Re: What is a Knowledge Graph? CORRECTION

Hi Paola,

See below.

On 7/24/2019 8:38 AM, Paola Di Maio wrote:
> One further note on the Knowledge Graph discussion
>
> The reliance on KG (both as a word/naming convention, as as a 
> mechanism for KR)
> is a concern, and somewhat can be cause of awful distortions - which 
> will impact perception and decision making
>
> The literature analysis by Mike Bergman is very valuable in that it helps
> us to understand what happened, how KG evolved
> http://www.mkbergman.com/2244/a-common-sense-view-of-knowledge-graphs/
>
> Mike, can you please specify which knowledge base/endpoint and what 
> software
> was used to generate the Figures 1 and 2 - could not find that info in 
> the post
> would like to replicate /tweak your citation diagrams

The data source for the figures is explained in Note 4 in the article. 
The graphs were produced in the calc application of LibreOffice (the 
Excel analog). I have attached the original spreadsheet in xls and ods 
(LO) formats.

Thanks, Mike

>
> I find this thesis and some of the conclusions, important:
> /pdfs.semanticscholar.org/d768/76495f20493243bb862fce467534226c8bd5.pdf?_ga=2.9759605.1126947389.1563945860-1966063881.1561180249 
>
>
> QUOTE
>
> e believe that these developments will continue to shift the attention 
> of industry and researchfrom the document-centric information 
> processing towards a facts or KG-based perspective inwhich information 
> will no longer be a collection of natural language text (documents) – 
> butinstead be handled at the level of (single or connected) facts. In 
> the long-term perspective, how-ever, when natural language generation 
> from such fact knowledge bases will work sufficientlywell, the users 
> will no longer interact directly with neither documents nor facts, but 
> only askquestions that an advanced search-engine interface will 
> answer, while the complexity of KGgeneration, information processing, 
> reasoning, and question answering will be hidden.
> UNQUOTE
>
> Namely the limitations of KG
> - cannot help to represent the truth/fact checking
> -  human understanding and decision making will be based on machine 
> based truth
> assertions (representationS) that humans cannot easily check/understand
> But fact checking cannot be fully automated!!
>
> In relation to AI, and SW, separating the human representation from 
> the machine representation (KG)
> may prevent not only fact checking but also error correction. arghhhh
>
> I hope that future work in KG  tackles these gaps
>
>
> PDM
>
>
>
>
>
>
>
> On Tue, Jul 2, 2019 at 10:43 PM ProjectParadigm-ICT-Program 
> <metadataportals@yahoo.com <mailto:metadataportals@yahoo.com>> wrote:
>
>     Mike and Hans,
>
>     Knowledge is much more than extracting structure from facts and
>     data. If I just recall that the collection of facts is subject to
>     the uncertainty principle, any structure deduced cannot be
>     complete, and the application of free will, and/or axiom of choice
>     create a dichotomy, knowledge is much more.
>
>     We are limited by our sensory apparatus, our hard wiring in our
>     human brain, including the shortcuts made when processing visual
>     data, and the limitations of natural language.
>
>     I agree that knowledge reasoning should be fairly straightforward,
>     but making the jump from KR to knowledge itself implies we come up
>     with some consistent many worlds modeling scheme in which the
>     virtual, mathematical and (many interpretations of) the physical
>     world coexist, reconciling incompleteness, uncertainty principle,
>     sensory limitations and application of free will and choice.
>
>     A convergence of efforts by string theorists, researchers in human
>     brain cognitive and biological structure fields, theoretical
>     physicists and mathematicians working on finite groups, category
>     theory, algebraic topology and logical structures for consistent
>     super theories, and an odd mix of linguists and philosophers
>     (including Buddhists) is doing just that.
>
>     But they are far from a consensus.
>
>     The point I am trying to make is that KR is more than semantics
>     and ontologies and knowledge graphs, graphs, category theory
>     diagrams and Feynmann diagrams and any other visualization tools
>     we use.
