04 January 2017

Models – In Search of a Definition


    Imagine you are talking with another person, you ramble about models here and there, and suddenly in the middle of the conversation a question falls like thunder, freezing the discussion for a few seconds: “you are talking about models, what is a model?”. The word become so common nowadays that such a question might seem a menace for the conversation. You might remember then some of the dictionary definitions you heard so often, though they pull with them other terms that need further clarification. Some well-known approximate quotations on models might spring into your thinking process, though they don’t seem of any help now. The seconds pass and the time of silence looks like an eternity, while your interlocutor stares at you waiting for an answer. Unless you are prepared to give a definition on interlocutor’s understanding, you’ll more likely be in the chase of a such definition. Words and ideas succeed fast, the silence grows deeper, your interlocutor becomes more anxious, and is waiting for an answer.

What is a Model?

    The easiest way to tackle such concepts is to start with a common representative example that can be used as scaffolding for a definition. If few people heard of “role models”, more likely almost all people having a TV, PC or similar device have heard of “top models” or “fashion models”. The “fashion model” as well the “role model” are idealized types of people, the first type considering mainly the appearance characteristics that makes a person attractive for presenting fashion, while the second considers mainly the characteristics that other people would want to copy. Both categories represent some idealizations in which some characteristics, qualities or features are evidenced.
     When one speaks about fashion models one can easily come with some names of such models who were en vogue over the years. On the other side maybe for many will be more difficult to come with names of people who can be considered as role models, unless they had in their life people who functioned as role models. A “role model” seems to be more abstract as concept than the “fashion model”, as the physical qualities are easier to grasps then the inner qualities. There can be defined qualities like success, confidence, hardworking or sociability that are attributed to both roles. In fact the qualities of the two concepts can intertwine to the degree that for some people a fashion model and role model may be defined by the same qualities, or the differences are so small that they can be ignored.

Fashion mode vs role model

    Based on the two examples we can construct now a definition. Let’s consider a model as an idealization of a concrete or abstract object, in which some characteristics, qualities or features are considered as important and definitory.

    The definition seems to be concise, clear, objective and precise, as much such a definition can be, so it looks like a good definition one can work with. The question is whether the praxis might invalidate it, where the gap between it and other definitions from technical literature is so big that makes this definition unusable. At least the following definitions seem to accord:

A model is a simplification of reality intended to promote understanding.” [1]
Models are replicas or representations of particular aspects and segments of the real world.” [2]
A model is a representation of reality intended for some definite purpose .”[3].
A model is an imitation of reality.” [4]
A model is a representation of some subject matter.” [5]

    From my point of view all these definitions aren’t good definitions because by attempting to be too general they lack precision. Is it any representation of some subject, of reality or part of it a model? Probably not! This raises another question: what isn’t a model? Unfortunately the answer isn’t that simple. Not any representation of something can be considered a model. Is it for example a cubistic representation of an object a model? The answer is again no! The model needs to keep certain characteristics of the object intended to represent, though more about it in other posts.

    Here are a few other alternative definitions for models:
A model is a physical, mathematical, or logical representation of a system entity, phenomenon, or process.” [6]
model: the artificial object which explains all the empirical facts under consideration” [7]

Models in Context

    Depending on the context in which is used, the concept of model is more elaborated and adapted as needed. One can talk about business, conceptual/thinking, mental, mathematical, statistical, scientific, mechanistic, behavioral, structural, social, political, logical, data or diagrammatic models. In fact models are the cornerstone of all sciences and pseudo-sciences, the foundation on which our understanding and knowledge is based upon. From the inner to the outer world, from simple to complex activities, from mathematics to religion, we use models on a daily basis. We think in models, or at least we use models in our thinking even if we are not aware of it.

    From the literature reviewed over the years it can be observed that most of the definitions converge within the same boundaries, the difference residing mainly in the vocabulary used – idealization and characteristics being replaced by the family of words from the below table:





     In various sources the denomination of model is substituted with synonyms that make better appeal of people’s understanding: pattern, example, emulation, analogy, visualization, system, replica, mold, mock-up, sketch, prototype, wireframe, schema, blueprint, (visual) aid, image (also picture, depiction), map, theory, principle, approximation, representation, allegory, metaphor, archetype, etc. All these can be considered upon context models, even if they might refer to totally different things.


    Even if our thinking became more complex, the average individual juggling with increasingly abstract concepts, it seems that we fail to define basic concepts like the one of model. Starting from two examples I attempted to provide a good definition one can work with. I tried also to provide a mechanism that can be used to extrapolate definitions for similar concepts.

