2001-2003 [email protected] ELITE ENTERPRISES AND KM.
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Transcript of 2001-2003 [email protected] ELITE ENTERPRISES AND KM.
2001-2003 [email protected]
Grid with asymmetric atomic sizeGrid with uniform atomic sizeGrid with varying asymmetric atomic size.• (this last guy must be the right guy, therefore, microscopic
atomic size should be built in. • The different models that use the “layer of understanding” will
determine what granularity they need.
grid of atomic concepts of uniform size;but how atomic should they be?
Scott A. Carpenter, 30-Oct-02-Wed-13:33pm
2001-2003 [email protected]
Grid with varying asymmetric atomic size.•(this last guy must be the right guy, therefore, microscopic atomic size should be built in.
•The different models that use the “layer of understanding” will determine what granularity they need.
2001-2003 [email protected] A. Carpenter, 04-Jan-03-Sat-09:13 am
Taxonomies within taxonomies…how fine?
Probably need to take it down to the individual word as does “Applied Semantics”.
FAST KB
Activity
SubWorkPlan or Test
Element
Hmmm, probably adding more and more redundancy as we move to the smaller taxonomies, as a particular Element (and especially a word or word phrase) is likely to be used in many larger taxonomic units. Therefore, we need an idea information base that feeds this base, and we need an element/word database to feed the information base. Thus, Applied Semantics provides the database. ALL tacit information is captured in the information base, and the tacit knowledge is captured in the knowledge base (FAST).
2001-2003 [email protected]
Document RepositoryUnorganized Information Base
Organized Database (micro micro taxonomy) Applied SemSemi-organized Information Base (micro taxonomy) FAST
Organized Knowledge Base (macro taxonomy) FAST
Scott A. Carpenter, 010-Jan-03-Fri-08:31 am
2001-2003 [email protected]
Document RepositoryUnorganized Information Base containing
independent concepts which are numbered 1-to-N
Organized Database (micro micro taxonomy) Applied SemSemi-organized Information Base (micro taxonomy) FAST
Organized Knowledge Base (macro taxonomy) FAST
1 2 3 … … N 1 2 3 … … N
2001-2003 [email protected]
Back EndStructure Model
DTD/SchemaVocuabularyTaxonomy
KnowledgeEngineers
Back EndGoal Model
DTD/SchemaTaxonomy
SME, Practice Manager
Document RepositoryContains unorganized and
unrationalized information, knowledge, and wisdom
KB Wisdom
WISDOM SYSTEM
I’m trying to figure out how to get applied semantics technology in here; the micro-micro taxonomy concept. What I think Applied Semantics can do is to facilitate conversion of all document repositories into KBs and provide Wisdom Systems!
Scott A. Carpenter, 04-Jan-03-Sat-09:12 am
2001-2003 [email protected]
DATA~100,000 unicode
ideograms for English, and
growing slowly.
INFOApplied Semantics 1,000,000 concepts
for English and growing rapidly
KNOWLEDGE?
Scott A. Carpenter, 04-Jan-03-Sat-10:11 am
2001-2003 [email protected]
Cognitive Paradigm for Learning
Environment (Reality)
Deep abstraction
Shallow abstraction
SimplicityOrder
Understanding
Model
Goal
Wisdom
Mission
Vision
Data
Index
Model
Equations
Goal
Mission
Vision
Data
Index
Information
Knowledge
Complexity Chaos
Mystery
?
?
ontology
taxonomy
index
?
2001-2003 [email protected]
Environment (Reality)
Deep abstraction
Shallowabstraction
Wisdom
Data
Index
Model
Equations
Goal
Information
Knowledge
Mission
Vision
ItemItem
FactFact
SolnSoln
Achievement
Achievement
GrowthGrowth
Scott A. Carpenter, 20-Jan-2003-Mon-23:19 pm
2001-2003 [email protected]
Environment (Reality)
Deep abstraction
Shallowabstraction
Simplicity Order
Wisdom
Data
Index
Model
Equations
Goal
Information
Knowledge
Complexity Mystery
Mission
Vision
Reaction rate parameter data fields
<rr> = f(temp)
Plasma physics(countour space pic)
Radiation losses
T-vs-<rr> index
<rr> varies exponentially with temp
Maximize SpJetPwr
Operate with <rr> = x and T = y because…
Systems Thinking
Component Thinking
Scott A. Carpenter, 010-Jan-03-Fri-10:49 am
2001-2003 [email protected]
Environment (Reality)
Deep abstraction
Shallowabstraction
Simplicity Order
Wisdom
Data
Index
Model
Equations
Goal
Information
Knowledge
Complexity Mystery
Mission
Vision
Reaction rate parameter data fields
<rr> = f(temp)
Plasma physics(countour space pic)
Radiation losses
T-vs-<rr> index
<rr> varies exponentially with temp
Maximize SpJetPwr
Operate with <rr> = x and T = y because…
Need to add more Data boxes with other parameters to support information box and K box.
2001-2003 [email protected]
Measures:1:2:32ab:3a+3b2bc:3b+3c2ac:3a+3c• These ratios should be measurables, but this means that
we have to have a system that can measure it accurately, not ficticiously.
• This picture looks pretty bad, as resources are not well shared.
• These ratios should be part of the VPs and their underlying departments Annual evaluations and profit sharing, so that it becomes the bane of all individuals to contirbute to automated and transparent system and work process and protections (IP).
• VPs don’t know very well the force structure and expertise of the other VPs, therefore, they tend to NOT rely on other’s expertise, but rather to build a reliable known expertise within their own particular organization. Thus, we need to encourage everyone to make each VPs resources known throughout the organization, to measure that, and to communicate that, and then encourage everyone to contribute to automation and transparency and global decision support systems.
