions could play in theory the role of an association. If the above examples fall in the “verb as association” category, the use of substantives as associations is maybe more difficult to intuit, so here is an example based on whale’s anatomy in which the “has-a” has been replaced with “anatomic part” association:

 KM - whale - substantive association
Between two concepts there could be in theory multiple associations, more than one explicit association, though few are such cases because typically is stressed only the most important/relevant association. In the below image, a part of a KM on “self-transcending knowledge”, could be seen how the “competitive advantage” is involved in two associations with the same concept.

KM - example 4Self-transcending knowledge KM part (KM based on [1] text)

The existence of multiple associations has several other implications in what concerns associations’ type. For example causality implies two inverse associations: “A causes B”, respectively “B caused by A”, in fact dealing with the same meaning associated in different directions by inversion of terms. Such constructs could be confusing, therefore a good practice is to adopt only one of the two associations; the simplest approach is to simply use “A causes B”. A similar type of association is the transposed association, in which from “A imply B” is inferred that “Not-B imply Not-A”. With this we entered in the territory of deductive reasoning, entailment and of rules of inference

Deductive reasoning could prove to be quite complex and of great use, especially when is intended to infer new associations (inferred associations) based on an existing set of associations. For example if in a KM we have that “A implies B” and “B implies A”, then we could deal with the equivalent association “A equivalent to B”, in mathematical terms expressed as “A=B”. Another simple logical inference is based on the simple rule of inference: if “A imply B” and “B imply C”, then “B imply C”. Implication could be applied also to causality, synonymy and several other types of associations.

The fact is that many of the rules of inference that apply is deductive reason could be used to KMs too, special inference engines could be used for this purpose. Associations between two or more concepts don’t have to be of the same type in order to prove to be useful, or in some cases even if the association seems to be of different types, the meaning they carry could be sufficient to allow an association to participate in inferences, this being valid especially for the associations belonging to the same class of meaning. In addition, associations of the same type and the concepts involved could reveal interesting properties that could be analyzed from the perspective of (superior) algebra or network theory.

Cardinality of Associations

The above representations have one important issue - they don’t reflect the cardinality of concepts, how many elements of the same concept participate in the associations. For example the whale has two blowholes and two pectorial fins, while a table has for legs, etc.  In database modeling the associations, actually called relations, include the cardinality (e.g. 1-to-1, 1-to-n, n-to-n) though it just highlights that there is one or multiple records/entities associated in relations. In our case is typically required to specify the actual cardinality. As database model could be regarded as KM too, it’s thus necessary to address both types of cardinality, when they apply.

References:
[1] A. Kaiser, B. Fordinal. (2010). Creating a ba for generating self-transcending knowledge. Journal of Knowledge Management.Vol.14, no. 6 [Online] 10.1108/13673271011084943

Knowledge Representation: Knowledge Maps (Part III: Concepts and Labels)

Knowledge could be broken down to concepts and the associations between them, words functioning as links between concepts. A concept could be seen as a unit or chunk of meaning, for example “mother”, “father”, “child”, “home” are a few of the concepts we incorporate in our conceptual vocabulary, the collection of concepts we hold in our mental world. The previous four mentioned examples are just words, though words are just labels, transporters of meaning, and they don’t equate to concepts. A word (written or spoken) same as an image, a symbol or sound are just a representation/externalization of a concept outside of the mental world, we could regarded them simple as labels. Sure, they are strong correlated, and concepts could exist without labels, same as labels could exist without the articulation of a concept in the mental world. In a simpler formulation we could say that:

Label + Meaning = Concept

Meaning and labels are concepts too, fact that makes the definition kind of redundant, but that’s less important as long the overall meaning is understood. In addition the concept of meaning is quite complex, meaning being considered as existing within a given context, a context that carries its own meaning and it’s a concept in itself. More redundancy, isn’t it?

We could in theory put on a paper all the concepts we know, to be more focused, all the concepts we know related to other concept functioning as topic. Such constructs are similar to the ones of tag clouds, user-generated tags used to describe the content of a web page. Another type of such collection of concepts is the shopping list or any other types of lists.