>
>     The implicate order David Bohm theoreticized underlying quantum
>     reality and the reality of our physical world, cannot be captured
>     by some mix of formal logic, semantic structures, ontologies or
>     computable frameworks.
>
>     And we we want someday A(G)I to be able to grasp human knowledge
>     in general, we must create a growth path towards formal structures
>     which have meta-layers above (knowledge) graphs, formal logic and
>     ontologies.
>
>     Mathematically speaking, using formal logic, ontologies and
>     generalized graphs is necessary but insufficient for this general
>     formal structure.
>
>     Milton Ponson
>     GSM: +297 747 8280
>     PO Box 1154, Oranjestad
>     Aruba, Dutch Caribbean
>     Project Paradigm: Bringing the ICT tools for sustainable
>     development to all stakeholders worldwide through collaborative
>     research on applied mathematics, advanced modeling, software and
>     standards development
>
>
>     On Tuesday, July 2, 2019, 7:38:19 AM ADT,
>     hans.teijgeler@quicknet.nl <mailto:hans.teijgeler@quicknet.nl>
>     <hans.teijgeler@quicknet.nl <mailto:hans.teijgeler@quicknet.nl>>
>     wrote:
>
>
>     Hi Mike,
>
>     What we collect are facts, not knowledge. This fact collection is
>     to be done during the entire existence of a process plant.
>
>     Once you have enough facts you might start extracting knowledge
>     from them, for example which kind of pump seal is best in a given
>     service, or what to do to optimize energy usage.
>
>     This derivation may take place by reasoning, statistical analysis,
>     etc.
>
>     ISO 15926 deals with facts by excluding modalities by adopting On
>     the Plurality of Worlds
>     <http://15926.org/topics/possible-worlds/Lewis-David-(1986)-On-the-Plurality-of-Worlds.pdf>of
>     David K. Lewis <https://nl.wikipedia.org/wiki/David_Kellogg_Lewis>
>     as summarized in http://15926.org/topics/possible-worlds/ .
>
>     This allows for modeling designed objects in a separate possible
>     world in the same manner as in the real world.
>
>     Regards, Hans
>
>     _____________________________________________
>
>     *From:*Mike Bergman <mike@mkbergman.com <mailto:mike@mkbergman.com>>
>     *Sent:* dinsdag 2 juli 2019 09:49
>     *To:* hans.teijgeler@quicknet.nl
>     <mailto:hans.teijgeler@quicknet.nl>; 'Patrick J Hayes'
>     <phayes@ihmc.us <mailto:phayes@ihmc.us>>;
>     'ProjectParadigm-ICT-Program' <metadataportals@yahoo.com
>     <mailto:metadataportals@yahoo.com>>
>     *Cc:* 'Dave Raggett' <dsr@w3.org <mailto:dsr@w3.org>>; 'Paola Di
>     Maio' <paoladimaio10@gmail.com <mailto:paoladimaio10@gmail.com>>;
>     'Amirouche Boubekki' <amirouche.boubekki@gmail.com
>     <mailto:amirouche.boubekki@gmail.com>>; 'Chris Harding'
>     <chris@lacibus.net <mailto:chris@lacibus.net>>; 'xyzscy'
>     <1047571207@qq.com <mailto:1047571207@qq.com>>; 'semantic-web'
>     <semantic-web@w3.org <mailto:semantic-web@w3.org>>
>     *Subject:* Re: What is a Knowledge Graph? CORRECTION
>
>     Hi All,
>
>     My take on the question:
>
>     http://www.mkbergman.com/2244/a-common-sense-view-of-knowledge-graphs/
>
>     Mike
>
>     On 6/25/2019 11:40 PM, hans.teijgeler@quicknet.nl
>     <mailto:hans.teijgeler@quicknet.nl> wrote:
>
>         Hi Pat,
>
>         +1 , that’s why we (the process industries) have an upper
>         ontology, defined in ISO 15926-2
>         <http://15926.org/topics/data-model/index.htm>, with 218
>         entity types and the reference data library of ISO 15926-4
>         <http://15926.org/topics/reference-data/index.htm> with 39,000
>         classes.
