We present here the last version of Darwin Methodology initially created to “see the Web more and better” that evolved to see the Web as a World of Avatars instead, cyber creatures that represent our past and present ideas and thoughts and even all type of intellectual speculations about our possible futures. This idea is not new: it goes back along centuries diluted and hidden as archetypes and models like “Romeo and Juliet”, “Don Quixote”, “Ulysses”, “Democracy”, “El Príncipe”, the Avatars of Hinduism, and actually as Cyber creatures by visionaries and scientists like Stephen Hawking. Why was it hidden for so long? Because only from very recently exist suitable cyber reservoirs to host The ALL almost “naturally”, openly and freely: The Web.

1. The Web as a World of Avatars
ANWOT - A new Way of Thinking
By Juan Chamero, from Barcelona, Spain, as of May 30th
2016
Avatar (2009 film), from Wikipedia
Introduction
We present here the last version of Darwin Methodology initially created to “see the Web more
and better” that evolved to see the Web as a World of Avatars instead, cyber creatures that
represent our past and present ideas and thoughts and even all type of intellectual speculations
about our possible futures.
This idea is not new: it goes back along centuries diluted and hidden as archetypes and models like
“Romeo and Juliet”, “Don Quixote”, “Ulysses”, “Democracy”, “El Príncipe”, the Avatars of
Hinduism, and actually as Cyber creatures by visionaries and scientists like Stephen Hawking. Why
was it hidden for so long? Because only from very recently exist suitable cyber reservoirs to host
The ALL almost “naturally”, openly and freely: The Web.
This presentation could be considered our third e-book of the Mind to Digital Series. It has five
sections namely:
i. Darwin Methodology Last Update deals with the idea of Web avatars fundamentally the
new Darwin Ontology Conjectures to cover this revolutionary vision;
ii. Darwin in a nutshell is a synthesis of Darwin methodology in order to see the Web as
semantically structured however not enabled yet to see it as a world of avatars;
iii. Darwin Demo deals with the details of The Art Thesaurus unveiled from the Web via a
Darwin AI Mega Algorithm and presenting Darwin as ANWOT, A New Way of Thinking;
iv. Darwin Project stands for Darwin as a Project to map and unveil absolutely EVERYTHING
disperse and hidden in the Web;
v. Darwin Tests and Reflections deals with some paradox and crucial tests performed by
Darwin Methodology along the last decade and some Web examples about concepts
versus words architectures semantic search superiority (See Kentucky Woodman!).

2. Darwin Methodology Last Update
 Darwin Ontology Adjustments, 1 page;
 Darwin avatars buildup in 12 big “industrial steps” analogy, 4 pages;
 Darwin Methodology – To “see” the Web more and better, avatar seeds, 12 pages;
 Darwin Ontology – Conjectures, 4 pages;
Darwin in a nutshell
 Darwin in a nutshell Index, 1 page;
 Darwin Brief, 1 page;
 Darwin Methodology, 2 pages;
o Darwin Carousel, 5 pages;
o Darwin Maps Build, 3 pages;
o Darwin Big Data, 3 pages;
o Darwin Icons Meanings, 5 pages;
 The Web as seen by Darwin Methodology, 3 pages;
 Darwin Bibliography, 1 page;
Darwin Demo
 A picture is worth a thousand words, 1 page;
 Intro to Darwin Art Map, 6 pages;
 Darwin Mapping History, 9 pages;
 Darwin Semantic Search, 19 pages;
 Q&A Logic of Web Search, 9 pages;
 The Art Tree Darwin Demo, 13 pages;
 Darwin Presentation (PPT), 25 pages; see pages 284 to 308;
Darwin Project
 Darwin Teaser, 11 pages;
 Darwin HKM (PPT), 75 pages; see pages 209 to 283;
 Present and Future of Web Searching, 4 pages;
 DM Mega Algorithm, 4 pages;
 Aiware Methodology, ikAK, 3 pages;
 Semantic Pills, within a Big Data Thesaurus, 35 pages;
 HKM Synthesis, HKM in numbers, 4 pages;
Darwin Tests and Reflections
 Wikipedia avatar, 3 pages;
 Word Searching Weakness, 1 page;
 Differences between data information and knowledge, 3 pages;
 The Web for fun, “who’s on first?, 2 pages;

3.  Crucial questioning, 4 pages;
 Kentucky Woodman, 3 pages;
 Human Knowledge Disciplines, 13 pages;
 Words versus concepts, 5 pages;
 Mathematics seed, 7 pages;
Epilogue
We intended to depict in this e-book a semantic tour around the Web using as a “cicerone” our
Darwin Methodology. We have “seen” semantically and at our will hundreds of thousands of
Websites related to our needs of data, information, and knowledge and even of intelligence. As a
consequence of our guided e-learning we acquire a valuable cyber wisdom we want to transmit.
If we were challenged to explain shortly the rational of our alleged “acquired wisdom” we would
recommend overview our Darwin Tests and Reflections section thru a mini tour as follows:
 Wikipedia avatar: it shows us the best we can do working conventionally, at large
subjectively via real or alleged authorities;
 Word Searching Weakness: it shows the intrinsic weakness and misleading ambiguity of a
trivial search like for example “dog”;
 Differences between data, information and knowledge: in fact at present we ignore what
are these differences scientifically talking. Notwithstanding we consider the above
hierarchical sequence a strong and valuable belief. There are hundreds of alleged
authoritative versions about it such as the one commented;
 The Web for fun: we use one of the most famous Abbot & Costello “routines” who’s on
first to exemplify the semantic confusion generated by bad and/or incorrect use of words;
 Crucial questioning: here we present the hardest Artificial Intelligence experts questioning
about Darwin namely: Darwin versus Google search; successfully high impact and/or
disruptive applications uses examples; Darwin ability to work within the Dark Web;
 Kentucky woodman: a semantic analysis of the term associated to Abraham Lincoln as
avatar unveiling the Web as_is departing from Zero Knowledge;
 HK, Human Knowledge Disciplines: A whole Web Thesaurus would cover about 200
disciplines. We have arrived to that estimation that upgraded from 150 at the beginning of
the 2000 depending of what we mean by “branch of knowledge”. See a brief exploration
about it as of 2014;
 Words versus Concepts: it is the summary of a Darwin workshop seminar held in 2015
about word versus concept and their associated universes and in mind images;
 Mathematics seed: example of a Semantic Seed buildup performed by Dr Eduardo Ortiz
and its team of PhD postulants about Mathematics and tested as trustable by Darwin
agents. Dr Ortiz is emeritus professor of Mathematics and History of Mathematics at the
Imperial College of London.

4. Darwin Ontology Adjustments
By Juan Chamero as of February 19th 2016
The Al is mentally imagined (“in mind image”):
Keeping it in mind – Poetry By Heart, Oxford Dictionaries
Prologue
This brief document deals with crucial Cyberspace fundamental findings. Documents reviewed have been
biographies and classic essays, to my knowledge, related to the scope of our ontology namely: Galileo
Galilei, Claude Shannon, Alan Turing, Roger Penrose, Albert Einstein, Stephen Hawking, Plato, René
Descartes, John Von Neumann, Nikola Tesla, Jaime Balmes, The Tao Te Ching book, Zen writings nucleated
around Bodhidharma, The Bible: Genesis, The Apocalypses and why not something about The Pope Francis,
Saint Augustin, Teilhard de Chardin and Umberto Eco, an atypical intellectual cocktail isn’t ?!
Because these rehearses surged a new updated Darwin Ontology to “see the ALL more and better”. Perhaps
this ALL be the common mind image the intelligence cocktail components share: Rational: a) Our mind
process continuously information and knowledge; b) this help us to live more and better; c) via intuition and
knowledge humans document their acts and experiences, let’s say their knowhow and living avatars.
Stephen Hawking states that these registrations (for example in books and in the Cyberspace) would be as
important as our lives. As a preliminary thinking he suggests that the image of the whole world as_is as
today and probably seeds of our future could be expressed in the Web. Provided this assert is true we would
be less of what we really could! (And even without recurring to God).
Note: does these assertions sound a little as science fiction for you? It would be equivalent to say that via
ontologies like Darwin we are enabled to know not only the best possible truths but the absolute best ones!
And all this without creating nothing new at human or artificial Intelligence level, simple unveiling all the
pieces of truth that somehow are disperse and semi hidden in the Web: almost a paradox of negentropy!
The adjustments have been synthesized in a 4 pages document denominated “avatar_buildup”. Its first page
deals of Darwin as unveiling avatars diluted in the Web. Within this vision a Darwin outcome as the Human
Knowledge Map would be simply a Human Avatar, big one and complex but at last an avatar! The second
and half of the third page is devoted to the epilogue that resumes the Darwin Ontology adaptations
performed in order to unveil not only what is actually visible but what is actually hidden or invisible as
avatars. These adjustments close our ontology with a finishing touch! => Back

5. Darwin avatars buildup in 12 big “industrial steps” analogy
ANWOT, A New Way Of Thinking doc, by Juan Chamero, from Spain as of February 15
th
2016
Face avatars from Deleket
Introduction
Avatars: cyber creatures that represent and guide, generally as archetypes, our lives. If we as humans have
defined our reason for living and our relation with THE PERCIEVED ALL throughout the cognitive hierarchy
data, information, knowledge and wisdom, we may assume that the avatars are creatures that represent
and help us to make a meaningful use of this hierarchy to solve and/or “to see” meaningfully any imagined
subject. Avatars are in mind images however not all in mind images are avatars. Avatars are then creatures
that in some extent represent us, our existence, our past and what we expect for our future as well.
Let’s imagine a world without humans but with the Web space “alive” as it is now: a sort of Cyber Sea where
live trillions of in mind images and avatars! We are used to see and to understand all type of in mind images
via trillions of explanations and descriptions documented in all the existent languages and cultures. As
eventual intelligent “aliens” we may imagine well how insects behave, how illnesses evolve, what a storm is,
and even what are more abstracts and complex things like hate and love. In Hinduism an avatar is an
incarnation or deliberate descent of a deity or Supreme Being to Earth.
In Darwin Ontology it is supposed that in the Web co-exist all imaginable avatars, for instance The Pope
Francis avatar as of today would be a creature that resume absolutely EVERYTHING we as humans “see”, as
related to the pope investiture, to the Catholic church and to its avatars along time, that is to say to Jesus, to
the Saints and prophets, to all type of passions from the compassion of Jesus to the tortures of the “Santa
Inquisition”, to all types of adhesions – rejections from atheism and agnosticism to the highest apologies of
faith, nor leaving outside the human Jorge Bergoglio as a person and his family and entourage.
Darwin Ontology enable us “to see” more and better the Web, and of its creatures, something similar to the
Galileo Galilei exploration of the sky thru its telescope. It enable us to unveil not only all the disperse pieces
of information and knowledge of all avatars but also the hidden intelligence that maintain them united as
entities. Within this paradigm would also be avatars all the big problems of the humanity. Let’s imagine now
we are commissioned to build a big and complex avatar like for instance Barack Obama, the Pope Francis,
the Refugees Problem, The EU Future, the Terrorism, the Democracy Evolution, the Genre Violence, etc. Do
not discourage everything is “up there” disperse but hidden in the Web Sea!