 

must_buy_twitter_shopping_list[1] Shopping list
Example of tag cloud Example of shopping list

                               

Each of the words from the above tag cloud, respectively shopping list, are labels of the concepts they represent. In contrast to the shopping list, the size of the labels used in the tag cloud is proportional with their occurrence, but that’s less important for now. The fact is that both are representing a collection of concepts. More complex collections could be based on concepts derived from scientific works, book indexes are another such of example.

In the above shop list, “movie tickets” is a multipart label for a “single” concept, though it’s composed of the labels of two different concepts – “movie” and “ticket”. In this way concepts/labels could be formed by the aggregation of meaning for concepts, respectively concatenation of labels for labels. In theory we could put together as many of concepts or labels as we wish, though there are some limits imposed by linguistics. In daily life aggregations/concatenations of 2-3 concepts/labels are pretty usual: “knowledge mapping” (= “knowledge” + “mapping”), “knowledge management”, “business intelligence”, “collective intelligence”, “harnessing collective intelligence”, etc. There are also examples of labels encompassing already a concatenation of other labels, words formed with prefixes (e.g.: “un” + ”believable” = ”unbelievable”), affixes (“engineer” + ”ing” = ”engineering”) or hybrid/compound words (e.g. “auto” + ”mobile” = “automobile”)  are the simplest examples we used on a daily basis, some of the languages being more abundant than the others in such compounds (e.g. German language is quite rich in such hybrid words). 

The linguistics and semantic meaning of words offer us a deeper overview on the formation of words and meaning, though we don’t have to go that far. I will just limit myself to mention that a morpheme is the smallest compound of a word, composed at its turn of multiple phonemes, the smallest linguistically distinctive units of sound, and graphemes, the smallest units of written language. In addition words or labels does not necessarily have to respect the rules of language morphology as a whole, one of such compounds that entered in my vocabulary many years ago, comes from the Disney’s musical film Mary Poppins, and those who the movie, probably already intuit what I’m talking about: Supercalifragilisticexpialidocious is formed, according to Wikipedia, from the following morphemes: super- "above", cali- "beauty", fragilistic- "delicate", expiali- "to atone", and docious- "educable", and the sum of these parts signifying roughly "atoning for educability through delicate beauty".

Given the richness of languages in what concerns the morphology, syntax and declension, how do we choose the labels? Also this is a complex topic and my knowledge stops somewhere. I prefer to use the infinitive form for verbs, nominative and singular form for substantives, sometimes called the dictionary forms, and include the prepositions when they change the meaning (English language is full of such constructs).  It’s not always so easy to do that, but I try to stick to it whenever is possible. In what concerns the labels formed of multiple other labels I prefer to choose the smallest unit of meaning that defines a concept “uniquely”.

Classes of Meaning

 A class of meaning equivalence, shortly class of meaning, comprises all the labels that share the same meaning [1]. Such a class comprises all the synonyms, acronyms and forms of construction of natural language used to label a concept. For example, depending on context, any of the following labels could be considered as belonging to the same class of meaning: abode, apartment, flat, home, mansion or residence. Many of us use acronyms in daily life, with formal or informal character: EOD (End of Day), ASAP (As Soon As Possible), US (United States, Uncle Sam, Upstream, Ultrasound), KM (Knowledge Map, Knowledge Management, Knowledge Mapping, kilometre), etc. 

The syntagm “forms of construction of natural language” refers primarily to the various elements of orthography  hyphenation, capitalization, word breaks, emphasis and punctuation, which introduce some variance in the labelling of concepts. On whether we write “knowledge based” or “knowledge-based”, “center” or “centre”, “Knowledge Management” or “knowledge management”, “class of meaning” or “meaning class”, the various labels refer to the same concept. Normally in a Map would be enough to include only one member of a class of meaning, unless is intended to highlight the synonymy or any other similar association type.