• We want to be able to reallocate costly human intelligence to create unique-value growth expertise and service and product value and intelligence delivery value!! That’s what our company is.
• Also provides for visibility of macro and micro strategies, and thus feedback on them and justification.
12bc
2ab
2ac
3c
3b3a
VPb ProfS
VPaEntS
VPc EduS
Scott A. Carpenter, 010-Jan-03-Fri-11:25 am
2001-2003 [email protected]
• I can make an equation for this thing that shows how saving redundant staff will allow allocation of resources to expand value-add intelligence expertise and product and service value adds!!! Max ROI.
• Notice how the overlap has increased! This means the measured ratios are improving.
• Now the VPs might say, wow, as we come to align our processes, perhaps it become simple enough for consolidation into only two VPs, or even 1 VP. Therefore, there must be incentive to automate and transparentize…the benefit to individuals would be annual bonuses and “new” challenge projects!!
• Scott, develop an equation set for this, with valuations, and then write a paper around it!!!!
12bc
2ab
2ac
3c
3b3a
VPb ProfS
VPaEntS
VPc EduS
12bc
2ab
2ac
3c
3b3a
VPb ProfS
VPaEntS
VPc EduS
Scott A. Carpenter, 010-Jan-03-Fri-11:55 am
2001-2003 [email protected]
Vision initiates the learning process by building the Templates, and thereafter works to extend
them.
A small chunk of Environment, filtered through an Index, yields Data
Data, filtered through Rules, yields Information
Information, filtered through a Model, yields Knowledge
Knowledge, filtered through a Goal, yields Wisdom
Vision
Wisdom, filtered through a Mission, yields Vision
IndexEnvironment
(a small chunk)
ModelInformation
What happens in the
environment.
Mission
Rules
Goals
Wisdom(best
practice)
How to use the
environment.
Data
What is in the
environment.
Knowledge(practice)
Why it happens in
the environment.
Imagination is more important than knowledge. - A. Einstein
2001-2003 [email protected]
Words
Common Understanding
Common Values
Unicode Accuracy
Xlation accuracy / Culture context is different, even if the language is common there will be some discrepancy. Common human context is key, and will likely be a focus of future technology development.
Common Values
Scott A. Carpenter, 20-Jan-2003-Mon-23:11 pm
2001-2003 [email protected]
Environment
DATA
VISION
INFORMATION
KNOWLEDGE
WISDOM
ENVIRONMENT(Complexity &
Mystery)
Mission
Goal
Model
Rules
Index
DATA
VISION
INFORMATION
KNOWLEDGE
WISDOM
Mission
Goal
Model
Rules
Index
A concise idea originates here, having a finite expanse (interpretation, scope)
Same overall system, but in a different language, and thus leads to
possibly different understanding – certainly the fuzziness has grown.
ENVIRONMENT(Complexity &
Mystery)
Grapheme 1
Syntax 1
Grapheme 2
Syntax 2
Lang 1Lang 2
Lang 1Lang 2
MindLang 2 MindLang 1
This is a paper! Scott A. Carpenter, 26-Oct-02-Sat-11:54
Carpenter Communication Paradigm (unicode must understand words, meanings, values)
Person has a new idea. This person extrapolates their goal list, and the idea “appears” to solve their mission (feasibility). Person then expands their model (generalization), and the idea “appears” to be a feasible solution. The rules are specifically described structurally that “appear” to make the model work. Then the index is expanded (vocabulary, unicode) and the data is obtained from the environment. How are each of these layers described by the person, by the system? As the concepts work their way down into atomic “understanding”, and then back up again in a different language? The uncertainty in understanding must grow! This implies that none of us will be standing on the same layers of understanding, as each of us will understand each layer slightly differently than anyone else. Fascinating. Note: In the figure below, the grapheme, syntax, and language might also affect the index, rules, model…
2001-2003 [email protected]
Unicode URI
RDF + rdfschema
XML + NS + xmlschema
These markup languages provide for term specification (I.e. resource definition).
Ontology Layer
Logic Layer
Scott, map this to your 6-layer model of human cognition.
Term definition and term relationships.
Deduce the implications of term definitions and term relationships; that is, add new information or knowledge.
Environment / UniverseWell of infinite mystery and complexity
2001-2003 [email protected]
Words Meaning
Values
Shared Symbols
Shared Understanding
Shared Values
Language Context
Actionable
Useful Output
Sender Receiver
2001-2003 [email protected]
Shared Symbols
Shared Context
Shared Values
UnderstandingLanguage
Teamwork
Communication
ROC
Return on Communication
2001-2003 [email protected]
Shared Symbols
Shared Context
UnderstandingLanguage
Environmentalist Nuclear Engineer
English
Clean the Earth
Kill Nuclear Power!
English
Clean the Earth
Build Nuclear Electric!
Symbols
Context
Values
Shared Values
Teamwork
2001-2003 [email protected]
Technology
MarketingResearch
IntellectualProperty
Ethics
InformationSystems
Advertising
AssetManagement
StrategicAnalysis
ManagingSkills
WorkforceMotivation
Economics
FinancialManagement
Acquisitions, Mergers
RiskManagement
Hedging
Ergonomics
Litigation
MaximizeShareholder
Wealth
Intra-Organizational
Culture
Inter-Organizational
Culture
Communication
MarketAnalysis
Trans-nationalism
2001-2003 [email protected]
Maximize Shareholder Wealth
Research
Risk Manageme
nt
Communication
Corporate Morale
Ergonomics
Workforce Diversity
Advertising
Market Analysis
Litigation
Business Models
Competition
Economics
Ethics
Acquisition & Mergers
Environment pollution
Financial Manageme
nt
Technology
HedgingInformation
Systems
Strategic Analysis
Trans-nationalis
m
Enterprise Resource Planning
Intellectual Property