6. Avatar Buildup
Step 1 – Semantic Exploration: Perform a first approach to the avatar: review the Web content with our
mind focused in finding names, traces, features, images, audios, text samples, memes, tags, collectives,
visible authorities; defining a first set of semantic axes of an hypothetic avatar “semantic seed”.
Step 2 – Semantic Resonance Exploration: Unveil the “names” of the first approach: each in mind image
has, for a given pair language – culture, a sort of “resonance name” like radio waves: asking conventional
search engines by these names they point to the best answers, in quantity and semantic quality. For
instance exploring the semantic neighborhood of these best names you may experiment significant changes
with minimum and/or negligible written or pronunciation differences. Resembling humans criteria Darwin
agents detect the best names for a given in mind image.
Step 3 – Identifying suspected Authorities realms: Pivoting and exploring websites content around
resonance names, for instance building hyperlinks versus hyperlinks matrices, will provide us raw data for
next step: namely chains (including closed loops) of meaningful related hyperlinks names semantically
weighted.
Step 4 – Unveil possible “conceptual graphs”: basically a human task: an expert or a group of experts
analyze the unveiled raw data looking for conceptual graphs to feed next step. At this step the global
structure of the avatar should be depicted and properly documented.
Step 5 – Unveil possible “semantic seeds”: basically a human task guided and aided by agents.
Step 6 – Select the best semantic seed: basically a human task. As the “hard” process, computationally
talking (+85%) begins next step, the selection must be backed up and justified as much as possible.
Step 7 – Make the semantic seed grow: there are many ways to make the semantic seeds grow “properly”,
however under the same ontology, depending of the nature, complexity and size of the avatar. One of the
simplest ways is to expand the initial names realm (the one that backed up the semantic seed unveiling),
let’s say from 50 to 100 names to a realm of a few thousands. For each semantic seed name it is unveiled
from the Web a “texton” a sort of logical huge vector built of pieces of content of the 500 to 1,000 top
websites retrieved. Darwin methodology states that within this huge sample it is meaningfully represented
the avatar, basically all its derived names and their logical probably locations within its logical semantic
skeleton. Darwin algorithms and agents make all the computations but humans are responsible of selecting
criteria of naming expansion and locations adjusting. As an outcome of this step we have our avatar
predefined but fuzzy as seen through a cloud: for instance as a set of 1.200 names related to the avatar but
still poorly structured along a conceptual graph of 500 nodes.
Step 8 – Specific Concepts unveiling: Darwin Ontology states that we humans, as a collective, document
according to a probabilistic “formula” (something like a WWD, Well Written Document formulae) using only
two kind of semantic particles: Common Words and Expressions and “specific concepts” closely related to
the in mind image we have in our minds about the main document subject. This specificity acts as a
semantic filter that aid us to see more and better the semantic skeleton of the avatar. Following our
example we arrive to a name realm of 1,500 terms and to a semantic skeleton of 450 nodes.

7. Step 9 – Check the Ontology Conjectures accomplishment: This is a necessary, hidden and heavy task
mostly performed by Darwin algorithms. We have to take into account that only long lasting and complex
avatars tend to structure like logical trees, like for instance Maps of Knowledge. Most avatars will have semi
arboreal structures however in part resembling directed graphs: this directionality enable us to activate
semantic ancestry and all types of parental relations via conventional search engines, for instance that
“popularity” rank tend to be higher with ancestry.
Step 10 – Evaluate the whole process and results: We may arrive to this step many times when building
complex avatars as a checking point of an iterative process that runs from step 1 to here.
Step 11 – Intelligent Report for Humans; First raw avatar synthesis: This is a human task. It resembles an
essay or a book editing with its corresponding Prologue, Epilogue, Introduction, Abstract, Index,
Bibliography and very important: its metadata structured as [avatar definition, Authorities and their profiles,
semantic and Web references, images, videos and audio, selected quotations, tags and memes].
Step 12 – Avatar buildup: it is a continuous task because avatars evolve and at the same time we evolve in a
sort of exponential e-learning process. Along circa 8,000 years the human being built something like an
avatars world library somehow ruled by a world plutocracy in a rare pairing between the wisdom of an
insignificant minority and the disproportionate power hold by another insignificant minority. At large the
Established Knowledge, the best truths, were those issued by geniuses, illuminated and powerful people and
entities. However the best truths should take into account the in mind images of information, knowledge,
opinions and why not the wisdom of we ALL humans as a collective of unique individualities. Now after more
than 80 centuries it is perfectly possible!
Epilogue
Darwin Ontology defines the life and interactions of Web Cyber creatures as a dual interacting scenario
depicting: The “K Side” or World of the Established Knowledge versus the “K’ Side” or World of the People.
Daily life avatars are usually hosted in K’ Side meanwhile formal long lasting avatars are generally hosted in K
Side.
Avatars popularities: as per Google we may distinguish avatars (pointing to 419,000,000 References) as a
single word concept and as the core of the expression "the avatars of life", (as a closed search within
quotation marks pointing to 54,000 References). Curiously the Spanish expression “Los avatares de la vida”
collects 233,000 References perhaps because within Spanish literature the term is misleadingly used as
synonym of circumstances.
Some definitions for avatar: “learning a second language” avatar draft written by students of the USC, US.
o The incarnation of a Hindu deity, especially Vishnu, in human or animal form.
o An embodiment or manifestation, as of a quality or concept:
o An icon, graphic, or other image by which a person represents himself or herself
o A digital construct (often an image file) that represents the online user in a virtual world.
We invite you to see a pre avatar buildup around the subject “How the world see us” restricted to Spanish
students of a second language, probably English, in an American university. As you may easily appreciate it is
incomplete and rather biased: authors “take side” openly and too frequently.

8. What’s life? What we present as avatars sounds a little disrupting a strange combination of knowledge and
intuition because these “virtual” creatures – avatars – could be all and nothing and for some cosmologist like
Hawking more alive and transcendental than humans. We invite you to imagine what’s real about them in
physical terms, matter, namely space and mass within the whole known universe: almost nothing, under all
cosmic scales close to absolute zeroes.
Note 01: Let’s try to imagine all forms of life distributed and diluted, in the average (for example in a ratio 1:1000) over the layers of the
biosphere, from the superior atmosphere and going deep a few hundred meters below surface, as compared to the Earth radio of
6,378,000 meters. It gives us almost zero mass respect to our planet, probably the only one with suspected life within our galaxy!
In Hawking words: …..”This has meant that we have entered a new phase of evolution. At first, evolution
proceeded by natural selection, from random mutations. This Darwinian phase, lasted about three and a half
billion years, and produced us, beings who developed language, to exchange information. But in the last ten
thousand years or so, we have been in what might be called, an external transmission phase. In this, the
internal record of information, handed down to succeeding generations in DNA, has not changed
significantly. But the external record, in books, and other long lasting forms of storage, has grown
enormously. Some people would use the term, evolution, only for the internally transmitted genetic material,
and would object to it being applied to information handed down externally. But I think that is too narrow a
view. We are more than just our genes. We may be no stronger, or inherently more intelligent, than our cave
man ancestors. But what distinguishes us from them, is the knowledge that we have accumulated over the
last ten thousand years, and particularly, over the last three hundred. I think it is legitimate to take a broader
view, and include externally transmitted information, as well as DNA, in the evolution of the human race”……
Bibliography
1. Life in the universe, by Stephen Hawking suggest the following evolution scheme: Energy => elementary particles => pre RNA
“accidents” => RNA => DNA => seeds of life => language => written language => “External” Evolution;
2. The Anthropic Principle, from Wikipedia: ….”The anthropic principle (from Greek anthropos, meaning "human") is the philosophical
consideration that observations of the universe must be compatible with the conscious and sapient life that observes it. Some
proponents of the anthropic principle reason that it explains why the universe has the age and the fundamental physical constants
necessary to accommodate conscious life. As a result, they believe it is unremarkable that the universe's fundamental constants happen
to fall within the narrow range thought to be compatible with life”……
3.CHON and CHNOPS: CHON is a mnemonic acronym for the four most common elements in living organisms: carbon, hydrogen,
oxygen, and nitrogen. The acronym CHNOPS, which stands for carbon, hydrogen, nitrogen, oxygen, phosphorus, sulfur, represents the
six most important chemical elements whose covalent combinations make up most biological molecules on Earth. Sulfur is used in the
amino acids cysteine and methionine. Phosphorus is an essential element in the formation of phospholipids, a class of lipids that are a
major component of all cell membranes, as they can form lipid bilayers, which keep ions, proteins, and other molecules where they are
needed for cell function, and prevent them from diffusing into areas where they should not be. Phosphate groups are also an essential
component of the backbone of nucleic acids and are required to form ATP – the main molecule used as energy powering the cell in all
living creatures. Carbonaceous asteroids are rich in CHON elements. These asteroids are the most common type, and frequently collide
with Earth as meteorites. Such collisions were especially common early in Earth's history, and these impacts may have been crucial in
the formation of the planet's oceans. => Back

9. Darwin Methodology - To “see” the Web more and better
Building an avatar seed
As seen by a Zen master - AI builder
By Juan Chamero, from Spain as of February 27th
2016
Galileo Galilei looking the sky, Wikipedia and many others sources
“To see more and better” avatar
Darwin Ontology states that the Web is a big Cyber Ocean that hosts Cyber Creatures named
“avatars” that register the Avatars of the Human Being, that is to say our vicissitudes, what
happen to us, what we think about everything and anything. The registration units are Home
Pages so within each of them could be avatars and/or pieces of avatars. This vision enable us to
see the whole Web like a dual scenario where we humans live continuously “emitting” messages –
aware or unaware of it - that are continuously registered by a sort of multimedia Cyber Ocean.
This document intents to describe how to devise an avatar seed about Darwin Methodology based
on a sample of well known quotations and inspirations related to human visions of the ALL
namely:
Galileo Galilei, Claude Shannon, Alan Turing, Roger Penrose, Albert Einstein, Stephen Hawking,
Plato, René Descartes, John Von Neumann, Nikola Tesla, Jaime Balmes, the Tao Te Ching book, Zen
writings about Bodhidharma, the Bible: Genesis, Apocalypses book and why not something about
Pope Francis, Saint Augustine d’Hippo and from Teilhard de Chardin, an atypical intellectual
cocktail isn’t?
Note: Umberto Eco was recently added to our inspirers list as a posthumous homage. We recommend to
read its book “How to write a Doctoral Thesis” similar to our Darwin avatar unveiling process performed
manually.