[1] SystemsThinking.org (2004) Models, by Gene Bellinger 
[2] Data Modeling Fundamentals: A Practical Guide for IT Professionals, by Paulraj Ponniah, John Wiley & Sons, ISBN: 978-0-471-79049-5, 2007
[3] Tools for Thinking: Modelling in Management Science, 3rd Ed., by Michael Pidd, John Wiley & Sons,
ISBN-13: 978-0470721421, 2009
[4] Process Systems Engineering: Process Modelling and Model Analysis Vol. IV, by Ian T. Cameron, Katalin M Hangos, Academic Press,
ISBN-13: 978-0121569310, 2001
[5] Workflow Modeling: Tools for Process Improvement and Applications Development, 2nd Ed, by Alec Sharp Patrick McDermott. Artech House,
ISBN-13: 978-1-59693-192-3, 2009
[6] Systems Engineering Fundamentals. Defense Acquisition University Press, 2001
[7] The Concept of Model: An Introduction to the Materialist Epistemology of Mathematics, by Alain Badiou, re.press,
ISBN-13: 978-0980305234, 2007


12 October 2014

Professional Defects and Thinking Models

Professional Defects

    I heard of “professional defect” almost 15-20 years back, in a colloquial discussion with an acquaintance. I don’t remember anymore the context entirely, though as I used it then, it became part of my vocabulary. With time “professional defect” meant for me “seeing and judging the world through the knowledge of our profession, and ignoring or misinterpreting thus some (important) aspects of our quotidian life”.  I’m not sure whether the term is actually in use or a similar term is used to reflect this aspect. I met occasionally similar constructs later, some of my German colleagues stressing the fact that sometimes we have to take out our professional glasses in order to see things differently (e.g. take out or put our managerial glasses). A generalization can be met in De Bono’s six thinking hats – the hats representing in De Bono’s perception the distinct six ways in which people think about the world, each of them stressing an import aspect of reality and our thinking patterns.

    While in school, preparing for our profession, and especially later when we arrive to practice it, we acquire a knowledge base, the facts about the world, a set of thinking models that provide an approximation of the world in which our profession is anchored, and heuristics, algorithms” of thinking and decision making that form with time thinking patterns. They help us understand situations and solve problems in our professional life. They add up to our previous personal experience accumulated over the years. In fact we’ll more likely attempt at first to use some of the experience we acquired before attempting a profession, some of the knowledge, models and heuristics being validated or invalidated in our professional life. With time we arrive to use some of the models we exclusively acquired and verified in professional life also in our personal life. This translation may seem natural as professional life extends itself sometimes beyond the borders of our profession – some coworkers become our friends, we spend more and more time in communities related to our profession, we meet similar problems in the two areas as of life, etc.

    This extension from professional to personal life can have positive as well negative implications. It is true that some models from professional life can help us figure out some aspects from personal life, we arrive maybe to validate and improve our models, reaching somehow a deeper understanding of life. The problem comes when we ignore that we deal with a different type of environment, with its own characteristics, with different groups of people having higher diversity and other characteristics than the ones we meet in professional life. As the premises, the environment and its actors change, some of the models need some tweaking or they become unusable in our personal life. Maybe the number of such cases is incomparable small when we regard other type of thinking fallacies we fall into on a daily basis, though as long they arrive to define us and our choices in one way or another, we need to take a step back and look at them.

Some Examples

    There could be found multiple examples in which the thinking patterns and models about the world we “learned” in our profession are used outside the professional life. Sometimes they look at the world by generalizing the characteristics of the individuals, focusing typically on a single aspect of the human nature, making totally or partially abstraction of the whole.  It’s also a sequel of the analytic way of thinking about the world we’ve been exposed from the early years of school. A more appropriate way of studying, understanding and modeling the human nature is by following the systemic thinking view in which the human being is more than the components that builds it – the body, the psychological, the language, the character, the behavior ranging from simple movements to complex forms of expression, the creativity, the ways of thinking transposed in decision making and the philosophy about life, that include the religious and the spiritual, the experience, the community the person belongs to, and so on. Some of these aspects are interrelated and mold together, and as the human they are a part of the complex web of life we belong to.

    Unfortunately, our models about the world are quite simplistic and inflexible, as long we keep them so and as long we can’t discover and build more complex models. Before jumping to further aspects about models let’s look at a few examples. They might not be representative, they might be a little brought to extreme, though they are met in life and affect us in one form or another.

    For example, a mathematician or somebody with strong mathematical background arrives to think of the world around him in terms of probability for an event to happen. On one side this can prove as a powerful tool to quantify and predict such events, though might make the person ignore the area of impossible, expressed maybe in opportunities with small chances to happen, opportunities that when considered could have a huge impact on his live. It’s a trivial example of the attempt to quantify and simplify the world to a degree that makes it understandable and predictable, mathematician’s luggage of models being more complex than that. Judging the words of wisdom of some mathematicians, they seemed to arrive to a deeper understanding of life - spirituality, philosophy, literature and wit melting in mathematician's life. Still anyone can be entrapped in the fallacies of the cold mathematical thinking about life in which everything is reduced to a representational model.