>
>         Application data are mapped to templates (212 small models,
>         each using some of those 218 entity types), in RDF, validated
>         with SHACL, and stored in a triple store.
>
>         Although this doesn’t cover the entire universe, it does cover
>         the technical and activity life-cycle information of a process
>         plant (oil, chemical, food, etc), integrated from cradle to grave.
>
>         Regards, Hans
>
>         __________________________________________
>
>         *From:*Patrick J Hayes <phayes@ihmc.us> <mailto:phayes@ihmc.us>
>         *Sent:* dinsdag 25 juni 2019 19:22
>         *To:* ProjectParadigm-ICT-Program <metadataportals@yahoo.com>
>         <mailto:metadataportals@yahoo.com>
>         *Cc:* Dave Raggett <dsr@w3.org> <mailto:dsr@w3.org>; Paola Di
>         Maio <paoladimaio10@gmail.com>
>         <mailto:paoladimaio10@gmail.com>; Amirouche Boubekki
>         <amirouche.boubekki@gmail.com>
>         <mailto:amirouche.boubekki@gmail.com>; Chris Harding
>         <chris@lacibus.net> <mailto:chris@lacibus.net>; xyzscy
>         <1047571207@qq.com> <mailto:1047571207@qq.com>; semantic-web
>         <semantic-web@w3.org> <mailto:semantic-web@w3.org>
>         *Subject:* Re: What is a Knowledge Graph? CORRECTION
>
>
>
>
>             On Jun 23, 2019, at 5:35 PM, ProjectParadigm-ICT-Program
>             <metadataportals@yahoo.com
>             <mailto:metadataportals@yahoo.com>> wrote:
>
>             Again, let us look at the issue at hand. Artificial
>             intelligence requires we represent knowledge in some
>             format. All forms brought to the fore so far stick to a
>             pretty simple way of representing knowledge.
>
>         Most (all?) of the KR proposals put forward in AI or cognitive
>         science work have been some subset of first-order predicate
>         logic, using a variety of surface notations. There are some
>         fairly deep results which suggest that any computably
>         effective KR notation will not be /more/ expressive than FO
>         logic. So FOL seems like a good ‘reference’ benchmark for KR
>         expressivity.
>
>             What we should be looking for is a generalized form in
>             which objects can be linked. The graph is an obvious form.
>
>             But we are focusing to much on the nuts and bolts level.
>
>             Since it is the generally accepted intention to use AI in
>             all walks of professional, commercial, personal and
>             academic life, we should be looking at the various ways of
>             representing knowledge.
>
>             Otherwise we end up creating knowledge representation silos.
>
>         Avoiding KR silos was one of the primary goals of the entire
>         semantic-web linked-data initiative. But this has many
>         aspects. First, we need to agree to all use a common basic
>         notation. Triples (=RDF =Knowledge Graph =JSON-LD) has emerged
>         as the popular choice. Getting just this much agreement has
>         taken 15 years and thousands of man-hours of strenuous effort
>         and bitterly contested compromises, so let us not try to undo
>         any of that, no matter what the imperfections are of the final
>         choice.
>
>         The next stage, which we are just getting started on, involves
>         agreeing on a common vocabulary for referring to things, or
>         perhaps a universal mechanism for clearly indicating that your
>         name for something means the same as my name for that same
>         thing. This seems to be much harder than the semantic KR
>         pioneers anticipated.
>
>         The third stage involves having a global agreement on the
>         ontological foundations of our descriptions, what used to be
>         called the ‘upper level ontology’. This is where we get into
>         actual metaphysical disagreements about the nature of reality
>         (are physical objects extended in time? How do we handle vague
>         boundaries? What are the relationships between written tokens,
>         images, symbols, conventions and the things they represent?