10. Galileo Galilei
Eppur si muove!, and yet it moves!
In 1633 after being forced to recant his claims that the Earth moves around the Sun
Galileo Galilei works inspired Darwin Ontology “to see more and better the Web” by inventing the
telescope “to see more and better the Sky”.
Claude Shannon
I just wondered how things were put together
Information is the resolution of uncertainty
Two Claude Shannon quotes from brainyquote.com. We human are in debt after its apparently
simple, astonishing and disrupting Theory of Information. We wrongly claim that we are in the Era
of Knowledge however we have still to make our homework to go a little ahead of Shannon within
the Information Era. Darwin makes its own homework along that line.
Alan Turing
Science is a differential equation; Religion is a boundary condition
Alan Turing could be considered the father of the Computing Science “avatar” in full as of today, a
real genius well endowed in almost everything and also pioneer of the thinking machines utopia.
He suggested that machines may think a crucial and long lasting controversial subject: A computer
would deserve to be called intelligent if it could deceive a human into believing that it was
human.

11. Roger Penrose
There are two other words I do not understand — awareness and intelligence.
Roger Penrose argues that the present computer is unable to have intelligence because it is an
algorithmically deterministic system against the viewpoint that the rational processes of the mind
are completely algorithmic and can thus be duplicated by a sufficiently complex computer. See
controversial with Marvin Minsky, that say exactly the opposite: that humans are, in fact,
machines, whose functioning, although complex, is fully explainable by current physics, See also
GoogleTechTalks.
Albert Einstein
Learn from yesterday, live for today, hope for tomorrow. The important thing is not to stop questioning.
Albert Einstein: what to meaningfully add to our avatar about science, knowledge, wisdom and
consciousness? We only dare to select some of its quotes:
o It has become appallingly obvious that our technology has exceeded our humanity.
o The true sign of intelligence is not knowledge but imagination.
o Logic will get you from A to B. Imagination will take you everywhere.
o Science without religion is lame, religion without science is blind.
Coexistence of dualities: Wave–particle duality is the fact that every elementary particle or
quantic entity exhibits the properties of not only particles, but also waves. It addresses the
inability of the classical concepts "particle" or "wave" to fully describe the behavior of quantum-
scale objects: As Einstein wrote: "It seems as though we must use sometimes the one theory and
sometimes the other, while at times we may use either. We are faced with a new kind of difficulty.
We have two contradictory pictures of reality; separately neither of them fully explains the
phenomena of light, but together they do".

12. Stephen Hawking
We are all now connected by the Internet, like neurons in a giant brain.
The Web Ocean hosting all Human avatars: In Hawking words: …..”This has meant that we have entered a
new phase of evolution. At first, evolution proceeded by natural selection, from random mutations. This
Darwinian phase, lasted about three and a half billion years, and produced us, beings who developed
language, to exchange information. But in the last ten thousand years or so, we have been in what might be
called, an external transmission phase. In this, the internal record of information, handed down to
succeeding generations in DNA, has not changed significantly. But the external record, in books, and other
long lasting forms of storage, has grown enormously. Some people would use the term, evolution, only for
the internally transmitted genetic material, and would object to it being applied to information handed down
externally. But I think that is too narrow a view. We are more than just our genes. We may be no stronger, or
inherently more intelligent, than our cave man ancestors. But what distinguishes us from them, is the
knowledge that we have accumulated over the last ten thousand years, and particularly, over the last three
hundred. I think it is legitimate to take a broader view, and include externally transmitted information, as
well as DNA, in the evolution of the human race”……
Plato
Wise men speak because they have something to say; Fools because they have to say something
This quote from Plato is a brief and antique example of semantic subtleness: two extreme “in mind
images” (wise – fool) expressed in a given language (English in this case) as a misleading similarity.
The theory of Forms (or theory of Ideas) typically refers to the belief that the material world as it
seems to us is not the real world, but only an "image" or "copy" of the real world. In some of
Plato's dialogues, this is expressed by Socrates, who spoke of forms in formulating a solution to
the problem of universals. The forms, according to Socrates, are archetypes or abstract
representations of the many types of things, and properties we feel and see around us, that can
only be perceived by reason (Greek: λογική).

13. René Descartes
Cogito ergo sum; Je pense, donc je suis; I think, therefore I am; Pienso luego existo
Descartes may be considered the father of the modern western philosophy and for many also of
the 17th-century continental rationalism, later advocated by Baruch Spinoza and Gottfried Leibniz.
See its Discourse on the Method and its four rules:
 "The first was never to accept anything for true which I did not clearly know to be such; that is to say, carefully to avoid
precipitancy and prejudice, and to comprise nothing more in my judgment than what was presented to my mind so clearly
and distinctly as to exclude all ground of doubt.
 The second, to divide each of the difficulties under examination into as many parts as possible, and as might be necessary
for its adequate solution.
 The third, to conduct my thoughts in such order that, by commencing with objects the simplest and easiest to know, I might
ascend by little and little, and, as it were, step by step, to the knowledge of the more complex; assigning in thought a certain
order even to those objects which in their own nature do not stand in a relation of antecedence and sequence.
 And the last, in every case to make enumerations so complete, and reviews so general that I might be assured that nothing
was omitted."
John von Neumann
With four parameters I can fit an elephant, and with five I can make him wiggle his trunk
There probably is a God. Many things are easier to explain if there is than if there isn't.
John von Neumann was the missing piece of the Cyber Era: a genius and a “doer” of the
everything! The above quotes speak by themselves.
About the hidden sides of many scientific milestones: John von Neumann, for many the father of
Modern Computing suggesting to Claude Shannon a name for his new uncertainty function: You
should call it entropy, for two reasons. In the first place your uncertainty function has been used
in statistical mechanics under that name, so it already has a name. In the second place, and more
important, no one really knows what entropy really is, so in a debate you will always have the
advantage.

14. Nikola Tesla
Every living being is an engine geared to the wheelwork of the universe. Though seemingly affected only
by its immediate surroundings, the sphere of external influence extends to infinite distance.
Nikolas Tesla, perhaps the best modern avatar of the “inventor” and of the inventive was a Serbian
American electrical engineer, mechanical engineer, physicist, and futurist best known for his
contributions to the design of the modern alternating current electricity supply system. See some
quotes from its autobiography:
 Instinct is something which transcends knowledge. We have, undoubtedly, certain finer fibers that enable us to perceive
truths when logical deduction, or any other willful effort of the brain, is futile.
 do not think there is any thrill that can go through the human heart like that felt by the inventor as he sees some creation of
the brain unfolding to success... such emotions make a man forget food, sleep, friends, love, everything.
 It seems that I have always been ahead of my time. I had to wait nineteen years before Niagara was harnessed by my
system, fifteen years before the basic inventions for wireless which I gave to the world in 1893 were applied universally.
Jaime Balmes
Entendemos más por intuición que por discurso: la intuición clara y viva es el carácter del genio
Father Jaime Balmes y Urpiá (Catalan: Jaume Llucià Antoni Balmes i Urpià; 28 August 1810 – 9 July 1848) was
a Spanish Catholic priest known for his political and philosophical writing. In some extents he could be
considered a “Common Sense Philosopher”.
 La lectura es como el alimento; el provecho no está en proporción de lo que se come, sino de los que se digiere.
 Me convencí de que dudar de todo es carecer de lo más preciso de la razón humana, que es el sentido común.
 Terrible es el error cuando usurpa el nombre de la ciencia.
Balmes distinguishes between the concept of truth and the concept of certainty. Truth is the
expression of the agreement of the ideal order with the thing. Certainty is the mental acceptance
of the truth. There are two kinds of certainty: general human certainty (acquired spontaneously
and instinctively), and philosophical certainty (the fruit of intellectual reflection).

15. Bodhidharma (Zen)
As long as you look for a Buddha somewhere else,
you'll never see that your own mind is the Buddha.
 If you use your mind to look for a Buddha, you won't see the Buddha.
 The mind is the root from which all things grow if you can understand the mind, everything else is included.
Zen, quantum mechanics, Yin – Yang, Tao Te Ching, mind, awareness, consciousness, ontologies,
Tai Chi, Kung Fu and more….: Bodhidharma, the Zen creator, was a Buddhist monk who lived
during the 5th or 6th century. He is traditionally credited as the transmitter of Chan (Zen)
Buddhism to China, and regarded as its first Chinese patriarch. According to Chinese legend, he
also began the physical training of the monks of Shaolin Monastery that led to the creation of
Shaolin Kung Fu. Darwin Ontology has something of Zen that states that the underlying base of
reality is change, process and impermanence relatively in slow motion and that the observer is
part of the system……The strange interactions of fundamental particles with the mind of the
observer ('quantum weirdness') have long been of interest to philosophers. There are two
opposing views: (i) Quantum weirdness produces the mind, versus (ii) The mind produces
quantum weirdness. See log about Buddhism, Quantum Physics and Mind.
Genesis – The Tower of Babel
The word is the Verb and the verb is God (Victor Hugo)
A Semantic Enigma: Is it an enigma or a warning light? Why so many and so different languages?
Is really the Verb the creator of the Everything? The Tower of Babel (/ˈbæbəl/ or /ˈbeɪbəl/;
Hebrew: ‫ל‬ ַּ‫ד‬ְ‫ג‬ ִ‫מ‬ ‫ל‬ ֶ‫ב‬ ָּ‫ב‬, Migdal Bāḇēl) is an etiological myth in the Book of Genesis of the Tanakh (also
referred to as the Hebrew Bible or the Old Testament) meant to explain the origin of different
languages. According to the story, a united humanity of the generations following the Great Flood,
speaking a single language and migrating from the east, came to the land of Shinar (Hebrew:
‫שנער‬). There they agreed to build a city and tower; seeing this, God confounded their speech so
that they could no longer understand each other and scattered them around the world.

