HumanML in New Kinds of Collaborations: HumanML in New Kinds of Collaborations Collaborators-participants from:
New York Academy of Medicine (NYAM)
OASIS HumanMarkup Technical Committee (TC)
OASIS Web Services for Remote Portlets (WSRP) TC
OASIS Emergency Management (EM) TC
Oracle Corporation
Disaster Management Interoperability Services
A New Kind of Collaboration: A New Kind of Collaboration Public Healthcare Preparedness Portal
Proof of Concept = Example
Web Services Portal = Pre-Arranged, Multiple Sources of Information in Single Display Format
Common Alerting Protocol (CAP) for Emergency Management Community Starts Process
Time Critical Follow-On Map & Medical Information for First Responders
Further Developments
HumanML Terminology: HumanML Terminology HumanML: General abbreviation for entire set of Human Markup Language specifications
Huml: The name of the ‘root’ XML Schema Element of the Human Markup Language Primary Base XML Schema Specification (and, therefore of the entire set of languages)
huml: The namespace prefix which identifies the HumanML namespace; also the abbreviation used for the OASIS HumanMarkup Technical Committee
HPCDML: The abbreviation for the Human Physical Characteristics Description Markup Language
ML: The abbreviation for Markup Language
Incubating: Incubating Public Information Environments (Framework)
New Kinds of Collaborations (Conditions)
Emerging Technologies (ET) (Vehicles)
Open Standards - ISO, W3C, IETF, OASIS
XML/RDF = Vocabulary + Resources
HumanML provides “Connection”
Connecting Emerging Technologies Vehicles
Ongoing Environment for Exploration
Incubating : Incubating Framework
Conditions XML, RDF
HumanML
Human Capital = Value of Human Knowledge: Human Capital = Value of Human Knowledge Most Capital inside Individual Human Minds
Useful to Individual but Limited Lifecycle
Less Useful to Groups, e.g. Business, Government “Soft” Human Science Capital Less than “Hard” Physical Science Capital
Lacks Empirical Foundation
Poorly Quantified Social Needs Difficult to Address
“ROI” Difficult to Measure
Factors at Work in Human Capital: Factors at Work in Human Capital 90% of Sum Total of “Hard” Human “Knowledge” Discovered in the Last Two Decades of the 20th Century
Worldwide Social Needs Growing with Economic & Digital Gaps between Affluent & Developing Worlds
Internet “Information Revolution” Set to Spread in Developing World at Stunning Rate in this Decade
HumanML Goals for Collaborations: HumanML Goals for Collaborations Increase Value of Human Science Capital
Build Application-Area-Specific Vocabularies
Use XML, RDF to Quantify Anecdotal Information
Occurences of “Tags” can be tabulated
Frequency and Amount and/or Volume of “Tags” within Population of Standard Documents over Timeframe can be Correlated and Compared to other Data to produce Empirical Analyses
Building Specific HumanMLs: Building Specific HumanMLs Primary Base Schema = Collection of Categories
Secondary Base Schema Built from Application Area- Specific Secondary Schemata
Structural Methodology = Paradigm
Subcommittees Formed by Application Area
Physical Characteristics Descriptions
Cognition
Mediation
Social & Cultural Descriptions
HumanML Structure: HumanML Structure
OASIS HumanMarkup TC Subcommittees (SCs): OASIS HumanMarkup TC Subcommittees (SCs) Current:
Human Physical Characteristics Description ML (HPCDML SC)
Planned:
Cognition in Environments (CogEnv SC)
Mediation SC
Cultural Descriptions
Needs Great Care and Attention to Craft Usability
Needs to include many considerations: History, Ethnography, Geography, Religion, etc.
