SHARED VOCABULARIES FOR COLLECTIVE INTELLIGENCE

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Information about SHARED VOCABULARIES FOR COLLECTIVE INTELLIGENCE
Technology

Published on July 3, 2009

Author: PaolaDIM

Source: slideshare.net

Description

Understanding the importance of common vocabularies for collective intelligence, the EIIF XG Incubator example for Emergency Management

Shared Vocabularies for Collective Intelligence DEST/IEEE 2009 Paola Di Maio, University of Strathclyde

Contents  Collective Intelligence  Shared Knowledge Representation  Syntax, Semantics, Pragmatics  Shared vocabularies  Emergency management  EIIF W3C XG

Natural Ecosystem

Digital Ecosystem

Knowledge Ecosystem

Human Collective Intelligence.  The dynamic aggregation of cognitive, reasoning and knowledge resources of humans supported by intelligent and networked information systems.

Intelligence as collective property  important parts of our intelligence reside in collective properties, not individual properties  important parts of our personal cognitive processes are caused by unconscious and automatic processes such as signaling and mimicry.  modeling humans as a distributed, network-based intelligence and then layer on individual cognitive processes is a radical change of emphasis for most researchers. (Alex Pentland, MIT)

CI as COMPLEX SYSTEM  Emergence results from dynamic combination of a system components, and based on the dependence of the whole on its parts, and their parts mutual interdependence and specialization.  Pattern formation: are the visible, orderly outcomes of self-organisation and the common principles behind matching behaviors.  Paradoxes. Diverse and heterogeneous components of a system can results in contrasting and sometimes opposed characteristics both being present , such as simplicity and complexity, order and disorder, random and predictable behavior,

IMPLICIT VS EXPLICIT CI  In explicit CI, individuals actively contribute information, knowledge and reasoning resources to a common repository – say a web based environment – so that they can be combined and manipulated.  Implicit CI takes place when our intelligence is tapped without individuals knowing it Whenever browsing the web while logged in into our accounts, our search history is recorded, Google even made it a useful feature: when 'search history' is on, a trail will be kept, surely useful in many ways, and potentially a gold mine of information. One of the caveats of implicity CI is intellectual property. 

BENEFIT: Speed of Aggregation  Speed advantage: Assume a fire emergency, of wildfire spreading over a region. Classical Examples of Collective Intelligence have sprung up during large scale disasters in recent years, using simple tools such as blogs, wikis and webboard where citizens would post information incident related information.

BENEFIT: Capacity, Reach, Quality, Complementarity  Diverse and complementary backgrounds and opinions  widest breadth and depth  provided adequately engineered CI process are in, the quality of the outcome from a collective efforts is higher than in individual efforts.

CO EVOLUTION

LIMITATIONS OF CI  The way that ants map out their environment, that bees decide which flower fields to exploit, or that termites build complex mounds, may create the impression that these are quite intelligent creatures. The opposite is true. Individual insects have extremely limited information processing capacities. Yet, the ant nest, bee hive or termite mound as a collective can cope with very complex situations. [...] The obvious question is whether high collective intelligence can also emerge from high individual intelligence. Achieving this is everything but obvious, though. The difficulty is perhaps best illustrated by the frustration most people experience with committees and meetings. Bring a number of very competent people together in a room in order to devise a plan of action, tackle a problem or reach a decision. Yet, the result you get is rarely much better than the result you would have got if the different participants had tackled the problem individually.  Francis Heylighen

Examples of CI  Collective Knowledge Bases  Indices  Collective reasoning and problem solving  Collective decisions Making  Forecasting/Prediction Markets

Stochastic Determinism  Stochastic, from the Greek "stochos" means "aim, guess", referring to conjecture and randomness. SD refers to the global logic that underpins the development of a system as the result of individual behaviors of a community of individuals appear to be random, or at least not following a hierarchical, centrally imparted behavior, yet resulting in an organic, socially purposeful action. In human CI systems, this principle corresponds to the state of randomness of communities where participants are not selected on the merit of their seniority, rank or expertise, but open (uncrontrolled) participation is encouraged. Collective intelligence relies on the principle of participation, thus characterized by chaotic patterns of interaction.( W. Sulis)