16. Apocalypses (Revelation)
We are just an advanced breed of monkeys on a minor planet of a very average star. But we can
understand the Universe. That makes us something very special (Stephen Hawking)
Revelation 19:11-21 And I saw heaven opened, and behold, a white horse, and He who sat on it is
called Faithful and True, and in righteousness He judges and wages war. His eyes are a flame of
fire, and on His head are many diadems; and He has a name written on Him which no one knows
except Himself. He is clothed with a robe dipped in blood, and His name is called The Word of God.
Pope Francis
Oh, how I would like a poor Church, and for the poor.
A leading exponent of the word sacralization and vulgarization at the same time
 Oh, how I would like a poor Church, and for the poor.
 We must restore hope to young people, help the old, be open to the future, and spread love. Be poor among the poor.
We need to include the excluded and preach peace.
 I am always wary of decisions made hastily. I am always wary of the first decision, that is, the first thing that comes to my
mind if I have to make a decision. This is usually the wrong thing. I have to wait and assess, looking deep into myself,
taking the necessary time.
 Sometimes negative news does come out, but it is often exaggerated and manipulated to spread scandal. Journalists
sometimes risk becoming ill from coprophilia and thus fomenting coprophagia: which is a sin that taints all men and
women, that is, the tendency to focus on the negative rather than the positive aspects.
“The internet …,” writes Pope Francis today, “offers immense possibilities for encounter and
solidarity. This is something truly good, a gift from God.” See Communication at the Service of an
Authentic Culture of Encounter": Pope's Message for World Communications Day.

17. Saint Augustine
The world is a book, and those who do not travel read only a page
Men go abroad to wonder at the heights of mountains, at the huge waves of the sea, at the long courses of the rivers, at the vast
compass of the ocean, at the circular motions of the stars, and they pass by themselves without wondering.
Augustine of Hippo (/ɔːˈɡʌstᵻn/ or /ˈɔːɡəstɪn/; Latin: Aurelius Augustinus Hipponensis; 13
November 354 – 28 August 430), also known as Saint Augustine, Saint Austin, or Blessed
Augustine, was an early Christian theologian and philosopher whose writings influenced the
development of Western Christianity and Western philosophy.
Sayings about Quantum Physics, time and Saint Augustine: In the Confessions of St. Augustine,
Book IX, Chapter X (chapter 9, section 10) there is a philosophical analysis of time. Though
Bertrand Russell was an atheist and says that he has a different philosophy of time than Augustine,
in his History of Philosophy, Russell nevertheless less says that Augustine's philosophy of time is
deeply profound. Among other conclusions, Augustine states that both the past and the future
exist simultaneously, and yet only the now exists. And that in God there is no time.
Teilhard de Chardin
The universe as we know it is a joint product of the observer and the observed.
Relevant concepts concerning Darwin Ontology: noosphere, prolegomena about The All, and
Omega Point. Pierre Teilhard de Chardin SJ (French: [pjɛʁ tejaʁ də ʃaʁdɛ̃]; 1 May 1881 – 10 April
1955) was a French philosopher and Jesuit priest who trained as a paleontologist and geologist
and took part in the discovery of Peking Man. He conceived the idea of the Omega Point (a
maximum level of complexity and consciousness towards which he believed the universe was
evolving) and developed Vladimir Vernadsky's concept of noosphere.

18. Darwin Ontology (I)
In any piece of the ALL you may see the ALL
This e-book depicts a long Semantic Web scouting along 11 years from two points of view: from
Digital to Mind along W3C standards and from Mind to Digital for many the "Common Sense
Way". The outcome of this journey is Darwin, a semantic ontology to "see the Web as semantically
structured" through a sort of "Semantic Eyeglasses". These virtual eyeglasses like the Galileo
Galilei telescope enable us to Map the whole Web as_is and to build Semantic Super Search
Engines that work at mode YGWYN in only one query.
Darwin Ontology (II)
Everything connected with everything
The Web is a layer on top of Internet that for many belongs to the people. In my humble opinion
this was not planned, but an accident, the consequence of the appearance of a revolutionary
technology as it happens along the evolution. Before Internet arrival communications media,
newspapers, Radio and TV worked unidirectional, from a de facto “Established Order” side to the
“People’s” side “broadcasting” programmed pieces of information and knowledge, from sellers to
buyers, from rulers to ruled, from teachers to students, from truth holders to truth seekers. The
Peoples’ side is explored via Darwin, an AI Ontology that enable us to see the Web more and
better focusing in Social Networks and the Deep Web, for many the hidden Web. As a demo a
Darwin agent makes over Established side a “tomography” for the theme art history, from
Altamira Caves to Nanoart.

19. Umberto Eco
Umberto Eco quotes by relatably.com
The last but not the least! I included Umberto Eco – the genial Italian author and semiologist
recently deceased - as representative of one out of many Darwin Ontology hidden influencers.
Read “come si fa una tesi di laurea”, how to write a doctoral thesis.
o But now I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by
our own mad attempt to interpret it as though it had an underlying truth.
o Captain Cook discovered Australia looking for the Terra Incognita. Christopher Columbus thought he was
finding India but discovered America. History is full of events that happened because of an imaginary tale.
Conclusions
We need a semantic ontology to see the Web more and better: what are the four crucial questions
we must ask ourselves?
 What do we have at hand?
o Data, Information, Knowledge, Wisdom
o Intelligence
 What should we have to unveil?
o The ALL
o The Everything Connectedness
o The Man Machine utopias
 What should we have to consider in the ontology?
o To unveil all type of Avatars;
o To unveil Semantic Logical Trees structures;
o To unveil all type of Directed Graphs;
o To unveil and manage K versus K’ namely: Websites versus Users dialogues;
o To unveil K Thesaurus, namely: formal Knowledge Thesaurus;
o To unveil K’ Thesaurus, namely: Users Knowledge Thesauruses;
o To take into account and continuously check that HK is bounded;
o To take into account and continuously check that HK’ is bounded;
o To take into account and continuously check the semantic weight of WWDs, Well Written Documents;
o To take into account and continuously check the Semantic Resonance of accomplishment unveiled concepts;
o To take into account and continuously check the In mind images uniqueness for all languages;
o To take into account and continuously check the Concepts Uniqueness for all languages;
o To take into account and continuously check the Concepts Specificity accomplishment and uniqueness for all languages;
o To unveil the best sets of Authorities for any subject;
o To check continuously that the ontology is fully accomplished by the Semantic seeds;
o To check continuously that Semantic fingerprints are appropriately computed for any subject;
o To check continuously that Semantic metadata are appropriately computed for any subject;
o To check continuously all type of intrusions warning and estimating their pollution effects;

20. World Authorities Influence Logic Matrix
Once defined – as a fact - our major Darwin Authorities Influencers we proceed to briefly depict
either the semiotic – semantic aspect or facet influence of each of them over our ontology. This
matrix behaves as a philosophical and scientific support about a complex problem: How to see the
Web more and better.
For instance one of the Darwin Conjectures states that the Web space is structured as a dual
system and continuous interacting worlds: K Side or Established Knowledge (Websites owners,
authors and administrators) versus K’ Side or People Side (we, humans as Internet users): Albert
Einstein, Stephen Hawking, and Bodhidharma are notorious influencers.
Another example concerns what we defined as “Semantic Resonance”: Our Darwin Ontology also
states that for a given pair “language – culture” we may unveil millions of “in mind images”. These
images are recognized by their “names”. It also states that they could be unveiled by the
phenomenon of “Semantic Resonance”: any in mind image could be retrieved via Conventional
Search Engines, by many different “names”, however only one of these names will be the semantic
winner in terms of quantity and quality of references.
 Galileo: the meaning of “To see more and better” and tools to perform it;
 Shannon: The actual Web is not yet semantic; intuitive ideas trying to understand
“knowledge” meaning by enriching and extending the meaning of ”information”;
 Turing: limits of Web unveiling by huge and exhaustive procedures – Big Data -;
 Penrose: Human Intelligence is more than algorithmically deterministic system;
 Einstein: coexistence of dualities; intelligence is much closer to imagination that to
knowledge;
 Hawking: cyber avatars; coexistence of dualities; externally transmitted information as
important as internally transmitted via DNA and genes to evolve;
 Plato: in mind image, forms and avatars; the essence of concepts as semantically specific
universals;
 Descartes: The Discourse of the Method in its full and ample sense;
 Von Neumann: entropy, negentropy, and Big Data within ontology concerns;
 Tesla: inventive avatars axes; ideas about Darwin Intelligence Reports buildup;
 Balmes: Logic versus Common Sense concerning trees, arboreal logic, semantic
resonance…);
 Bodhidharma: quantum physics and mind; coexistence of dualities; avatars; awareness;
 Genesis: The Power of Semantics; The Power of Words;
 Apocalypses: The ALL, The EVERYTHING and the END; black holes;
 The Pope: as a typical Darwin avatar archetype:
 Saint Augustine: only the NOW exists; time inexistence utopias;
 Teilhard: The Noosphere;
 Darwin: The Semantic Ocean  Semantic Web  Noosphere;
 Eco: ideas about how to build trustable IR’s;
=> Back

21. Darwin Ontology - Conjectures
By Juan Chamero, from Spain at March 30th
2016
Conjectures Subjects Overview
Darwin Ontology enables humans to “see more and better” the Web throughout the ontological
and computational guide of its Conjectures. This vision involves seeing the Web as totally indexed
by meanings, approaching as much as possible to the Semantic Web utopia and the detection and
retrieval of all type of data, information and knowledge disperse on it. Conjectures subjects follow:
1 (a) A world of human “in mind images”;
2 (b) A world of “words”;
3 (c) A quantifiable and bounded World;
4 (d) A world of probabilistic nature;
5 (e) A nominative world: all its creatures have a name;
6 (f) A world of semantic vibrations;
7 (g) A world of avatars;
8 (h) Avatars library;
9 (i) Retrieval of hidden intelligence;
10 (j) Knowledge DIKW;
11 (k) A world of Arboreal Structures;
12 (l) Avatars unveiling and IR’s, IdeI’s;
13 (m) K versus K’ worlds;
14 (n) K versus K’ Semantic interchange;
15 (o) Two types of Semantic Particles;
16 (p) e-membranes and unveiling without perturbing;
17 (q) Disciplines of Knowledge, WWD’s and WFF’s;
18 (r) Subjects and Concepts;
19 (s) Knowledge Authorities;
20 (t) Human Knowledge, Thesauruses and Derived Concepts;
21(u) Thesauruses for K and K’;
22(v) Semantic Web;
Avatars Conjectures: Internet and particularly the Web enable humans to keep a huge, open and in extreme detail virtual log book of
our lives, of our occurrences, activities and even of our thoughts and “in mind” processes along time as well. The entries of this log
could be assimilated to “avatars” in their different acceptations namely from graphic representations of all type of things and entities
including personalities and investitures to incarnation of deities or facets of them and of ideal creatures. Avatars could also be imagined
like “meaningful in mind images” that need to be “explained” to be understood. Conjectures in emerald deal with avatars.
Semantic Web Conjectures: We may also see the Web as a huge multimedia reservoir structured as a dual and continuous interacting
world: one we name as “K side” assigned to formal creatures registering the “Established Knowledge” at a given moment and the other
we name as K’ side assigned to the people as users and at the same time proprietors of the “Knowledge in Formation”. Conjectures in
blue deal with Semantic Web.
Hinge Conjectures: In order to operate such a huge and complex semantic system we need of a few “hinge” Conjectures in grey
connecting the old Darwin Conjectures (in blue) to the new last 10 conjectures (in emerald) that enable us to “see” the Web as an
Ocean of Avatars, a more advanced vision than the Semantic Web.