Human Physical Characteristics Description ML: Human Physical Characteristics Description ML HPCDML Requirements “inclusive”
Designed to Provide Standardized Description of Physical Characteristics of Humans, (Including Ancestral Remains) with Specific Responsibility to Harmonize and Interoperate with Widely Accepted Public Health, Medical, Biometric,Human-Modeling, and Public Safety Standards
Actiively Working With Digital Archive Network for Anthropology and World Heritage (DANA-WH) of the Archeology Technologies Laboratory (ATL) of North Dakota State University
HPCDML Designed for 3D: HPCDML Designed for 3D Physical Accuracy
AnatML, FMA, Medical Informatics
H-Anim, VRML/X3D
Kinesic Behavioral “Vocabulary” for Bodily Gestures
Motion Capture
Non-Verbal Elements of Communication
Kinesic Motion Capture Sample: Kinesic Motion Capture Sample
Showing Emotions in HPCDML: Showing Emotions in HPCDML Emotional Behavioral “Vocabulary” for Bodily Gestures
Modeling Facial Musculoskeletal System for Behavior On Demand
Maintain Goal of Physical Accuracy
Basic Emotions from Primary Base Schema Enable Combinations Using Range of Intensity
Real-Time Interaction Objective
Emotional Expressions Sample: Emotional Expressions Sample
Archaeology Technologies Lab http://atl.ndsu.edu: Archaeology Technologies Lab http://atl.ndsu.edu Emphasizes Digital Technologies
Visualization
Laser Scanning and Digital Imaging
2D Images, 3D Models, Animations
Digital Libraries, Archives, Databases
Content Storage/Access
Distributed Network Systems
Internet 2 (I2) Broadband
Stand Alone and Web-Based Applications
Immersive Virtual Environments (IVE)
Virtual Museum Exhibits (VME)
User Interfaces and Clients
New Portal: http://www.dana-wh.net: New Portal: http://www.dana-wh.net New Portal: http://www.dana-wh.net
Purpose of DANA-WH: Purpose of DANA-WH DANA-WH is a Digital Library collection intended to be a globally accessible, distributed, cross-platform information storage, retrieval , and analysis system containing textual, metrical, and graphical (2D images and 3D models) content utilized in human cultural and biological heritage research and education.
Achieving DANA-WH Goals Requires Widespread Collaboration: Achieving DANA-WH Goals Requires Widespread Collaboration All Domains and Fields of Human Heritage
Archaeology, Archaeometry, Geoarchaeology, Geophysical Prospecting, etc.
Classical Studies and Historical Archaeology
Biological and Medical Anthropology
Paleoanthropology, Paleoethnobotany, etc.
Behavioral and Cognitive Anthropology
Ethnography, Ethnology, and Museum Studies
Linguistics (including writing systems)
and all the rest… (Computer and Information Sciences, Geosciences, and other related fields…)
DANA-WH contains lots of Data: DANA-WH contains lots of Data
Slide22: DANA-WH: Simultaneous Views of Multimedia and Related Data
Slide23: DANA-WH Client Content Display (Fijian Ceramics)
Slide24: DANA-WH: 3D Wireframe (and Point Cloud) Polygon Views
Slide25: DANA-WH: 3D Model with Color Texture Map
3D Caliper Tool: 3D Caliper Tool
Hominid Endocasts: Hominid Endocasts
3D Models of Hominid Fossils: 3D Models of Hominid Fossils Australopithecus africanus, Cranium STS 5, “Mrs Ples”
3D Reconstructions and Animations of Hominid Remains: 3D Reconstructions and Animations of Hominid Remains http://atl.ndsu.edu/thumb2.htm
Cuneiform Writing Systems: Cuneiform Writing Systems
Native Dancer Diabetes Health Care Education Video Game : Native Dancer Diabetes Health Care Education Video Game
Diabetes and Native Americans: Diabetes and Native Americans Diabetes Epidemic: approximately 33% of Native Americans have some form of diabetes
22% of White Earth people have Type 2 Diabetes (so-called adult onset)
Typical onset, 10 years ago: 42 years old
Today, youngest case: 9 years old.