>         What is a ‘background’? What is a ‘shape’? Is a bronze statue
>         the same kind of thing as a piece of bronze? What changes when
>         someone signs a contract? Etc. etc., etc.) This is where AI-KR
>         and more recently, applied ontology engineering (not to
>         mention philosophy) has been working for the past 40 or 50
>         years, and I see very little hope of any clear agreements
>         acceptable to a large percentage of the world’s users.
>
>
>
>
>             Category theory diagrams, graphs and Feynman diagrams are
>             three well known forms of representing knowledge graphs,
>             but only in semantic web technologies we specify tuples, a
>             restrictive form of representation.
>
>         Category diagrams and Feynman diagrams are meaningful only
>         within highly restricted and formal fields (category theory
>         and quantum physics, respectively) so have little to do with
>         general KR. If your point is that diagrams are useful, one can
>         of course point to many examples of them being useful to human
>         users, but this does not make them obviously useful in
>         computer applications.
>
>         Tuples are not more restrictive than graphs, since a
>         collection of tuples is simply one way to implement a graph.
>         Tuple stores ARE graphs.
>
>         Best wishes
>
>         Pat Hayes
>
>
>
>
>             Milton Ponson
>             GSM: +297 747 8280
>             PO Box 1154, Oranjestad
>             Aruba, Dutch Caribbean
>             *Project Paradigm*: Bringing the ICT tools for sustainable
>             development to all stakeholders worldwide through
>             collaborative research on applied mathematics, advanced
>             modeling, software and standards development
>
>             On Sunday, June 23, 2019, 3:57:01 AM ADT, Paola Di Maio
>             <paoladimaio10@gmail.com <mailto:paoladimaio10@gmail.com>>
>             wrote:
>
>             Chunks are also used in NLP (which is part of/related to
>             CS either way)
>
>             aka tokens
>
>             Various useful references come up on searching chunks as
>             tokens
>
>             https://docs.oasis-open.org/dita/v1.2/os/spec/archSpec/chunking.html
>
>             https://www.oxygenxml.com/doc/versions/21.1/ug-editor/topics/eppo-chunking.html
>
>             On Sun, Jun 23, 2019 at 1:12 AM Dave Raggett <dsr@w3.org
>             <mailto:dsr@w3.org>> wrote:
>
>
>
>
>                     On 22 Jun 2019, at 14:54, Amirouche Boubekki
>                     <amirouche.boubekki@gmail.com
>                     <mailto:amirouche.boubekki@gmail.com>> wrote:
>
>                     Le ven. 21 juin 2019 à 16:27, Dave Raggett
>                     <dsr@w3.org <mailto:dsr@w3.org>> a écrit :
>
>                         Researchers in Cognitive Science have used
>                         graphs of chunks to represent declarative
>                         knowledge for decades, and chunk is their name
>                         for an n-tuple.
>
>                     I tried to lookup "graph of chunks" related to
>                     cognitive science. I could not find anything
>                     interesting outside this white paper about
>                     "accelerating science" [0] that intersect with my
>                     goals.
>
>                     [0]
>                     https://cra.org/ccc/wp-content/uploads/sites/2/2016/02/Accelerating-Science-Whitepaper-CCC-Final2.pdf
>
>                 Chunks are used on cognitive architectures, such as
>                 ACT-R, SOAR and CHREST, and is inspired by studies of
>                 human memory recall, starting with George Miller in
>                 1956, and taken further by a succession of
>                 researchers. Gobet et al. define a chunk as “a
>                 collection of elements having strong associations with
>                 one another, but weak associations with
>                 elements within other chunks.” Cognitive Science uses
>                 computational models as the basis for making
>                 quantitive descriptions of different aspects of
>                 cognition including memory and reasoning. There are
>                 similarities to Frames and Property Graphs.
>
>                 Dave Raggett <dsr@w3.org <mailto:dsr@w3.org>>
>                 http://www.w3.org/People/Raggett
>
>                 W3C Data Activity Lead & W3C champion for the Web of
>                 things
>
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