22. The First 12 Conjectures Synopsis
The Web could be seen as a world of human in mind images; humans agree about their meaning
thru specific and appropriate use of words; this universe could be quantified; however
probabilistically; it also could be imagined like a huge Cyber Ocean where these nominative
creatures, bearing personal names, live; It also could be imagined like a huge Ocean where these
nominative creatures behave like wavelets enabling their detection and recognition by semantic
resonance via search engines; in fact a world of avatars as virtual creatures registering “literarily”
the avatars of our past, present and probable futures lives; these avatars are documented and
hosted like in conventional libraries but by pieces of information and knowledge disperse by
billions here and there; the patterns of this dispersion suggest the existence of a hidden
intelligence that could be unveiled; up to here we have presented a set of 10 Conjectures necessary
to operate with avatars. However conventional informatics works by de facto under a sort of Cyber
pre agreement: the DIKW Pyramid; from here we may state that formal knowledge tend to
structure by itself as a wood of “Semantic Trees” and that knowledge in formation tend to
structure also by itself as more primitive and disordered arboreal forms; knowledge in formation,
informal forms of knowledge and complex forms of information are the basic components of
Intelligence Reports managed as avatars;
Darwin Ontology Conjectures
a) A world of human “in mind images”: Human beings transmit their cognitive legacy thru
“in mind images” as “concepts” only “seen” thru our minds;
b) A world of “words”: In mind images identify specific pairs “language- culture” for instance
“American - English” and “International – Spanish” meaning that they can be explained
and understood thru the pair language – culture of their belonging;
c) World sizes: The total number of these in mind images, as Web space creatures, is
estimated at present from 12 to 20 million per pair language – culture;
d) A world of probabilistic nature: For each pair language – culture in mind images are
“unique” however with a “unicity” spectrum of probabilistic nature that is to say that all
them as well as their corresponding explanations may differ slightly from person to person
and even from situation to situation and from moment to moment;
e) The names of its creatures: For each pair language – culture in mind images are identified
by their “unique” names expressed as precise chains of words namely: “running”,
“meditate”, “son of a single mother”. “EU young people unemployment rate”, “Pope
Francis”, “Barack Obama”, etc.;
f) A world of semantic vibrations: Names are unique in probabilistic terms, “probabilistically
talking” for a determined place and time, for example the Web as_is at a given moment
associated to a sort of “Semantic Resonance”;
g) A world of avatars: These in mind images we nominate as “avatars” could be mentally
seen, perceived and/or represented thru text, visual images, sounds, and multimedia of

23. any type are Cyberspace “virtual creatures” defining our civilization at ANYTIME and
ANYWHERE;
h) Avatars library: Our civilization along time, have properly agreed and recorded besides
those agreements throughout books, essays, comments and very recently in semantic
documents as Web pages;
i) Retrieval of hidden intelligence: Avatars are either seen or looked like structured
following similar patterns to our way of thinking for example more and less important
more and less complex however always hierarchically and by affinity interrelated as
pertaining to a unique “The All”;
j) Knowledge DIKW: Hypothetical Conjecture: DIKW Pyramid. This parallel life paradox of
we, humans, and of our avatars looked like embedded within a common sense model
agreed and evolving along time represented by the hierarchical pyramid Data =>
Information => Knowledge => Wisdom refined and structured thru a growing intelligence;
k) Arboreal structures: Knowledge defined as the hierarchically triad Facts (Data) =>
Information => Skills and Talents, and as our evolutionary guide as well would structure
by itself as arboreal forms. Ideally as a wood of “Semantic Trees” of unique roots and
thematic ancestry;
l) Avatars unveiling and IR’s, IdeI’s: Avatars are “seen” by our minds with a diversity of
forms and ways proportional to their complexity and to the cultural differences of the
observers, humans, groups, and/or collectives (see Conjecture d)). This feature enables us
to unveil objectively and non-vitiated IR’s, “Intelligence Reports”, semantically depicting
as many facets as existent in the avatar at a given moment, something like for instance
Vision 1 of the “ism - 1”, Vision 2 of the “ism - 2”,…., Vision n of the “ism - n”, etc.;
m) K versus K’ worlds: General man-machine interaction could be imagined as a continuous
dialog and dynamic equilibrium between two sides: the Established Knowledge - Realm K
versus the People’s Knowledge – Realm K’;
n) K versus K’ Semantic interchange: Through the subtle interface between K and K’,
relatively to each side inflow and outflow only two kinds of semantic particles:
“Established Concepts” (from K to K’) and “People’s Concepts” (from K’ to K). These
particles are “separated” by communications/instances, operators from K and K’
respectively necessaries to make dialog meaningful;
o) Two types of Semantic Particles: Documents and messages, the elementary objects of
Realms K and K’ are only constituted by two kinds of semantic particles: “Common Words
and Expressions” and “Concepts”;
p) e-membranes and unveiling without perturbing: This digital dialog may also be imagined
like performed trough “e-membranes”, resembling bio membranes with endoderm,
mesoderm and ectoderm where inflow and outflow traffic of semantic particles and
instances could be “seen” without perturbing K and K` Realms actors. Darwin took its
name of this Conjecture: Distributed Agents to Retrieve the Web INtelligence as a Darwin
network of e-membranes;
q) Disciplines of Knowledge, WWD’s and WFF’s: Documents in K side tend to discriminate in
“disciplines” of the Established Human Knowledge. For each discipline there exist a

24. minority of documents that fit “as much as possible” to their “trees” being at the same
time literary and conceptual “Well Written” and a majority of document that doesn’t. The
first ones are considered “authorities”. WWD, Well Written Documents resemble WFF’s,
Well Formed Formulae of Formal Logic;
r) Subjects and Concepts: Subjects are those specific concepts associated to the nodes of
their respective discipline trees as the “semantic paths” that arrive to them from their
roots. Concepts “should be” the same for all pairs language - culture. For each node there
exists one and only one subject. Being the subjects known appear for each of them new
and somehow derived concepts that “belonging” with a strong specificity to it could be
defined as its “Associated Concepts”, namely those ones that “at large” define and precise
their respective themes;
s) Knowledge Authorities: For each subject there exist at a given moment with a high level
of probability, within universal and huge reservoirs like the Web, a “Set of Authorities”
dealing with it with a well defined authoritativeness;
t) Human Knowledge, Thesauruses and Derived Concepts: From “Sets of Authorities” we
may develop a sort of industrial process to extract their “Associated Concepts” sets
establishing then the following correspondence: for each subject we may find its
representative authorities set and from it we may build its Associated Concepts set. All
discipline trees of the “Human Knowledge” that within their nodes have their respective
authorities’ sets and their respective Associated Concepts sets constitute the “Web
Thesaurus”;
u) Thesauruses for K and K’: A similar Thesaurus could be defined and unveiled in the K’
Realm as the “People’s Thesaurus”. Similarly to Subjects K, Authorities K, Associated
Concepts K could be defined Subjects K’, Authorities K’ and Associated Concepts K’;
v) Semantic Web: Once K and K’ sides are known as_they_are, unveiled from retrievable
Web documents and messages, actors on each side are enabled to know as much as
possible of the other side. This event will accelerate the human learning process. K and K’
could be considered as fully mapped and this mapping may be continuous and perfected
along time.
=> Back

25. DARWIN in a nutshell
Darwin Methodology Briefing
By Juan Chamero, Principal Architect, from Barcelona as of 2015-01-13
Upon INTAG proprietary document: darwin_brief_PDF.rar
Darwin Brief (darwin_brief.pdf): a brief Darwin index to accede to:
 WHAT is Darwin (darwin_methodology.pdf): it is a methodology to “see more and better”
the Web and comparable data reservoirs thru 11 applications;
 HOW to “see” the Web from Darwin (Darwin_Web_EN.pdf): for experts;
 BIBLIOGRAPHY (Darwin_bibliography.pdf): about Darwin and its creators;
Conclusions: ¿Are we in the dawn of a new way of thinking?
And in its turn Darwin Methodology (darwin_methodology.pdf) opens in:
 A CARROUSEL (darwin_carrousel.pdf): imagery about a possible way to explore Darwin
meaning as a manifestation of a new way of thinking and a new vision of existent world
under the new technologies;
 A KNOWHOW sample (darwin_basicbuildup.pdf): something about HOW Darwin “see”
meaningful connected what appear in the Web disperse here and there and not
structured;
 Even though not conscientious of it we humans are by de facto and of a sudden
submerged in BIG DATA (darwin_BigData.pdf) scenarios that each time leave us less time
to think: ancestrally we passed from a “many” of hundreds and thousands of events and
instances to trillions and more and shrinking our meditations times from months, days and
hours to fractions of a second as well. Darwin moves with suitability in these scenarios.
 Complementary a brief explanation of the 11 Darwin Applications and of their respective
DARWIN ICONS (darwin_icons.pdf). Icons and avatars are a common place of our cyber
culture that has incorporated besides text and image the audible, the visible and shortly
the tactile.
=> Back

26. Darwin Brief
Juan Chamero, from Buenos Aires, Argentina as of January 1st 2015
Index
 Darwin Methodology (2 pages)
o Darwin Carousel (5 pages)
o Darwin Maps Buildup (3 pages)
o Darwin Big Data (3 pages)
o Darwin Icons Meanings (5)
 The Web as seen by Darwin Methodology (3 pages)
 Darwin Bibliography (1 page)
Recommended lecture order: if you are well acquainted with Semantics you may start reading
The Web as seen by Darwin Methodology. If you are not the order suggested is to read Darwin
Methodology, an introductory document that explains how to see the Web as semantic. This
document is complemented by three appendixes: Darwin Carousel, a document that tries to
explain that perhaps we are in the dawn of a new way of thinking; Darwin Maps Buildup, a
document that explains the basic knowhow to unveil non structured information and knowledge
out from the Web; and Darwin Big Data, a document explaining how Big Data have challenged us
and perhaps is somehow changing our way of thinking computationally.
We also recommend reading Darwin Icons Meanings document that briefly describes each one of
its actual 11 applications and finally Darwin Bibliography, an index of links.
=> Back

27. Darwin Methodology
Distributed Agents to Retrieve the Web Intelligence
By Juan Chamero Principal Architect of Darwin Methodology, as of January 6th
2015
We present Darwin, a methodology to “see more and better” huge reservoirs of data like the Web as if their
contents were semantically structured. It implies detection, retrieval, ordering and synthesis of all pieces of
information and knowledge about any subject disperse here and there within the reservoirs. The synthesis
may take the form of: (see below); see Darwin icons meanings;
o Thesauruses;
o Maps of Knowledge;
o Non intrusive e-membranes to communicate among different environments;
o OOC, Only One Click Semantic Search Engines;
o Encyclopedias;
o Non intrusive massive Surveys and Polls about any subject;
o Intelligence Reports about any subject;
o Avatars, AI creatures that represent and/or emulate primary powers and trends;
o Intelligent Web Portals;
o Big Data synthesis;
o Autonomous Artificial Communities;
Are we around the end of Conventional Thinking?
Behind Web Semantic: a global cultural discontinuity?
Apology from Legal Dictionary
This is an apology and a sample of recent digital history: At the end of our long journey that lasted 15 years
trying to unveil the Web we failed to document an enough comprehensive synthesis of the work performed
and its findings. Why? As a Zen master however specialized in Artificial Intelligence I continued with my
Western habit writing books and essays via “papers”, white and classified ones, trying to explain others the
whole history as a “linear” logic sequence, from prologues to epilogues thru abstracts, antecedents, of
course the textual cores, appendixes and bibliographies. The investigated theme, Web Semantics was
perhaps too big and vague and seen at distance it seems to be highly disruptive as well.