     Not far from the previous example, a philosopher builds in his mind a world of ideas, and sooner or later arrives to evaluate the world around and his personal interactions with the world based on the philosophical currents he adheres to. No matter how complete and well-established a philosophy is, it’s a human based system of beliefs and models, with its loops and wholes. Sooner or later the philosopher will find himself trapped in the threads of his own philosophy as long he applies it too deep und unaware into his personal life. From this perspective it will be hard for a philosopher to be happy and content with his life.

    A psychologist or somebody with a similar background may arrive to judge the people outside his praxis based on the traits they reveal. A chemist or biologist may see human’s constitution governed by a chain of chemical reactions, reducing thus feelings and behavior to them. A doctor may start to see in people the predispositions to or existence of a given disease, arriving maybe to judge people based on certain predispositions. A dentist might start evaluate people based on the denture they have. A sales person might start to acquire new friends (exclusively) based on the predisposition of buying a product. Accountants and the other financial professionals might see the world around them through financial models and wealth. An artist may treat as inferior people those who don’t exhibit any artistic skills. A priest may see the people around him as sinners.

   There are many other examples, each profession comes with own type of similar fallacies. Think about your profession or the professional environment you belong to! More likely you’ll discover similar examples. How deep have they penetrated in the human society? How much have they influenced or still influence you? How could you escape them?

A Jump to Thinking Models Fallacies

    Models are a good way to represent and approximate the world around us and predict behavior, though paraphrasing George Box, all models are to some degree wrong. Sometimes is enough if a model is right once in a while, other times we need to have reliable models. In general acceptance the success of a particular model is tied to its ability to cope capture the behavior of the real world, while its reliability is proportional to the number of cases it does so. When dealing with people often we need reliable models. It’s a question of ethics, but primordially of chances we lose to meet new interesting people, new experiences, and why not in overcoming our current condition.

    Relying too much on a model make us vulnerable to a range of events that are not addressed by our models. Some of the presumptions on which such models are built upon, same as the limitations of our thinking models can get easily forgotten in our decision making process. We become then the prisoners of a set of (thinking) patterns from which will be impossible to exit unless we realize their traps. This actually applies to all type of models we built along the years. Some of them are rooted deeply in our beliefs on how the world (environment) around us works or is supposed to work.

    Not only the beliefs we have, but also the models we acquired and use make us filter the signals, events or information from our environment. What we consider in a model is as important as what we leave out. The components removed by reducing the world to a model can be quintessential in what concerns the understanding and why not the living of life as a whole – the religious, the spiritual, the favorable chance, the free will, the tipping point, the random, the potential of people or groups to raise above some condition(s). No matter how well established some models, there will always be exceptions. We should expect for such exceptions to happen. They should make us challenge and enhance our models.

   Going beyond the limitations of our models can prove to be a considerable challenge. We need to challenge our models on a daily basis, their visible and hidden premises, recognize their advantages, disadvantages and area of applicability. We need to detach ourselves from the models we’ve built, adapt them or learn new similar models that complement or counterbalance the existing models. Each model offers in the end a glimpse of truth, though we’ll mistake if we consider it the ultimate truth.

02 January 2013

Is the Dot-Com Bubble 2.0 on its Way?


 The First Dot-Com Bubble

    The dot-com bubble (aka Internet bubble) refers to the time period between 1995 and early spring of 2000, when the American economy underwent through a considerable boom, fact reflected in the increase in stock prices, especially the one associated with Internet-related assets [1]. The principal fuel for dot-com bubble seems to be the Internet and its huge potential for high-tech as well for non-high-tech companies. Data were communicated in real time at affordable prices, through web sites companies were having the potential of being known and of reaching potential customers all over the world, universities and companies could easier collaborate. It was the naissance of Internet phone, multicasting, e-commerce and e-auction portals, online banking and collaborative tools. The enormous potential was increasingly reflected in the news. Forbes and Wall Street Journal were encouraging people to invest in risky companies [4]. The public awareness was increasing [1], and the offer was huge. If previously a company needed to have had at least several profitable quarters before it went public, by 1999 the restrictions were relaxed considerably, it was enough to have a sketchy business plan, an Internet address and a few people who could speak the right jargon [1]. Numerous start-ups entered the marked over night, their entry being facilitated by the lower entry cost associated with the innovation [3], the sudden appearance of new niche markets and the demand coming from early adopters, eager to make most of the new technologies.

    Many start-up companies like Google, Amazon or Netscape haven’t made a profit during the first years, however the high IPO value of their stocks allowed them to raise a substantial amount of money [4]. As the stocks of many companies were skying high, more and more money were pushed in the economy, many of the investments being driven by the mirage of getting rich over night. The investments in software, computer and communication equipment companies grow, IT becoming an important component of the US economy [2]. In fact, by October 1999, the stock value of the six biggest IT companies – Microsoft, Intel, IBM, Cisco, Lucent and Dell - was 20 percent of the US GDP [5]. Cities in US, trapped by the dream of becoming a new “Silicon Valley”, invested in their communication infrastructure and built network enabled offices to attract internet entrepreneurs [4]. Europe joined the rush as well, telecommunication companies investing in 3G licenses [4], companies were expanding to accommodate the increase demand coming from US.