Increased 32% in ages 15-19
Nutrition and Physical Activity: Nutrition and Physical Activity “Reduction in incidence of type 2 diabetes with lifestyle intervention or metformin” (New England Journal of Medicine, 2002)
Percent reduced incidence of diabetes
17% placebo
31% metformin
58% nutrition/physical activity
Video Games:: Video Games: Reach the target audience: 10-18+ “proclivities of youth”
Provide virtual/safe environment to experiment & learn
New, emerging genre of healthy video games
Dance Dance Revolution
Friendly Competition Drives Learning: Friendly Competition Drives Learning Students strive to learn diet and lifestyle to do better in dance competition
Assumes dance aspect of the game is fun & engaging
Proper choices are rewarded with Powwow Regalia that allow dance character to gain more points in each competition
Benefits: Benefits Immediate:
provides a non-threatening, and easy exercise
interactively engages child in health education process
Cultural:
encourages pride in child’s culture
teaches cultural dance skills to children
Provides:
a culturally relevant map to long-term healthy lifestyle and diabetes management
Native Dancer Motion Capture of “Jingle Dance”: Native Dancer Motion Capture of “Jingle Dance”
Virtual Museum Exhibits (VMEs): Virtual Museum Exhibits (VMEs) Enhance Exhibit Space and Maximize Collection Display Copyright ©2003 NDSU Archaeology Technologies Laboratory Samoan Adze #c8940 from Bishop Museum Collection, Honolulu, Hawaii Samoan Virtual Pavilion
Cognition in Environments: Cognition in Environments Application Area
Cognitive Information Processing Models
Interpretation of Interaction Patterns
Basic Concepts…
Roles of Family, Kinship, Clans, Ethnic Ancestry, ‘Culture’
More to come
Cognition Requirements: Cognition Requirements Cognitive Information Processing
DARPA Criteria:
can reason in a variety of ways, using substantial amounts of appropriately represented knowledge;
can learn from its experiences so that its performance improves as it accumulates knowledge and experience;
can explain itself and can accept direction;
can be aware of its own behavior and reflect on its own capabilities; and
can respond in a robust manner to surprises.
More Cognition Requirements: More Cognition Requirements Cognitive Information Processing
Models Processes of Perception
Models Processes of Communication
Models Processes of Decision-Making
Model for Perception Undecided
Semiosis Communication Model
Sign, Signal, Symbol
Semiote = Cognitive Agent
XML Schema for Semiosis, Semiote: XML Schema for Semiosis, Semiote <xs:complexType name="Semiosis" abstract="true">
<xs:annotation>
<xs:documentation xml:lang="en">
Semiotic Communication Mode
Semiosis is a meaningful exchange of signs, signals and symbols among cognitive agents.
NOTE: This process is the model of the human communication process upon which HumanML is based. It can be, and we expect that it will be further enumerated by semiotic types and extended in the Secondary Base Schema and subsequent huml schemata.
</xs:documentation>
<xs:appinfo>NONE</xs:appinfo>
</xs:annotation>
<xs:attributeGroup ref="humlTemporalAtts"/>
<xs:attributeGroup ref="humlCommAtts"/>
</xs:complexType>
<xs:complexType name="Semiote" abstract="true">
<xs:annotation>
<xs:documentation xml:lang="en">
Cognitive Agent
A Semiote is a cognitive agent who participates in meaningful signal exchange among cognitive agents.
NOTE: This element is the actor in the semiotic model of communication It is a set of processors capable of emitting, receiving and responding to signals.
