humanml in new kinds of collaborations

9 December 2003 HumanML in New Kinds of Collaborations

Collaboration Expedition Workshop #30

1

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



2

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



3

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

ML: The abbreviation for Markup Language



4

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



5

Incubating

Framework

Conditions

XML, RDF

HumanML



6

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



7

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



8

HumanML Goals for Collaborations

Increase “Soft” Human Science Capital (Adding Value) 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



9

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



10

HumanML Structure



11

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.



12

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



13

HPCDML Designed for 3D

Physical Accuracy AnatML, FMA, Medical Informatics H-Anim, VRML/X3D

Kinesic Behavioral “Vocabulary” for Bodily Gestures Motion Capture “Native Dancer”



14

Kinesic Motion Capture Sample



15

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



16

Emotional Expressions Sample



17

Cognition in Environments

Application Area Basic Concepts… More to come



18

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.



19

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



20

XML Schema for Semiosis, Semiote<xs:complexType name="Semiosis" abstract="true">

<xs:annotation><xs:documentation xml:lang="en">

Semiotic Communication ModeSemiosis 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 AgentA 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>



21

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



22

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



23

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



24

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



25

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



26

CRM and ROI in Child Protective Services Slide 1



27




28




29




30

Collaboration Expedition Workshops Provide Incubator

Digital Dividends Brochure Practice-Centered Research and

Design Report Two Years Work Now Showing

Results



31

HumanML Mission Complements

Collaboration Process XML & RDF Provide Interoperability GPRA of 1993 Taking Hold HumanML Aids Sematic Web

Semiotic Communications Processing Inference Engine Modeling



32

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



33

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



34

humanml in new kinds of collaborations

Documents

human capital90

individual human mindsuseful

specific vocabulariesuse

rdfhumanmlhuman capital

root xml schema element

humanml namespace

emergency management

valuebuild applicationarea