   Excessive IT investment, overconfidence and other factors made the bubble to burst in the spring of 2000. It was a turning point for the American economy as well for Europe, the dot-com stocks falling down, following the exit and bankruptcy of many dot-com companies. It was also the chance for other IT and non-IT companies to take over the assets of fallen companies. It was the time for acquisitions and mergers in order to survive the crisis. It was an opportunity for innovation to propagate and workforce to migrate from company to company. The investments in IT infrastructure continued moderately also after the burst, the economy revigorating itself slowly but steadily.

The Second Dot-Com Bubble?
   Marc Andreeson, founder of Netscape, pointed out recently that “the ideas on the internet in the 1990s are all happening now” [7], and he seems to be right. The overevaluated IPOs of social networking companies like LinkedIn, Facebook or Groupon [6] seem to support the premises of a second dot-com bubble (aka dot-com bubble 2.0, to follow the trend, social networking bubble or social media bubble). Of course, social networks companies have a huge potential especially in what concerns the harnessing of collective intelligence and the diffusion of information, with application in multiple domains, but there is lot of work ahead until harnessing this potential. The boom of fancier and miniaturized electronic devices, plus the promises of Social Media, Web 2.0 and thinking further of the Semantic Web (aka Web 3,0), Big Data, Cloud Computing, Personal Cloud, Integrated Ecosystems, Enterprise App Stores and other technologies (e.g. in-memory computing, HTML5, Silverlight) seems to multiply exponentially the value of data, technology and networks. There are lots of opportunities for companies to appear over night, for small and average companies to grow, and for big companies to consolidate their position on the market. There is also lot of optimism in what concerns the future of the Web on one side, and the Web-centric organizations and business models on the other side, but is this optimism entitled? Could the boom of these technologies corroborated with the “this-time-is-different” syndrome and ignorance of history, facilitate the appearance of a second Internet bubble?  For sure that’s possible, but hopefully it won’t become reality, at least not in the near future. Hopefully the markets have learned something from the past…

Beyond Bubbles

  Despite the negative effects the dot-com bubble had or might have at micro and macro level, I strongly believe that on the long term economies have the capacity to recover, and sometimes such bursts are necessary for the restructuring and re-leveling of values. Despite any future crisis, the Internet will continue its development fueled by the need for more capable technologies and, where technologies and needs are, investments more likely will follow.

[1] G. Callahan, R. W. Garrison () Does Austrian Business Cycle Theory explain the Dot-Com Boom and Bust? [Online] Available from: http://mises.org/journals/qjae/pdf/qjae6_2_3.pdf (Accessed: 31.08.2012).
[2] Wikipedia (2012) Web Development. [Online] Available from: http://en.wikipedia.org/wiki/Web_development (Accessed: 31.08.2012).
[3] http://www.aeaweb.org/annual_mtg_papers/2007/0107_1300_0902.pdf
[4] Wikipedia (2012) Dot-com bubble. [Online] Available from: http://en.wikipedia.org/wiki/Dot-com_bubble (Accessed: 01.09.2012).
[5] M. Buttel (2010) 10 Years On: When the bubble burst. Financial Services Technologies. [Online] Available from: http://www.fsteurope.com/news/when-the-bubble-burst/ (Accessed: 01.09.2012).
[6] North American Value Investing. (2012). Are We in Another Dot Com Bubble? [Online] Available from: http://navinvesting.blogspot.de/2012/05/are-we-in-another-dot-com-bubble.html (Accessed: 02.01.2013)
[7] D. Soskin, (2012) Is the dotcom bubble 2.0 set to burst? [Online] Available from:  http://www.growingbusiness.co.uk/dot-com-bubble-2-0.html (Accessed: 02.01.2013)

Note: The current post was adapted after my assignment submission for the Internet History Technology and Security Coursera Course.

05 November 2011

Nowadays Frustrations of Software, Devices and Services – The PDF Editor for Tablets

    We are dreaming about a Semantic Web, about semantic, intelligent and multifunctional tools and devices, though the paradox is that most of the software and electronic devices out there don’t address basic needs! Frankly I don’t care if my device can talk with my refrigerator and can make a list of what I need to buy, or that my book reader recommends me other books, based on what I read or browse. Sure, this kind of functionality is nice to have, though I can live without it and sometimes I found it irrelevant or even annoying, as the recommendations are fuzzier than the techniques they use. The example of books reader is not random, because my recent frustrations are related to it.