Knowledge Representation: Knowledge Maps (Part II - Knowledge Mapping)

It’s natural to talk about K-maps within Knowledge Representation, and extensively within Knowledge Management, domains in which the process of creating a K-map is known as Knowledge Mapping, shortly K-mapping. In essence that’s what K-mapping is about, creating a K-map, however in literature could be found more elaborated definitions. According to D. Hyerle, K-mapping is “a rich synthesis of thinking processes, mental strategies, techniques and technologies, and knowledge that enables humans to investigate unknowns, show patterns of information, and then use the map to express, build, and assess new knowledge” [1]. 

Within the same context but from a slightly different perspective, [3] regards it as a “consciously designed communication medium using graphical presentation of text, stories, models, numbers or abstract symbols between map makers and map users”. In the context of K-mapping in organizations, B. Bergeron defines it as the “process of identifying who knows what, how the information is stored in the organization, where it’s stored, and how the stores of information are interrelated” [2]. All the above definitions focus on mapping as a process, knowledge as the object of the mapping process and the context in which it occurs.

The use of various types of K-maps introduces similar concepts, K-mapping being referred as concept mapping when talking about concept maps or when the granularity of a map is at concept level, mind mapping when the focus is Mind Maps or externalization of mental maps, semantic mapping when discussing about semantic maps, process mapping in the case of process maps, etc. Related concepts stress other aspects of K-mapping referring to different levels of abstraction, for example ontology creation or ontology engineering, in this context ontology mapping referring to the mapping between different ontologies. Same happens in the world of the databases in which data modeling or semantic modeling refers at the creation of a data model, while data mapping refers at the mapping between two structures.

As stressed before, the various types of K-maps in use introduce their own creational philosophy, which with a little effort could be raised at the state of methodology. K-mapping as a process could be reduced to input, output and what happens in between. As input for a K-map could be used the various types of media content, mental models, knowledge of experts, discussions outcomes or any other sources of information. As knowledge is not always available at our disposal, searching for knowledge, identifying knowledge is quite a time consuming task, especially when knowledge is not indexed, easily accessible or we don’t exactly know what we are searching for. In general we talk about knowledge acquisition, which refers to the process of extracting knowledge, structuring and organization of knowledge

When creating a K-map we are doing extensively knowledge acquisition, essential in the process of learning. In exchange, when we create K-maps on the mental models, we are externalizing our knowledge, transforming the tacit in explicit knowledge, figuring out or better said evaluating what we stored in our brain, grounding of knowledge by finding meanings, formalizing concepts, finding the best formulation, finding new associations, building on previous knowledge, examine beliefs, integrating, mixing and recombining knowledge, identify patterns in knowledge, patterns of thinking, becoming creative, etc. Also these aspects are part of K-mapping, even if they are not so visible in the process, however they are stressed especially during K-mapping. 

The structuring and organization of knowledge in K- mapping is done in representational form (visualization), translated into spatial organization or simple aggregation of information, in patterns or models of expressions, and here the various types of K-maps are used as a form of expression. Mapping techniques need to be flexible in order to reflect the representational richness of knowledge, they evolve with experience, “the one who maps” learning with time to take advantage of the appropriate type of K-map or pattern. K-mapping is thus an iterative process, a K-map being evolved during several stages, the final outcome being unexpectedly different than the inputs or expected outcomes.

K-mapping applies to individuals as well as to groups, collaborative or coordinative K-maps involving more complex forms of acquisition, process or visualization, often being involved some forms of negotiation and knowledge sharing from which the output emerges. Collaborative K-mapping seems to be preponderant to the contexts in which the force of the group emerges, mainly economical and scholar organizations, and recently social networks.