28. The Web explodes registering almost everything that happen in our world openly and free. Darwin enables
us the building of tools and methodologies to see the Web more and better at extreme detail resembling a
super ultra semantic telescope. However we have to pay a toll to use those tools and methodologies: to
enter de facto into Big Data scenarios embedded “of a sudden” in a world that enforce us to behave “real
time” without enough time to “think”. Now the Zen non linear way of thinking comes in my help.
Zen exploration?: Are we going to a “To be aware of everything” way of thinking?: One of the trivial things
we “discovered” by exploring the Web as our main source of information and knowledge is that ALL is
related to ALL and EVERYBODY to EVERYBODY being those everybody physical and juridical creatures and
avatars, where everything that occurs to them has sense. It’s is like making a census by interviewing people
as persons searching for how they consider something bad or good, we like or we do not like. From the
beginning, by dialoguing, questioning and why not answering, we may easily detect factors that were
initially ignored and that in order to be honest and precise should be taken into account. We continue
thinking how to face this new challenge where nothing is really environment but interactive part of a unique
and always changing ALL, but in the interim reporting our awareness state along our Web explorations. And
reporting not only the rare things we may found but also our agents’ findings under our guidance.
The bonus of being aware example: As an example Darwin process raw cognitive units named “textons”,
huge vectors of 10,000 documents and more per theme and talking about a cognitive universe of 1,000,000
themes we should – in theory- process 10,000,000,000 documents!. This is an a priori discouraging scenario,
isn’t? However the first textons exploration presented to the “eyes” of our agents rareness signs that enable
us to find two and three order zero shortcuts. To understand Darwin better we invite you to follow its
logbook.
Darwin Logbook
Darwin Carousel – A Technology Paradox
Why do we do what we did?
Carousel from Google images
Basic building knowhow
Web Thesauruses and trustable Intelligence Reports buildup
A Big Data Challenge
How to retrieve all concepts of a given language culture
Ways to make sense of Big Data, from Phys.org
=> Back

29. Darwin HKM Carousel
A technology paradox
Juan Chamero, as of January 5th
2015
Encyclopedias: Paradoxically wiithin the Digital Revolution, within The Information Society and very recently
within the Social Network conventional Encyclopedias are dying! Until recently the last Encyclopedias like
The Britannica announced its last 2010 printed edition version dealing with approximately 80,000 subjects,
by the way 10% of the available knowledge disperse in the Web. The last systemic index of the Human
Knowledge before these “conventional” was the Diderot Encyclopedia (1751 – 1772) edited in French.
The Diderot Encyclopedia
Wow! Knowledge is within our minds!
And not only knowledge but all type of information and even wisdom! Being deep in our minds we only
acquaint of these substances indirectly thru registers, documents, works and gestures! So if actually the
Web hosts 40,000,000,000 documents we may say that we may “have at hand” 40,000,000,000 documented
expressions of those ideas! The first time we humans have “at hand” a global and meaningful sample of all
type of ideas from genialities to stupidities, online, and almost real time besides!

30. The power of gestures: if you query Google Images by “demand for explanation” it will render you hundreds
of versions of this image. Do we need some extra explanation to understand this universal baby gesture?
And we also have at hand billions of images about the Web_as_is “everything”!
Demand for Explanation
How many types of “in mind” ideas do we have? At least three types: pieces of information, pieces of
knowledge, and needs. Pieces of information are a continuous need to guide our lives; pieces of knowledge
are a crucial need to evolve positively along our lives; needs in general to live and for a living. We acquire
knowledge by studying, information by questioning; general needs are acts that become “experience”.
From dreamstime.com
In order to study [1] you need “libraries”, “Thesauruses” and “Encyclopedias”; In order to have an efficient
questioning [2] you need “semantic search engines”, and in order to optimize your experience [3] you need
to collegiate with similar people. Darwin enables the Web to be used as a study home, become semantic
conventional search engines and facilitate open and free organization of people with similar areas of
interests.

31. A little about some necessary “bored” things:
First HKM, Human Knowledge Map, about ICT (2002): we created the first Web Thesaurus about
Information Computing and Telecommunications. Initially we started joining the last ACM, Association of
Computing Machinery (2001) semantic index with the IFIP UNESCO Informatics standardization for the RW,
Rest of the World: an ICT Thesaurus of 2,300 subjects and 54,000 concepts. We see below its upper 5
hierarchical levels.
Are arboreal structures natural forms of our thinking? It seems that yes, they are. And going a little farther
what about our abstract thinking? It also seems that we are also used to. In the figure below at left asking
Google by “fractal tree” we get a sample image of primitive arboreal abstract trees. At right asking Google
Images by phylogenetic and then by Life Trees we may get a full sample of arboreal trees (real bio trees).
Abstract trees Bio trees
Google Homage to Ramon & Cajal Nobel Price of Medicine, (1906), neuroscientist, perhaps the father of
modern neuroscience, was considered a disastrous student with an extreme revolutionary antiauthoritarian
attitude and even for his father a “little short” of brain. One of his metaphors was: cortical pyramidal cells
may become more elaborate with time, as a tree grows and extends its branches. I believe that this

32. metaphor suggests us that we may go far walking with small steps but always expanding our mind
awareness by exploring the unknown. Ramon & Cajal was, like the Great Leonardo, a brilliant draftsman: he
began drawing more and more complex neural networks and learning from them at exponential pace.
The beginning should be neat and easy for all: semantic seeds. As explained above Ramón & Cajal started
his adventure “to see more and better” the brain trying to unveil and draft on paper a single neuron. We as
Darwin Project were experimenting with different types of seeds and strategies for growing. Our option for
The Art map building was the last downright schema.

33. Of course we do not imagined the seed as having 7,570 nodes as an “adult tree” but as a tiny skeleton of a
root initially opening in up to seven clusters as seen in the image below namely: performing arts, visual arts,
culinary arts, literature, arts history, physical arts, and arts infrastructure.
The Art Thesaurus: the figure below depicts one of the visions of The Art Thesaurus resembling a “map” to
facilitate the human comprehension and exploring the existing knowledge as is in the Web at a given (any)
moment. It could also be seen as the Upper Levels of an Art Tree index.
Another technological paradox: we have seen Ramon & Cajal paradox, the revolutionary and/or disruptive
innovations as a sort of unsought premium bonus of long scientific exploration efforts. Another one is the
Global Warming phenomenon ”unveiled” by Wallace Smith Broecker, geophysicist and climate authority as
one “byproduct” of his research along decades about the CO2 concentration in our atmosphere. And from
this discovery proliferate hundreds of derived and interrelated researches, for instance the creation of
“Artificial Trees” (see below in thebreakthrough.org).
Artificial Trees, from thebreakthrough.org
=> Back

34. Darwin Methodology
HKM, Human Knowledge Map basic building knowhow
Juan Chamero, as of January 5th
2015
Darwin HKM buildup could be logically imagined along a sequence of four mega steps, namely: a) MS’s data
discovery; b) HKM Logical Skeleton buildup; c) HKM unstructured data sample; d) HKM structured.
Step 1: By MS’s, Major Subjects data discovery we mean scouting the Web to retrieve all “modal names” of
the knowledge branch under study, only their names not their conceptual meaning not their relative
ordering within the Logical Tree of the knowledge branch. In our example we mean discovering the 7,570
names of The Art MS’s, Major Subjects.
Step 2: By HKM Logical Skeleton buildup we mean to unveil from the Web the semantic ordering of modal
names becoming “nodes names” of the Knowledge Tree finding the unique correspondence between a tree
node and its modal name: 7,570 unique nodes  7,570 unique modal names for our example.
Step 3: By HKM unstructured data sample we mean a huge conceptual but still unstructured data sample
of the branch of knowledge under study. This Big Data scenario is not easy to imagine: For each node we
need a meaningful sample (for instance 10,000 Web Pages) that enables us to discriminate how structured,
noisy, disperse, misleading and diluted from its semantic point of view a given MS is.
Step 4: By HKM structured we mean a synthesis of the above mentioned data sample: for each node we
should synthesize its “semantic fingerprint”, a set or sets of specific concepts that statistically and ideally
are used in the Web_as_is at a given moment and for a given pair language culture to describe the subject
inspected.
Step 3 Performing: Let’s suppose that somehow we have already successfully performed steps 1 and 2
starting step 3. Using the names list obtained in Step 1 we proceed to buildup textons, one for each name,
as for our example 7,570 textons of about 10,000 Web Pages each. Once the textons are stripped off from
code leaving only meaningful text and images we should inspect their content document per document
retrieving their potential concepts, in the average 50 per document totaling about 500,000 suspected
potential concepts per subject!
Note 01: take into account that a whole HKM have about 800,000 MS’s, Major Subjects.
Step 4 performing: we proceed now to synthesize that huge mass of 500,000 potential concepts per subject
by finding the “modal”, semantically the best, 50 in the average.
Note 02: The sample expanding to around 500,000 suspected potential concepts was designed in order to
study how structured, noisy, disperse, misleading and diluted from its semantic point of view a given MS is.