    Two years ago or so I bought a Digital Book Reader from Sony (Sony PRS-700BC), I founded it great at those times especially because it allowed me to annotate, highlight, extract and review the extracted text from a document (See Finally the Digital Book Reader). Unfortunately the functionality was not scaling good with documents’ size, waiting sometimes for half a minute until the change was made and I could continue to read. In some cases, I was spending more time on waits than on reading. In addition the display of formulas and images was quite problematical, being almost impossible to read a technical book. And then appeared the tablet…

   I found iPad a little too expensive for my reading needs, so I waited until Toshiba’s Folio 100 appeared on the market, almost in anonymity. It was much cheaper than the iPad, was having a 10.1 inch  widescreen display, relatively a small weight, and thus ideal for reading. In addition, the future support for Flash made it a good candidate for watching video learning content, another of my request. In three words: I loved it (and I still do). When I started to use it, I was kind of disappointed, because in came only with FBReaderJ reader, too limited for my needs and useless for my small electronic library mainly composed of PDF, DJVU and DOC files. After a short visit in Toshiba Market Place available through my tablet’s application, I bought myself, for small money, Documents To Go from DataViz Inc, a Software for viewing and editing of Microsoft Office 2007 documents, and for viewing PDF documents. A few months later I discovered in the same store the Office Suite Pro from MobiSystems, which provided almost same functionality as Documents To Go, with a plus for PDF viewer because it kept track of the page I was last time viewing and the scrolling of pages was more stable. There were PDF documents I could read with one software and not the other, and vice-versa, so they were kind of complete each other, however I was having two problems:
- there were PDF books I couldn’t read correctly with any of the two applications.
- my reading experience was quite static as I was having no possibility to annotate or highlight the text. It’s true that Documents to Go allowed me to copy a chunk of text, though because it doesn’t remembered the page I was in, the feature was almost useless.

   A few months ago, during the summer more exactly, given the fact that both solutions deal pretty good with Word files, I thought of converting some of the important PDF files to Word. My first thought was to check first the Adobe site. As they have nice tools and even nicer prices, I ended by buying Nitro PDF Professional. It covered the functionality I needed, unfortunately the size of output files and the conversion of images and formulas was not functioning as expected. I managed to address the first issue by splitting the initial PDF files in smaller files, and then convert them to Word. It worked, though it remained the problem of formulas and images, and they were present in most of the books I read.

   This week, taking advantage of some free time I had, I tried to look more into this. Toshiba’s Market Place was not offering other software for PDF so I had to look somewhere else, and the best place seemed to be the Android Market, where a multitude of software products wait for mobile and tablet proud owners. I found several PDF readers and editors, and in the end I decided to go for RepliGo Reader from Cerience. What appealed to me was the fact that I could cross and underline text, or add sticky notes in PDF files. Its price, 3.99 was quite appealing so there I am proceeding to check out, and then the surprise – I can’t buy it! I tried to go around the message: “There are no Android phones associated with this account.”. I checked the help, the various functionality, of how I can register a device, though I kind of lost myself in there. Finally I arrived to Google Mobile and everything looked like it made sense, I thought… I was following my own tail. As it seems, you can buy a product only if you are having an Android device with a phone number, that passed Google’s compatibility requirements. In addition, “manufacturers must obtain a license from Google in order to install Android Market on their devices”, so if your device isn’t in the list of Supported Devices, then there is no way you can consider the Android Market! Folio 100 isn’t in there, so I can go and … anyway, there must be other way!

   Frustrated I searched on Google if RepliGo Reader is available from other sources. My first stop was on Amazon where RepliGo Reader was available for 4.99. Good! I’m progressing. I downloaded Amazon Appstore (Amazon_Appstore-release.apk) and installed it on my Folio. It works great but it doesn’t do anything no matter what button I click. I tried to install it several times, without success. Probably the application isn’t compatible with my device. Who knows?

    Even more frustrated I checked on Android Market several PDF readers, trying to see if I can buy them from other stores. Again, no luck! During my searches I observed that Adobe has finally a reader for mobile devices (iOS & Android), the Android version being available only through Android Market. WTF!!! (pardon my language) I continue to search and discover a few sites of file sharing, though that’s not a solution! Finally I find a blog post on Adobe site with a link to a FTP location where Acrobat Reader can be downloaded. I installed it and it seems it works. It has very basic reader functionality (more basic it can’t be), though it comes from Adobe and is supposed to render with high fidelity PDF documents. As far I tested it, I’m having problems with the scanned old books that come from Google Books. It seems Adobe has several other products for mobile market (e.g. CreatePDF, Photoshop Express), reflecting that they are moving onto this market too.

    I continued searching and thus I found the AppBrain site. I tried to download RepliGo Reader, though the installation doesn’t work neither on my built-in browser, nor on Opera. Then I fond out that I have to install the Fast Web Installer and AppBrain App Market. Great, they I can’t install them neither! I searched for them on Google and I discovered them on Handster (here and here). I installed them without problems, though it seems AppBrain App Market uses Android Market, and as I don’t have it I can’t go any further. In the end I found Android Market 3.2.0 from APKTOP. I tried to install it but it didn’t work. Later I found a post from TalkAndroid, where is specified that the device need to be rooted – getting root access to the file system. I found an “How to Root Toshiba Folio 100” article, though it hasn’t helped too much, Super One Click freezing each time I started to use it.