References:
[1] M. Jafari, P. Akhavan, A. Bourouni, R. H. Amiri, (2009). A Framework For The Selection Of Knowledge Mapping Techniques. Journal of Knowledge Management Practice, Vol. 10, No. 1, [Online] Available from: http://www.tlainc.com/articl180.htm (Accessed:16 October 2010)
[2] B. Bergeron. (2003). Essentials of Knowledge Management. John Wiley & Sons, Inc. ISBN: 0-471-28113-1.
[3] H. P. Tseng, Y-C. Lin (2008) A Knowledge Management Portal System for Construction Projects Using Knowledge Map. Knowledge Management:
Concepts, Methodologies, Tools and Applications, M.E. Jennex (Ed.). ISBN-13: 978-1-59904-934-2.

31 October 2010

Knowledge Representation: Knowledge Maps (Part I - An Introduction)

Most of us are familiar with the geographic Maps, during school hours or outdoor trips we had at least once the possibility of guiding ourselves using a Map. Paraphrasing Alfred Korzybski, “the map is not the territory”, though a Map offers a bird’s eye view of the territory, it might be not perfect, nor so detailed as we would like it to be, though it allows people identifying their position, their destination, their route left behind and the one ahead, the obstacles, the boundaries, the known and unknown zones. Our marvelous memory allows us storing details of such Maps, more or less perfect copies of the Maps, voluntarily or involuntarily memorized. 

Even more, we are creating in our brain an adaptable dynamic Mental Map of the world we live in, reflecting the changes occurred in it the way we perceive them. It is what Robinson, quoted by [1] calls it “reduction of reality” and “construction of an analogical space”, the complex structure of reality being reduced to an easy to memorize Map attempting to be a reflection of reality. A geographic Map uses Names, color, spatial organization, and a small set of symbols in order to represent a projection of the geographical world we live in. In a similar manner we could map also the various types of knowledge using a similar set of tools known as Knowledge Maps or simply K-maps.

Especially between students, could be met the practice of underlining or marking a chunk of text with special marker(s), highlighting the respective text as important, at least for a second review. The chunk of text could be a concept, a definition or a whole paragraph, and that’s actually the input for a K-map. In theory you could put the whole chunks of texts together on post-it or electronic documents, group them together in some way, and there you have a rudimentary K-map. Thus could be intuited that a K-map is a graphic organizer of chunks of texts identified as information or knowledge. Putting together row text allows structuring the content based on identified associations, it could be sequential structure, logical implication, importance, topic, etc. 

Thus are created implied or explicit association between the various chunks of text. Further value could be added by breaking the text in smaller chunks, summarize a chunk in fewer words, replace words with more meaningful words, add numbering, symbols, other types of markings (e.g. NB = “nota bene”, QED = quod erat demonstrandum), references, questions, etc. Of course, the same could be done in the book itself though ignoring the fact that book’s owner or further readers could argue such methods, the value comes from having the chunks of text coming from different books in one place or, if you want, in fewer text containers, and the electronic documents make this approach such an easy task.

From a visual perspective, processing a whole chunk of text could be time consuming, especially when we look for specific information, typically key words, primary concepts, definitions, etc. Marking such text in special ways brings some additional value, though the linear character of text makes it still difficult to process. What if we break the text at conceptual level? Wouldn’t such output be easier to process? Now it depends also on each person’s capabilities, though working with concepts seems closer to the mental structure of our mind, in the way meaning is represented and created. 

What if we further represent the associations between concepts explicitly, giving them names, and thus associating other concepts with them? Wouldn’t be such structures easier to process and understand? Such structures would be also K-maps, though their content is more refined. Actually the concept-based and whole propositions could be mixed together in K-maps, the degree of refinement of such concepts being more a figure of taste or, as will be further seen, of philosophy.

Until now we considered a K-map as being an aggregation of chunks of text of various granularities, implied or explicit associations, and the later could be labeled using other more or less standardized concepts. We talked also about formatting, meaningful display, resources, symbols and other types of markings. These are in fact the content elements of a K-map, but in definitive what is a K-map?!