35. We have now our first version of a HKM, in our example for The Art: 7,570 nodes, going from “root” to
“leaves” along 13 levels and having in the average 50 specific concepts per major subject/node, rounding
about 378,550 concepts plus the skeleton 7,570 subjects that are in fact the leading concepts of the
discipline under study.
Steps 1 and 2 performing: these steps could be seen as a coupled semantic convolution of names and
hierarchies, a sort of e-learning process of rapid convergence that started with a “semantic seed” for each
branch of the HK. In an extreme we may also explore the Web without the aid of seeds starting from zero
knowledge. Along our 15 years of work, four prototypes and dozens of semantic seeds buildup for third
parties, we have thoroughly checked that any Web expert may identify the “authoritative” core for any
branch of the HK in no more than one day effort.
Specifically The Art authoritative core of about 200 authorities was identified by a human. Each of them
semantically covered more than 50% of the suspected MS’s and its 2% top covered more than 95% of the
suspected MS’s. Backed up by this departure knowledge we initiated a sort of “anthropic algorithm”: a
human expert in multi agents programming, learning as much as possible by himself and guiding and/or
adjusting agents work, a sort of a man machine cooperative gathering selecting pieces of information and
knowledge jumping from link to link within the base cluster and from it to semantic neighborhood clusters,
expanding the initial base.
How to check that something goes wrong along the exploration: This anthropic process evolves too fast
suggesting us that probably logic attracts logic tending to empower it and to weaken the illogic. We also
have a mechanism of easily checking what’s poorly structured from a semantic point of view: the ontologies.
Effectively any ontology enables us to check something that already exists and to answer questions such as:
was it created or not under ontology conjectures? Notwithstanding ontologisms aid us nothing about the
“art” of creation of things. For instance it tells nothing about how to unveil – or in an extreme to invent- a
logical skeleton of art but on the contrary it warns us if something goes wrong.
HKM buildup Schema
The figure above illustrates a core part of the intertwined process of 4 steps. From 1 to 4 we depict at left
the four big steps looping embedded. In the middle we depict a KT, Knowledge Tree of 15 nodes from root
to leaves. A HKM Human Knowledge Map resembles a logical forest of 200 trees, one for branch of
knowledge and each tree having in the average 4,000 nodes (Major Subjects) totaling a sort of World
Encyclopedia of 800,000 Major Subjects for a given pair language culture. At right we show a huge matrix
used to check whether or not semantic hierarchies ideally corresponds to logical trees: nodes 1 and 2 derive
from unique ancestor 0 (root), nodes 3, 4 and 5 derive from unique ancestor 1,……, and so on and so forth.

36. Now you have to imagine that “within” any node is hosted metadata and sets of concepts and images
specifically related to its subject. So the mass of concepts of a given branch of knowledge, usually more than
95%, is hosted in the nodes! The 5% left corresponds to the names of the MS’s (main subjects, main themes
and topics of the discipline under study).
At right we depict the MS’s versus itself, nodes versus nodes. If these MS’s are structured like a Logical Tree
the matrix would be practically empty. Its unique ancestry nature enforces the “x” as shown. However in the
real Web all type of abnormalities proliferate like the ones in yellow. This is one of the hardest Darwin tasks
HAZ, Hierarchy Abnormalities Zoning.
=> Back

37. Some Darwin Challenges
A Big Data Challenge as well
Juan Chamero. as of January 5th
2015
Challenge I: Darwin Concepts Unveiling from Textons
Darwin retrieves suspected potential concepts out of textons, documents however semantically “noisy”.
Talking of a 10,000 Web Pages textons sample we mean extracting their 10,000 corresponding semantic
profiles (Darwin “fingerprints”).
Texton: a large enough string of meaningful documents supposedly dealing with the same MS, Major
Subject, for instance “modern theatre” within “The Art” branch of knowledge. The location within the string
for instance from its beginning to its end and from left to right is directly related to its semantic significance.
Textons usually have from 1,000 to 10,000 documents (Web Pages  URL’s).
Note 01: this is a strong supposition that must be checked along the Darwin concepts unveiling process. The “raw data” is
provided by conventional search engines like Google that “rank” URL’s as per their own criteria. This primary ordering
that is taken into account by Darwin is continuously checked and enriched because it performs an exhaustive analysis
about how all textons deal with subjects and rank conceptually between them!. In common words Darwin detect that
some sources (URL’s) may provide more and better information to us than allegedly supposed by its Google rank that is
to say they behave as specialized ones!
Textons corpuses must be stripped off from “no content” information, like all type of coding before their
processing. Textons are the raw data of Knowledge Maps, at large a semantic sample of it however not yet
structured: hierarchically “flat”. Darwin as a process following its own Ontology Conjectures unveils in its
turn the potential concepts hosted here and there within textons as a function of their intrinsic statistical
“rareness”
Textons unveiling
Texton [pair LC; SMS; n; W]: pair Language Culture, Suspected Main Subject, amount of documents, amount
of words], for instance
Tx231 *EN USA; “modern theatre”; 12,324; 15,355,409+;
Read as: Texton 231 for the pair EN USA (English – American), dealing with “modern theatre” having a string
of 12,324 Web Pages corpuses and 15,355,409 words
The key is to detect potential concepts or “cepts” as a function of their rareness along the following steps:

38. 1. Jargon confirmation and coherence tests performed on it, f.i.: EN - USA Art Jargon of ~4,000 terms;
2. SJD, Semantic Jargon Distribution: Statistical Jargon words’ presence within textons;
3. SJD rareness;
4. First potential single word concepts and/or “cepts” (c’s) List;
5. n-ads potential c’s Frequencies Database creation;
6. 1-ad presence and from 2-ad to 6-ad potential c’s presence distribution within texton: f.i.: the four
words {the backwoodsman of Kentucky} in allusion to Abraham Lincoln generates from 1-ad to a
4-ad: [the; the backwoodsman; the backwoodsman of; the backwoodsman of Kentucky];
7. HUMAN defines, adjust rareness thresholds;
8. Lists of potential c’s with their justification parameters;
9. Semantic checking of potential c’s “names”: searching their “modal names”;
10. Semantic checking “ex-post” of MS versus the checked potential c’s: do these c’s represent
semantically the initially supposed MS?;
Once finished this process step for a given Major Branch of the Human Knowledge, for instance “The Art”,
we may say that we have unveiled it completely but still unstructured, flat, as a huge logical tree of only one
level! Talking about The Art thesaurus of 7,570 nodes, each one corresponding to a single Major Subject of
the Art discriminated by about 400,000 c’s. Once structured, the last global Darwin step: these 400,000 c’s
show as structured in 13 levels!
Challenge II: Semantic Synthesis via Textons Processing
Given a cluster of documents supposedly dealing with the same subject unveil from it the best fit to its
specific set of concepts (ideally its “subject semantic fingerprint”). This is one of the strongest Darwin
conjectures that globally stand for: humans tend to register their ideas statistically following secular rules
(see Darwin Ontology) generating by de facto “WWD, Well Written Documents”. So Web pages dealing
with the same subject spin around these ideals like semantic vortexes: being the internal the best
documented meanwhile the externs the worst.

39. We humans are specially suited to unveil those specific concepts (see Darwin history) as a function of how
good a document is concerning the ideal: from our experiences with hundreds of advanced students of
Informatics and Systems Engineering a human in a couple of hours could be trained to detect specific
concepts within documents chosen at random about any subject. This “methodological talent” could also be
easily transferred to an agent (see How Darwin unveils potential specific concepts out of a document).
For each Th Semantic Threshold Level of “rareness”, in the figure above Th03, Darwin algorithms unveils a
specific set of 46 potential/suspected concepts supposedly pointing to the MS, Major Subject, of the texton
analyzed. If the texton have 10,000 text corpuses pertaining to their corresponding 10,000 Web pages we
would unveil for instance 500,000 potential concepts names for an average of 50. In fact a Big Data scenario
where in the average for each MS and for each Threshold we should define the “best fit” to the “specific
concepts set” used statistically worldwide for a given MS and for a given pair “language culture”.
Going a little deep on the details: from these 500,000 [URL, concepts] pairs, only for a given MS, we must
find the best fit to a sort of “modal” “specific concepts set” of it. To perform this task we may need the
following structured data: [MS, URL, {code, name}, frequency] where MS stands for Major Subject, URL by
the Web address, {code, name} set of pairs (code, potential specific concept name),and the frequency of the
potential specific concepts appearance within the page.
Given a MS of a branch of the HK the challenge is to unveil out of the Web the best fit for the “specific set”
of concepts semantically related to it, namely the set of concepts specifically used – probabilistically - in
WWD, Well Written Documents. In numbers for a branch of knowledge, for instance “The Art” (without
considering frequency):
4,000,000,000 names 
[8,000 subject names per Branch of the HK
x 10,000 Web Pages per subject name within each branch
x 50 potential specific concepts per Web Page ]
Note 02: This Big Data briefing accounts to have an idea of the order of magnitude of the computing needs. This will
provide us the upper threshold level, almost a “brute force” reductionist approach. However as it occurs in most Big Data
processes we human learn fast. In the examples above we may pass from a first trial of 4,000,000,000 names processing
for a single subject of a HK branch to no more of a few million as long as we go from one MS to another, for instance
from 4,000,000,000 to less than 4,000,000 with an average of 40,000,000. What really happens is that from the designed
10,000 Web Pages capture per MS we may “discover” among those 10,000 URL’s a small sample of a few hundred of
“authoritative” URL’s concerning the MS under analysis.
What’s then missing?
Only two things: iii) How do we unveils all the subject names of a given HK; iv) how to structure those
subject names along a unique logical tree.
=> Back

40. Darwin Methodology Applications
By Juan Chamero Principal Architect of Darwin Methodology, as of January 11th
2015
It is a dreamstime.com free use image. Search thru Google Images via query [teacher
clip dino] as open search.
Thesaurus is a sort of reference book of concepts, and in Darwin Ontology of “in mind ideas”
represented by one or more words of a given pair language culture usually with synonyms and
sometimes with antonyms. Thesauruses may suggest the best suited synonym for a given moment
(present) named as the “modal name” of the referenced “in mind idea”. The Web imagery used to
associate thesauruses with dinosaurs.
It is a vision of the upper levels of a HKM, Human Knowledge Map of The Art. See a
sample extraction of it sheets 1, 2 and 3, (Theatre Mapping) as of September 2008 from Spain.
HKM stands for mapping the whole knowledge or a branch of it, semantically, by meaning,
resembling Logical Inverted Trees from their “roots” down to their derived “nodes” thru a unique
ancestry. Its content and the “intelligence” behind it is detected and unveiled from the Web by
Darwin Methodology under the guide of Darwin Ontology, a set of “strong” semantic conjectures
about how we, humans, document our “in mind” ideas.
Non intrusive e-membranes like a sort of intelligent interface among two or more
autonomous applications. Each one provides some type of service to the others under a non
intrusive operation scenario. See BBC Science as of July 2003.
Non intrusive and non perturbing e-membranes are necessary interfaces to communicate two
different “words” that enable both to continue working autonomously, within their own hierarchy
and rules and without perturbing each other. The e-membrane designers must have into account
that the communicated systems may not only differ in objectives, times, rhythms, but also in their
semantic. In the example published by the BBC of London the figure refers to an e-membrane
between a conventional procurement SAP system (for an international oil corporation) and a