    Browsing through APKTOP website, I found out several downloadable PDF reader apps available also on Android Market: RepliGo Reader, Documents To Go, Go Book, Acrobat Reader 10.1, EBookDroid, Aldiko Book Reader, etc. They are quite cheap on Android Market and some even free, though as they aren’t available for devices as mine, I would expect users will go and downloaded from such more or less legal sites. Excepting the legal issues, there are also some security concerns, some of such applications could be tampered, so you are using them on your own risk!

    Looking back at this long story and the long hours I spent attempting to find a PDF reader with annotation capabilities, I have to highlight several points:
1. It’s incredible how un-intuitive are web sites like Android Market or AppBrain Market. Un-intuitive not necessarily from the perspective of navigability, but of not making visible aspects like: how, why, where, why not!
2. I wonder why Toshiba doesn’t comply to Google’s compatibility requirements? Maybe they tried to make a honest buck through their store, but then why haven’t tried to attract more apps vendors and have more applications ported on their device.
3. I observed that there are great apps out there, though because they are sold only through sites like Android Market reduces considerably vendor’s profits!
4. I don’t understand why even if some apps are Free, Goggle still imposes restrictions on who can download them. I would expect that they try to force vendors to comply to Google’s compatibility requirements. Is this the way to go?
5. It seems the speed with which smartphones and tablets entered the market has created some breaches in vendors’ strategy, breaches from which the customers will suffer, and indirectly the vendors themselves. Here I could put the lack of compatibility and adherence to standards, lack of documentation and tools.
6. I’m afraid apps vendors will arrive in media vendors position of blaming people for pirating software. Even if apps are cheap, the inexistence of an adequate infrastructure for making apps available, will lead more likely to such issues.
7. Frankly it sucks to spend so many hours in order to find, install and troubleshoot software! All I was looking for was an app that allows me to read and annotate or highlight text in a PDF document. It isn’t rocket science! I would even expect to have such a software coming by default with a tablet, given that’s one of the main purposes of such a device.

23 July 2011

Search Queries Tools – Part II: Soovle

    Soovle is a customizable engine that provides suggestion services from several major search engines (e.g. Google, Yahoo, Bing, Answers) and content providers (e.g. Amazon, YouTube, Wikipedia), several others being available within just a simple drag and drop away (see Engines).  Soovle blog provides additional information, like a short history of the tools used for developments (current version was built with jQuery) and several tips. You should check the demo too, even if the tool it’s quite easy to use.

    I tried Soovle using as input the “knowledge” keyword:

search comparison - Soovle knowledge google

    As can be seen, excepting several common terms (e.g. “knowledge”, “knowledge management”), the output for each engine it’s quite different. Because there is no visual aid, the extraction of common terms between engines it’s not so easy as it should be. Maybe something should be done in this direction – for example using colors, font weight or sorting.

    When multi-term words are used (e.g. “data information knowledge wisdom”) the output becomes difficult to read, so maybe some styling would be useful in order to help determine the start/end of a group of terms.

    Currently, the tool allows selecting a group of 7, 11, respectively 15 search engines. It would be useful to reduce maybe the number of search engines and increase the number of terms, allowing to compare the results for only 2-3 search engines. A matrix (terms vs. engines) could facilitate maybe the visualization of data.

    As it seems the spaces influence the output, for example “DIKW” vs. “DIKW ” vs. “ DIKW” will return different results.

    I really like the fact that by providing a first letter of the second term (e.g. “knowledge a”), the output can be limited only to the terms whose second terms start with the specified letters. (I needed this kind of functionality some time ago and I had to rely entirely on Google’s autocomplete feature.)

    I was searching for my favorite quote from J. Keats “a thing of beauty is a joy forever” (with quotes). Unfortunately, none of the default 7 engines returned the quote, even if Bing’s result included some “joy”-related results. I tried the same search directly in Google and Bing, and matches were found?! Same result for “joy+forever”. Without some deeper knowledge of the architecture of the search engines and the tool itself, it’s hard to find what causes this behavior or to identify some of the differences in processing.

Comment: In the initial post it seems I misquoted Keats. I can't recall if then I used the misquoted chunk of text or the actual quote. Rechecking Soovle, it actually returns results for Google, YouTube and Bing.

Search Queries Tools – Part I: Web Seer

    Since quite some time, Google provides an autocomplete feature extended to combinations of words. That’s quite an useful feature because often it “saved” my time from typing full words or combinations of words. What’s interesting is that the autocomplete algorithm provides the terms based on user’s search activities. I was asking myself if we could do more with search queries. This evening, while browsing, I discovered A. Smarty’s post on “How To Visualize and Play with Google Suggest Results”, in which she shortly presents three interesting tools: Web Seer, What do you suggest and Soovle. As I found out there are several other tools like Übersuggest, Quintura, etc. In this post I will focus only on Web Seer, following to review shortly several other similar tools in the next posts.