Extrapolating the above considerations, a Knowledge Map or K-map could be considered as a visual graphical tool used to aggregate and represent information or knowledge. The definition seems to need further refinement because the graphical character implies a visual component, representation could involve aggregation and thus the later term could be abandoned, while following the DIKW pyramid, knowledge involve information. Graphical is the form of representation, while the role of visual is to represent explicitly the channel of communication, in fact stressing its visual, respectively graphical character, a K-map could be considered as synonym to visual aid or graphical organizer, terms more frequent used, especially in teaching. No matter of the degree of knowledge encompassed, a representation of the knowledge is not the knowledge itself, it resumes thus to information that triggers knowledge and the associations existing between information. Thus, a K-map could be defined as a visual graphical tool used to represent information and the associations existing between them, either implicit or explicit. The term information encompasses here any type of symbols or chunk of texts. When information is present in its most granular form, at concept level, the K-map is a visual graphical tool used to represent concepts and the associations existing between them.

The definition of a K-map represent the “what” from the W5H1 syntagm, how about the why, who, when, how, by whom and by what means? Why a K-map, isn’t the text or what we know enough? Do we really have to break the knowledge into such maps? Maybe we don’t, it depends on each persons capacities, some of us have a really good memory, retain everything they read and recalled it any time. For others, such capabilities come with some effort, spending some time in memorizing the information we consider as useful for the future, and also this step depends on each person’s capabilities and skills. As mentioned in introduction, the read material could be “formatted”, broken into pieces, annotated, summarized, restructured in order to increase the efficiency of memorization and recall. 

According to researchers, in brain itself takes place some unconscious restructuring of information, associations are created, strengthened and removed, the later activity resulting in forgetting the information once stored, the recovery of such information necessitating a review of the source or sources used in the first place to acquire the respective information. Considering the huge amount of information our brain deals with, it’s almost impossible to identify during a simple read, all the connections existing between the various concepts assimilated, especially when they aren’t so evident. This perspective of what’s happening in our brain is quite simplistic, though can be discovered already some gaps in the learning process, gaps which in theory could be addressed with the help of K-maps. As its name and definition denote, a K-map has the function of a map, used to represent knowledge. 

Once such a map created, it would be easier for us to access it, and thus to refresh our information, eventually use it as a reference to the actual text. In addition, when evaluating the associations of such a map, existing or inexistent, we could identify new associations, conditions under which they hold (e.g. range of applicability, exceptions), new concepts, new contexts, etc. Let’s not forget that the human is a social being, the meaning of the concepts we deal with relying also their meaning at macro level – organizations, communities of practice, friends or any other types of groups. The individual maps could be used in order to compare and evaluate knowledge, collective collaborative and coordinative creation of K-maps coming with their benefits too. They could be used as a baseline for learning, negotiation, documentation or (self-) evaluation. 

The creation of a K-map requires additional time, time we don’t always have. Does it really make sense to create such a map all the times? It’s probably recommended to create it when we acquire new knowledge, especially when we want to identify the concepts on which the respective chunk of knowledge is built upon. Once the backbone concepts mastered, the necessity of a map decreases to some degree, in the end its necessity depending on individual needs. A K-map could be useful also when externalizing the knowledge, especially the tacit knowledge, in organizations being quite a valuable tool in documenting the various types of information organization work with, process maps, flow maps, value stream maps, being several examples of such K-maps.

How to create a K-map? In definitive maybe we create such maps without knowing it, it’s built in our “ADN” as we often arrive to express complex thoughts by externalize them in diagrammatic form. There are more than 50 types of K-maps available in the literature: Concept Maps, Semantic Nets, Conceptual Graphs, Mind Maps, and so on. They have many similarities, often the similarities residing in the philosophies used to create them. Adhering to one or more of such maps is a question of need, preferences, habitude and requirement. Sometimes also deviations from the philosophy behind a map could prove to be useful as long satisfies a purpose, same as a map arrives to be misused, for example by placing too much content, be it irrelevant or relevant, or of using too much formatting, not respecting guidelines, etc. There are several requirements a K-map should satisfy – it should be simple to use and navigate, with an approachable level of complexity and thus understandability, adaptive and dynamic.