</xs:documentation>
<xs:appinfo>NONE</xs:appinfo>
</xs:annotation>
<xs:attributeGroup ref="humlCommAtts"/>
</xs:complexType>
Peacemaking and the Three Names: Peacemaking and the Three Names Diplomacy Too Specialized
Conflict Resolution Too Negative
Bridging Perspectives Too Undefined
Mediation Just Right
Process Shows Need
Requirements and Charter-writing Underway
Cultural Descriptions: Cultural Descriptions Requirements Under Consideration
Native Ethnic/Linguistic Authors Whenever Possible and Reasonable
Anthropologist Consultation or Training Favored
Authenticity & Accuracy Tracking to Compare Behavior of Self-Identified Cultural Members with Description
Previous HumanML Experience Provides Guidance
Rigorous Documentation & Approval
Continuous Update Capacity Sought
From Constable’s Toward a Model for Language Identification: Defining an Ontology of Language-related categories : From Constable’s Toward a Model for Language Identification: Defining an Ontology of Language-related categories
Diagram of Language Agencies such as HumanMarkup TC Based on Constable’s Proposed Language-related Categories: Diagram of Language Agencies such as HumanMarkup TC Based on Constable’s Proposed Language-related Categories
A HumanML-enhanced Transliteration Example from a Proposed Application Concept: A HumanML-enhanced Transliteration Example from a Proposed Application Concept
CRM for HumanML Users: CRM for HumanML Users HumanML Preferences ML Probable for:
Individual Single-Sign-On Applications
Individual User Profile for in-depth ID Authentication and Personalization
Using Satisfaction Index in tracking Delivery of Highly Targeted Materials from Specific Individual Preferences to:
Eliminate Spam
Produce “Focused” Marketing for Business, and
End User Service and Satisfaction from Receiving ONLY Desirable, Preferred, Requested Information
HumanML Enhancements for CRM : HumanML Enhancements for CRM Combinations of HumanMLs Enhance Traditional CRM Capabilities
HumanML in CRM-Based Results-Analysis Aids Performance Improvements
CRM-Based Results-Analysis Aids Improvement of HumanML
HumanML Goals “Glue” for Collaborations: HumanML Goals “Glue” for Collaborations Improve Communications through Clarity and Accuracy
Provide Means to Model Cognition and Perception
Provide Means to Measure and Evaluate Results
Provide Models for Collaborations by Example
CRM and ROI in Child Protective Services Slide 1: CRM and ROI in Child Protective Services Slide 1
CRM and ROI in Child Protective Services Slide 2: CRM and ROI in Child Protective Services Slide 2
CRM and ROI in Child Protective Services Slide 3: CRM and ROI in Child Protective Services Slide 3
CRM and ROI in Child Protective Services Slide 4: CRM and ROI in Child Protective Services Slide 4
Collaboration Expedition Workshops Provide Incubator: Collaboration Expedition Workshops Provide Incubator Digital Dividends Brochure
Practice-Centered Research and Design Report
Two Years Work Now Showing Results
HumanML Mission Complements Collaboration Process : HumanML Mission Complements Collaboration Process XML & RDF Provide Interoperability
GPRA of 1993 Taking Hold
HumanML Aids Sematic Web
Semiotic Communications Processing
Inference Engine Modeling
Public Healthcare Portal Collaboration: Public Healthcare Portal Collaboration New York Academy of Medicine Proof of Concept Public Healthcare Preparedness Portal
CAP Alert - OASIS Emergency Management TC
Disaster Management Interoperability Services
WSRP 1.0 Web Services for Remote Portlets TC
OASIS HumanMarkup TC
Oracle Corporation
Portal Demonstration Script: Portal Demonstration Script DMIS Issues CAP Message
CAP Message Displayed on Portal
EMT Accesses Portal, Selects CAP Message
EMT Accesses Map Portlet Sequence
EMT Accesses Medical Treatments Information Portlet
Proof of Concept Public Healthcare Preparedness Portal: Proof of Concept Public Healthcare Preparedness Portal
Conclusion : Conclusion Summary
Incubate New Kinds of Collaborations
Provide Added “Measurable” Value to Human Capital
Stress Accuracy
Harmonize Physical Description Standards
Build Toolset for Cognition
Build Toolset for Mediation
Collect Cultural Descriptions
Demonstrate Benefits through Collaborative Projects Enabled by HumanML Standards