   Web Seer allows users to compare the “matches” between two Google queries, for example “are man” vs. “are women”, “will he” vs. “will she”. To remain in blog’s thematic , I checked tool’s output for “data” vs. “information” and “information” vs. “knowledge”:

search comparison - data vs information

    The query results for both terms are somehow predictable – “data mining”, “data warehouses”, “data entry” and “data values”, respectively “information architecture”, “information management”, “information security”, “information technology”, “information is beautiful” (see also the book) are quite popular terms in the scientific and non-scientific literature.  I would expect the comparison is based on the most popular terms, because the two concepts don’t share many common terms, and even if there are some common terms within the above results (e.g. “data architecture”, “data systems”) they aren’t highly ranked. Arrows’ weight depicts the number of occurrences of the respective terms, which combined with the terms themselves, help to make an idea of the strength and resemblance existing between two concepts.

    Climbing the DIKW scale here are the comparisons between information and “knowledge”, respectively “knowledge” and “wisdom”:

search comparison - information vs knowledge

search comparison - knowledge vs wisdom

    As it seems the results are consistent between relations, same combinations being used in two comparisons in which the same term is involved, life in the above diagrams. It’s natural that the results are also commutative, in order words “knowledge” vs. “information” renders same result as “information” vs. “knowledge”.

search comparison - knowledge vs information

    The association is also reflexive:

search comparison - information vs information

    And transitive, as “data” vs. “information”, and “information” vs. “knowledge” lead to “data” vs. “knowledge”:

search comparison - data vs knowledge

    The algebraical operations are not so important, though some consistency of the results is needed between representations. It’s interesting that the comparison is influenced by a space placed at the beginning (e.g. “ data”) or end (“data ”), as can be seen in the following representation of the two:

search comparison - data vs data

    I would expect other similar signs (e.g. punctuation signs, special characters) influence the comparisons too. Talking about DIKW, the knowledge pyramid, let’s see the comparison between “DIKW” and “data information knowledge wisdom”:

search comparison - DIKW   

   As the two concepts have close semantics, “DIKW” is the acronym for “data information knowledge wisdom”, here’s the comparison between two synonyms: “distribution” vs. “diffusion” (like in distribution/diffusion of knowledge). As can be seen the association is stronger.

search comparison - distribution vs diffusion

    Actually the first attempt with the tool was a comparison “concept map” vs. “mind map”:

search comparison - concept vs mind map

    Which looks slightly different than “concept maps” vs. “mind maps” (so the plural form of words introduces variances):

search comparison - concept vs mind maps

    Considering the few examples run, the tool is quite intuitive and catchy. I would consider its utility as relative, even if the above examples are not representative and the relationships between them are more contextual.  Still it’s a good tool for identifying automatically the relations/associations between concepts, to identify associations’ strength and maybe several semantic connotations.  It would be interesting to see only the common terms, as many K-maps focus on this aspects, to introduce language and context, and the possibility to compare more than two terms (for example using Venn diagrams) or to show more/less common terms.

30 April 2011

Weighted Categorization of 4 Knowledge Maps

    Last year I was brainstorming with M. Mahmoud on a weighted categorization of various Knowledge Maps (K-Maps), this as input for his Diploma paper. He focused only on Mind Maps, Conceptual Graphs and Concept Maps, considered by us as mature enough and rich in expressing the various facets of knowledge. We came up with the following tables which could be used to evaluate the value of each K-Map based on a mixture of criteria provided by [1] and [2], considered also in [3]: content type, recipient type, content formats, layout, creation mode, purpose, knowledge type, visualization type, graphical form and function type. Each criteria is weighted on a 1..5 scale, from weak to strong. A downside of the below tables is that they were based on our understanding of the respective K-maps and were not based on survey or any other types of scholastic techniques, so the values should be used with caution. We also attempted to evaluate the K-maps from the perspective of humans (H) and computers (C), as the two type of M-map consumers come with different requirements. We find out that the evaluation of K-maps from this perspective isn’t so easy to achieve, not being aware of the all results in the field, the lack of time being other important consideration. We managed to apply this distinction only to content type, where a value of 2H refers to human, while a value of 2C refers to computers. The values considered for the other categories are considered only from the perspective of humans. What is missing from these tables, in respect to the initial tables, are the comments made to the some of the below evaluations.