41. “pilot” e-procurement system working in parallel with the conventional one. The purpose of the e-
membrane was to learn as much as possible in the less time about real e-procurement instances.
SSSE, Super Semantic Search Engines, Semantic Direct Search Engines, also YGWYN – IOOC
Search Engines, You Get What You Need In only One Click Search Engines. See also “Súper
Buscadores Semánticos (i) y (II)”.
Initially the main purpose of Darwin was the creation of a Semantic Search Engine that enable
users to find in the Web the best information about something they need in terms of information
and/or knowledge whether possible in only one click. The icon for this Darwin application was
selected from “How Darwin unveils concepts”, see below.
Conventional Search Engines like Google are like a non semantic library where all existent Web
documents are classified by their words. Google tells you nothing about the meaning of Web
documents. Darwin Methodology unveil documents meaning at a given moment by structuring
them semantically and building the Web Thesaurus, resembling a World Wide Library, depicted in
the figure as a hypercube of as many “floors” as semantic levels the Human Knowledge has.
Encyclopedias building should be one of the first semantic areas of necessary Web
applications but unfortunately its development is almost frozen. There are exceptions like
Wikipedia, and projects about specific thematic subjects like Europeana and Wolfram Alpha. (See
Videos Google: World in hand).
By first time we, humans, have at hand all the records of our living, our past and now our present
practically at real time! Encyclopedically talking we have at hand (of course with the appropriate
technology) all the pieces of information and knowledge about anything. With applications like
knowledge mapping (the second of our list) we may locate “directly” the best authoritative
sources practically about anything. The only remaining task (by now the human touch of direct

42. knowledge retrieval) is to “synthesize” and “edit” the content of those sources meaningfully and
automatically, namely via a conventional computing process. Darwin Methodology is pursuing this
goal. In the interim Darwin may deliver to humans all the content they need specially suited for
editing.
Surveys and Polls: This icon corresponds to one of the classic applications: stats focused
in Surveys and Polls. See all types of visualizations in Google Images as: [surveys & polls results].
See image as applied to Health Science Strategies.
Darwin faces it singularly because having at hand information about anything even without
needing being aware of addressed people, entities and avatars. We may obtain meaningful
answers from querying to all types of just “observing” non intrusive procedures. We may also have
at hand “massive” information at any time and intervals of time about any specific aspect of the
research and the possibility of filtering observations thru causal cultural behavior models as well.
Intelligence Reports: This icon represents information and knowledge unveiling and we
used it as an avatar of “intelligence”. Darwin stands for Distributed Agents to Retrieve the Web
Intelligence supposedly disperse and hidden.
Intelligence: take a look at Intelligence in Google Images and appreciate the dominant imagery we
humans have about this subtle concept: light, luminosity, tending to be blue and expanding. In the
data evolution from chaos to information to knowledge to wisdom the thing or “thing” that
enforces evolution from chaos to wisdom is the intelligence. Intelligence Reports are documents
that enable us to “infer” results and consequences, trivial and sophisticated ones, explicit or
hidden out of a structured and as much detail as needed description of something existing.
Darwin enables us to create trustable Intelligence reports about ANYTHING as long as we have at
hand enough trustable information and knowledge about that ANYTHING. As in the case of Stats
Surveys and Polls, these reports could be performed at non intrusive mode and without disturbing
the Web.
I is an icon avatar from the film Avatar. Avatars are creatures and or entities that
represent existing entities, persons, beliefs, truths, etc. See avatares (Spanish) Pope Francis demo,
avatar(computing).

43. Avatar is an abstract entity and/or a digital or Web creature that intents to represent: a given
entity, person physical or juridical, the best way scientifically taking into account all possible
meaning axes of its “character” and facts even those considered good or bad, sayings of all types
from beliefs to conspiracies, researches performed on it for instance: the Pope Francis or Barack
Obama, or the Organized Crime in the World, etc.
I-Webs, Intelligent Web Portals: icon to represent how Web connections evolve along
time for the pair information people. See Explaining the Semantic Web and Making sense of the
semantic web. Be cautious! Most of these projections that intent to see the Web extrapolated to
year 2020 should be considered possible trends, among many, of a phenomenon that evolves
exponentially so fast and unpredictable that may mislead seriously our forecasts.
I-Web is a Website (or Web Portal) intelligently designed taking into account the available
technologies and the available resources of the Website owners and administrators. We may
found today excellent Web 1.0 Websites and from poor to awful Web 3.0 Websites. For instance
there are thousands of “top ranked” Web 3.0 Websites with their own proprietary data still
semantically unstructured. In any buildup the beginning is the beginning and the beginning in all
Web projects should always be its “semantics”, namely the “semantization” of its data and
vocabulary.
The Web creatures live in different habitats and under different technologies concerning their
abilities to communicate with others meanwhile performing their daily tasks in order to survive
either tagged as Web 1.0, Web 2.0, Web 3.0 and now very recently as Web 4.0. Concerning Web
development we have as options a paraphernalia of software panaceas and tools that are usually
applied to Top Websites and Portals and that have strong prerequisites to work successfully such
as Distributed Search, Cloud Services, Mobile Interfaces, Social Networks interaction, Privacy
Protection, Top Down and Bottom up design, Big Data Apps. Implementing advanced applications
without satisfying those prerequisites is suicidal.
Notwithstanding we may transform any Website in an I-Website without trying to become it Web
3.0 or Web 4.0. First of all as commented above we must semantize as much as possible data,
vocabulary, and naming. Then updating and or replacing of programming platform, languages,
reviewing databases structures having a horizon of planning of not less than a decade.
Big Data Synthesis:. Semantic Web needs of Big Data; it’s intrinsic to its nature. Its
market is enormous and growing at a pace of 10 percent a year without taking into consideration
yet video and audio content. From de facto Darwin works within Big Data scenarios and have an
extensive experience on it with proprietary procedures and algorithms. The image icon has been

44. selected from one of the typical and oldest Big Data applications. See original image of this
impacting Big Data application at CERN Server, Switzerland (LHC Large Hadron Collider).
As Professor Mark Whitehorn says “Big Data may be misunderstood and overhyped - but the
promise of data growth enabling a goldmine of insight is compelling. Professor Mark Whitehorn,
the eminent data scientist, author and occasional Register columnist, explains what big data is and
why it is important. And adds: “Data is not large and it is not small It does not live and it does not
die It does not offer truth and neither does it lie.”
In our humble opinion BD always existed. We do not believe that it is a new data dimension but
something that at a given moment of our knowledge presents as rare, too big and complex. Let’s
clarify within our Darwin Methodology: 40 years ago matrix processing was bound to a volume of
data 100x100, something that holds in an Excel sheet of 100 columns by 100 rows. Why? Because
rounding errors propagation. Imagine now volumes of data generated by some social networks
about the order of 1,000,000x100,000, for example applied to a behavior study of 1,000,000
persons related to their opinions about 100,000 themes! In order of not over dimension the
resources and tools to face this BD challenges we need fundamentally experience and common
sense (see our document about Big Data Challenge).
: Autonomous Artificial Communities: as of today is easy and not too expensive to create
this type of communities. They could be a virtual and idealized emulation of a real one to be
tested its evolution (see artificial islands in Lonely Planet and Laulasi Islands as per Wikipedia).
These communities could be populated by persons, avatars, agents and a combination of all them.
Searching in Google by [artificial communities] as open search you may find Synthetic Microbial
Communities, Google AI Communities, Artificial Reefs Communities, Planned Communities,
Artificial Foraging Ant Communities, Artificial Plant Communities, Artificial e-Learning
Communities, Artificial Fresh Water Protozoan Communities, etc.
=> Back

45. The Web as “seen” by Darwin Methodology
By Juan Chamero, from Buenos Aires, as of 5
th
of November 2014
The Word of People
Humans have millions of ideas in their brains
Hidden and elusive except by proper use of language
Figures below illustrate very simplified how to build via agents a HKM, Human Knowledge Map, from a
“semantic seed”. Darwin states that in the Web is “always” hosted the sum of the knowledge even though
unstructured and disperse in approximately 35,000 millions of Web pages as of today. Darwin Ontology
states that we humans keep (save) in our brains a finite universe of “in mind” ideas estimated in 12 to 20
million per pair “language - culture”.
This cognitive asset has being coined thru millions of years and documented since the writing discovery.
However this asset looks like hidden and elusive. The only way we have at hand to retrieve those ideas is
thru the “correct use” of language within the right context, for instance the word Rigoletto point “correctly”
to the “Opera Rigoletto from Giuseppe Verdi within “Performing Arts” context and within Opera context
staying semantically differentiated from hundreds of acceptations and/or frequent uses of the same word as
for example a commercial brand or a restaurant.
Darwin Ontology was conceived to retrieve information and intelligence out from big data reservoirs
somehow semantically structured (probabilistically). However the Web content is only indexed by “words”,
not for ideas or concepts, being considered “semantically unstructured”. In order to “see” its content as if it
were semantically structured Darwin query it as if it is!. It uses as a valid stratagem the following set of
suppositions:
1. ALL: Web Completeness: The All is present in the Web notwithstanding disperse and hidden;
2. STRUCTURE: Logical and Probabilistic Completeness: The All is “probabilistically structured” under
logic algebraic forms;
3. CREATURES: Web creatures: from this structure arise dominant ideas (in mind ideas) humans use
to communicate between them;
4. NAMING: Modal names: dominant ideas have specific names, “unique” and dominant for each pair
language culture;
5. DOCUMENT: “The Word of People”: all Web documents are expressed around these ideas just by
using their specific names, their synonyms and/or their distortions;
6. TREE: “The Word of People” structure: dominant ideas are hierarchically structured tending to
evolve and conform as inverted logical trees;
7. FUZZYNESS: the nature of this structure is probabilistic and also its math logic;
8. EVOLUTION: This structure evolves: it evolves fast along time from seeds and/or graphs of words
and concepts pertaining to diverse disciplines. New disciplines are continuously created and some
others disappear. New branches and new concepts are cognitively detected and assimilated;
9. ANTHROPIC: Content and Structure could be retrieved: even being the Web space open,
practically unbounded, and continuous could be precisely mapped as HKM, Human Knowledge