 “By what means” could refer here to the tools used to create K-maps and the channels used to distribute them. Again it’s a question of need, preferences, habitude and requirements. In the past years appear many tools used for the creation of K-maps, having multiple features, but still lacking in representational content the human mind is used to. The paper and a crayon could prove efficient as well, while those with an exceptional memory could create such maps directly in the inner mental world. Everything is possible, everything it’s a question of practice and self-improvement of techniques.

References:
[1] Hyerle, D. 2008. Thinking Maps®: A Visual Language for Learning. In: Thinking Maps®: A Visual Language for Learning, ISBN: 978-1-84800-149-7. [Online] Available from: http://www.springerlink.com/content/x57121720731381j/ (Accessed: 23 June 2009)

12 October 2010

Meta-Blogging: Is Blogging Stagnating?

Introduction

When I started this blog, it wasn’t in my intent to do meta-blogging (blogging about blogging), though a few days ago, while browsing through Linkedin posts, Nic Oliver’s question “Where have all the bloggers and commenters gone?”  draw my attention. The question is rooted in his observation that a few social sites, he was member of, are registering an apparent decrease in the number of blogs and comments. Is it really this happening? The question preoccupies me not only as blogger and owner of a blog on web-related theme, but also as I’m interesting in the evolution of web and its trends. 

Until now I had no reasons to pose such a question, I mean even if the current blog had few visitors in the past month, this was also a consequence of the fact that lately I haven’t managed to post something new, however my sql-troubles blog acknowledges a considerable increase in the number of visitors, from about 50 users per week at the beginning of this year to about 250 users currently. I know that’s not a big number when compared with other professional blogs, though for beginning that’s even a little more than I expected. I could corroborate the increase in the number of visitors with the increase in the number of posts and the fact that I tried to post each week something.

A Look at Personal Navigation History

Looking back at my navigation history of the past months I have to recognize that I focused more on professional blogs, mainly on the MSDN blogs which are going through a considerable boom, probably a result of a change in strategy coming from Microsoft. Spending more time on content creation and reading of a several profession-related books, the time spent on reading others’ blogs decreased considerably. I even kind of neglected Linkedin in the detriment of Facebook, though the time spent on Facebook decreased considerably lately because of the lack of time corroborated with saturation in what concerns the wanted and not wanted content, from the later category I remark the Farm Ville and Mafia games content. I could add also the relatively small number of new features added to Facebook, feeling that something more could be done in this direction, especially in what concerns content filtering, categorizing and aggregation. I am remarking these facts also because the respective problems could apply to other social networks or blogging too, and from this point of view I have several person observations.

Personal Blogging Concerns

I’m using Blogspot since almost 5 years now, it’s a nice blogging platform, though with a few exceptions the number of important new features since then is quite small, lacking several important features. The best example is the editor which provides few built-in html functionality when compared with the HTML tags available in HTML4 or newly HTML5. Sure, the HTML editor supports in theory all HTML tags though they need to be entered manually, and this equates with considerable effort from my part in some cases, especially when I consider the programming language code that needs special formatting in order to be easily readable. I found myself in the position to appeal from necessity to an editor like Windows Live Writer, though it has its issues too. To content formatting adds content presentation, in this category falling blog’s layout, quite inflexible from some points of view, and content categorization. Labeling and clouds are great in order to highlight important keywords, though I feel something more could be done in this direction, for example aggregating labels in categories or in Knowledge Maps.

Another important problem for myself is commenting, and here are several aspects. First, and maybe the most important aspect related to users authentication for commentaries, some of the blogs request a user to be logged in in order to comment, sure some of the websites are integrated with Facebook, Twitter or myOpenID credentials, though not all the users have and want to create a new account for this purpose (SideWiki it’s out of discussion here as it’s not integrated directly in the blogs). Secondly, the comments have poor or inexistent rich formatting, often resuming to text messages. Third aspect: it would be useful to have more flexibility in what concerns the notification when a new comment is posted.  Fourth aspect: also comments require sometimes some categorization, especially in what concerns in filtering out adulatory or irrelevant content. Fifth aspect: annotation, one of the important features of the Read-Write web is almost inexistent.