Content Type

Mind Maps

Conceptual Graphs Ontology Concept Maps Weight Notes
Methods  2H, 2C 2H, 2C 4-5H, 2-3C 3H, 3C 2  
Processes 2H, 2C 1H. 1C 4H, 3C 4H, 3C 3  
Experts 5H, 2C 3H, 3C 5H, 2C  5H, 2C 3  
Organizational subdivision 5H, 1C 1H, 3C  5H , 1C 5H, 1C 2  
Lessons Learned and experiences  4H,1C 3H, 4C 3-4H, 1C  5H, 2C 3  
Skill and Competencies 5H, 2C 3H, 2C 5H, 2C  5H, 2C 3  
Concepts 4-5H, 3C 3-4H, 3C 5H, 3C 5H, 3C 5  
Events 4-5H, 3C 3-4H, 3C 5H, 3C 5H, 3C 4 same as concepts
Patents 2H, 1C 2H, 1C 3H, 1C 3H, 1C 2  
Communication flow 4-5H, 4C 4-5H, 4C 4-5H, 4C 4-5H, 4C 5  
Interest or Knowledge needs 4-5H, 2C 4-5H, 2C 4-5H, 2C 4-5H, 2C 4  
Recipient Type Mind Maps Conceptual Graphs Ontology  Concept Maps Weight Notes
Individual  5 4 4 5 5  
Team 5 4 5 5 3  
Organization And Networks 5 3 5 5 3  
Dyadic 5 4 4 5 4 same as individual
Departmental  5 4 5 5 2 same as team
Community  5 3 5 5 3 same as organization
Inter-Organization Maps 5 3 5 5 2 same as organization
Content Formats Mind Maps  Conceptual Graphs Ontology Concept Maps Weight Notes
Websites 5 3 4 5 3  
Documents  4 4 4 4 4  
DataBases or Repositories 5 5 5 5 5  
Learning Object  5 3 5 5 2  
Online Courses  3 1 3 3 3  
Notes taking 4 1 2 4 4  
Layout Mind Maps Conceptual Graphs Ontology  Concept Maps Weight Notes
Chained 3 4 5 5 3  
Clustered 5 2 5 5 4  
Hierarchical  5 3 5 5 4  
Radial 5 1 4 5 3  
Networked 5 3 5 5 5  
Creation Mode Mind Maps Conceptual Graphs Ontology Concept Maps Weight Notes
Manual 5 3 4 5 5  
Automated 2 3 2 2 3  
Semiautomated 3 4 3 3 3  
Collaborative 5 4 5 5 4  
Purpose Of KM Process Mind Maps Conceptual Graphs Ontology Concept Maps Weight Notes
Knowledge Creation 5 2 4 5 3  
Knowledge Assessment  or audit 5 3 4 5 4  
Knowledge Identification 5 4 5 5 4  
Knowledge Development or Acquisition 5 3 4 5 4  
Knowledge Transfer 5 2 4 5 5  
Sharing Or Communication 5 2 4 5 5  
Knowledge Application 4 3 5 4 3  
Knowledge Marketing  Maps 4 2 2 3 2  
Knowledge Type Mind Maps Conceptual Graphs Ontology Concept Maps Weight Notes
Know-What 5 4 5 5 5  
Know-Who 5 4 5 5 5  
Know-Why 5 4 5 5 5  
Know-Where 5 4 5 5 5  
Know-Who 5 4 5 5 5  
Visualization type Mind Maps Conceptual Graphs Ontology  Concept Maps Weight Notes
Sketch 3 1 2 4 4  
Diagram  3 1 2 3 3  
Image 3 1 2 3 2  
Map 2 1 2 2 2  
Object 1 1 2 2 3  
Interactive Visualization 3 1 3 3 4  
Story 3 2 2 3 4  
Graphical Form Mind Maps Conceptual Graphs Ontology  Concept Maps Weight Notes
Table 2 2 3 3 3  
Base Map     3 3 3 3 3  
Diagrammatic Maps 3 3 3 3 3  
Cartographic Maps  3 1 4 3 2  
Geographic Maps 3 1 4 3 2  
Heuristic Maps 3 1 3 3 3  
Metamorphic Maps 2 2 3 3 4  
Interactive Maps  4 2 3 4 4  
Mental Maps 4 2 2 3 4  
3D Maps 4 1 2 2 4  
Function Type Mind Maps Conceptual Graphs Ontology  Concept Maps Weight Notes
Coordination  3 2 4 4 5  
Attention  3 1 2 3 4  
Recall 4 1 2 4 5  
Motivation 3 1 2 4 3  
Elaboration  4 2 4 4 5  
New Insight 4 3 4 4 5  

[1] Burkhard, R., Meier, M., Smis, M., Allemang, J., Honisch, L. (2005). Beyond Excel and Powerpoint: Knowledge Maps for the Transfer and Creation of Knowledge in Organizations. Proceedings of the 9th International Conference on Information Visualisation, p76-81. [Online] Available from: http://ieeexplore.ieee.org/Xplore/login.jsp?url=/ielx5/10086/32319/01509062.pdf?arnumber=1509062  (Accessed: 13 March 2009)
[2] Eppler, M.J. (2008). A Process-Based Classification of Knowledge Maps and Application Examples In: Knowledge and Process Management, Vol15, No1, p59–71. John Wiley & Sons. [Online] Available from: www.interscience.wiley.com (Accessed: 13 March 2009)
[3] Nastase, A. (2009). Utilizing Mind Maps as a Structure for Mining the Semantic Web. [Online] Available from:  http://www.scribd.com/doc/16612282/Dissertation-paper-Utilizing-Mind-Maps-as-a-Structure-for-Mining-the-Semantic-Web (Accessed: 20 June 2009)
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