Interactive Determinism  According to this principle, the interaction among the constituents of a system results in some unique collective property, a type of synergy where the sum is more than just the sum of its factors. Thanks to ID, a system defines it dynamic processes on the fly, as a constant flow of chain reactions that are 'unpredictable' however they follow some built in logic. Self organization is the result of ongoing interactive determination and adjustments .( W. Sulis)

NON REPRESENTATIONAL CONTEXTUAL DEPENDENCE  CI behavior is determined by adaptive responses to the interaction among individuals and their environment, and does not depend on a shared cognitive representation (knowledge representation, model of the world). Biological systems do not have mental capabilities in the cognitive sense, and their behavior can be boiled down to a set of environmental responses. In biology, simple life forms do not posses the cognitive apparatus to support mental capabilities required for mental models to form, in contrast to human systems whose communication depends on shared conceptual and semantic models.( W. Sulis)

SHARED KR  EXPLICIT HUMAN CI REQUIRES SHARED KNOWLEDGE REPRESENTATION  Models (Ontology, schemas)  Artifacts (vocabularies)

Image by P Levy

Shared Vocabularies  Different kinds of vocabularies: (taxonomies thesauri, glossary data dictionary)  Shared vocabulary is generally a controlled vocabulary

Controlled Vocabulary Paradox: No single definition of what a CV is * A carefully selected set of terms - words and phrases - such that each concept from the domain of discourse is described using only one term in ... en.wiktionary.org/wiki/controlled_vocabulary * A set of standard subject terms used by a database to describe the subject content of the items cited within the database. Many, if not most, databases use a controlled vocabulary. These controlled vocabularies vary from database to database. ... www.clarion.edu/395/63165/ …. many other definitions of what a controlled vocabulary is …

Lexical Relations

Integration vs Interoperability

PRAGMATIC SEMANTIC SYNTACTIC. Carlile

Syntax, Semantic, Conceptual, Pragmatic

Shared Vocabulary Levels  Syntax (schema, xml, rdf)  Semantics (meanings)  Conceptual (representation)  Pragmatic (use)  Procedural (common processes)

EMERGENCY MANAGEMENT  In a broad sense, it is envisaged that there is a top level 'universal' interoperability requirement, which is to support the communication and mutual reinforcement of all potential agents able to provide capability to deliver aid and act as first responders during an emergency to interoperate  Responders need the ability to easily and fluidly share information, voice data and video. That is not possible with most deployed systems. [Bob Block]  In such unconstrained scenario responders may be a mixed bag of organisations and individuals whose operations are regulated by different protocols, who communicate in different languages and following different rules, each providing a contribution to overall emergency relief capability. The above is likely to be a chaotic 'open world' scenario, where resources and decision making are distributed, and coordination is the key strategic requirement

Functional Boundaries  Resources and Assets  Safety & Security  Staff Responsibilities  Utilities Management  Patient, Clinical, Medical  SLA and QoS  Security  Ethics

Problem Space Terms/concepts used by different agencies in the same operational field Terms/concepts used by different agencies in different operational fields Terms/concepts used by agencies in different countries, across 1. and 2. above

W3C EIIF  Incubator Group  Aim to create common framework for information exchange  EM Metadata  Open, encourages wider participation  Many challenges, creating the common view is non trivial

Framework Diagram

Vocabulary

Conclusion  Information Integration/Interoperability is necessary for optimisation of the supply chain in EM (and other fields) for innovation, process transformation, agility  Understanding the underlying challenge of shared vocabularies may lead to more problems initially,but to more realistic and sound solutions in the long term  Likely to remain work in progress

Qs?  Thank you for listening  Questions, comments, suggestions,  Paola.dimaio at g/mai'l

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