Saturation Point

All the above aspects could in theory make users a little unsatisfied with the blogging experience and reflect thus in a possible decrease in the number of blogs, posts or comments. In order to understand what’s happening we have to go deeper and understand the value of blogs for both, bloggers and readers, the important link between the two being the content. I was thinking that maybe we reached a content saturation point in which bloggers have less to say, the important subjects being exhausted. Maybe we reached also a break-even point between request and demand in what concerns the content reached an equilibrium in some domains, the variety and coverage of content facilitating this. Maybe the readers lost their interest, in definitive they want to be entertained, otherwise they’ll find another entertainer. Now not sure how many bloggers want to be in the position of an entertainer…

Time and Satisfaction as Drivers

As I was highlighting above, also the available time for blogging is a problem as good content and comments requires time, often some research in addition to the personal experience, from the later perspective the subjects could drain, bloggers having nothing more important to say (I actually have seen a few blogs closed because of that). The inverse ratio between time spent on one side and financial or personal satisfaction on the other side is possible to have depleted over time. For sure many people are blogging because they have something important to tell the world on professional and non-professional themes. It’s not only the interest but also some satisfaction involved, either financial or appreciative. 

The financial outcomes are quite small, resulting from ads and number of clicks gathered, the relevance of ads’ content being quite an important factor, and here I’m having some personal complaints too. The appreciative satisfaction is somewhat reflected in the number of visitors, the comments they post and the value they have for the blogger, and I would say that’s quite an important factor. I have also to remark the destructive/pejorative intent of some of the comments, many readers lacking in some basic blogging and social web ethics, being inclined to denigrate rather than criticize constructively. To this adds the volume of spam, the use of captchas, excepting their role of reducing the quota of spam, have the side effect of annoying the commenter, in some situation the use of captchas being totally badly-designed.

Content Absorption

A considerable number of blogs were just reflecting personal non-technical events from bloggers’ life, social networks like Facebook absorbing increasingly such content, and from this perspective I have to recognize that they are more appropriate for this purpose. Probably many commenters moved to the (social) professional networks, having more freedom in posting the questions, and potentially more experts, and thus a higher number and diversity of opinions, plus the feedback seems to function better. In addition, the professional nature of such networks could bring in theory more value than the blogs, the marriage between blogs and professional networks being the logical and maybe necessary move, though this requires a richer integration between the two platforms.

Behavioral Change

Maybe readers have started to do some research by themselves or learned to use online encyclopedias like Wikipedia that offer a good inverse ratio between content on one side and complexity, variety, spread, navigation on the other side. Maybe the users moved to the video content, richer in visual and auditive experience, many universities, companies, professionals and non-professional posting their webcasts or radiocasts online, collections like YouTube/Edu being a good example. Or maybe the users are too demoralized because of the crisis, sure that’s a forced possible cause, though in the end also the socio-economical factors should be considered.

Some Statistics

I was wondering how many bloggers moved their blogs between the various platforms or they totally abandoned their blogs or how many readers comment actually what they read. Even if I’m a little reticent to the way some statistics on the web reflect the reality as long I don’t know the background and the way they were collected, they could be used at least as approximation/trending. Technorati through its State of Blogosphere annual report seems the most quoted source for such statistics, though the report for 2010 it’s not already available, while the statistics for the previous years seems to be dispersed across several posts. Here are some important facts related indirectly to the current topic quoted by SEJ from Technorati:

- 77% of Internet users read blogs
- 70% of all respondents say that personal satisfaction is a way they measure the success of their blog
- the most common rate of updating is 2-3 times per week

Unfortunately no number in what concerns my three above concerns. Anyway, several blogs, for example Caslon Analytics blogging and PCMag.com, are quoting an old report coming from Perseus, in which is estimated that about 66% of the blogs are temporarily or permanently abandoned after two months. I wanted to dig more into the topic but the time and the ocean of information, in which is still difficult to search for relevant information, made me stop here…

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