Web Language

Pierre Lévy

Sujets

• Comunicación
• Cultura
• Conocimiento

Informations

• Publié par: McLuhan-Marshall
• Nombre de lectures: 24
• Langue: Español
• Poids de l'ouvrage: 1 Mo

Extrait

Cyberspace and the Future of Memory

Vic e-week 2006

Prof. Pierre Lévy

Canada Research Chair in Collective Intelligence Fellow of the Royal Society of Canada University of Ottawa

Evolution of Cultural Memory

Cybers ace 2000

Mass Media 1500

Alphabet -1000

Writing -3000

Orality -300000

Ubiquity, interconnection and activity of signs. Semantic numbers.

Technical self-reproduction and broadcasting of signs. Scientific notations.

Universal writing system using +/ 30 - signs: phonograms. Positional notation, 0.

n T N e u c m h e n r ic al a s l .     m M e e m as o u r r y e  o m f  e l n a t u g n u i a t g s. e: ideograms.

Myths, rites, oral transmission. Icons.

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Limits of the Contemporary Web

Linguistic, cultural and disciplinary fragmentation. Search engines look for characters strings instead of looking for concepts or subjects (that are independent from words in natural languages). No automatic hyperlink generation between documents on same subjects. No automatic semantic distance calculus (even in relatively homogeneous corpuses). No transverse automatic inferences (across ontologies, terminologies or documentary languages).

Computer memory = bits addresses . Operating systems. Applications software Augmentation of logical and arithmetical processing.

Internet Protocol = information servers addresses. Routers. Personal computing. Virtual communities. Digitized media convergence.

Virtual Memory Architecture

Noos here 2015

< IEML> concepts addresses </IEML>. Semantic computing, multimedia exploration. Shared virtual semantic memory. Global collective intelligence. Augmentation of interpretation.

Internet 1980

Com uter 1950

Web 1995

URL = http://pages addresses. Search engines, browsers. Global multimedia hypertextual public sphere.

ebwtoi nentccrnoInte neenarttsis.sro om cenweet bonti.sretupnncereocItn itnob teewned couments.ntIecnncoer ions.gnificateewtis noitceb nrcteneonIn

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Why Semantic Numbers ?

(1) Natural constraint: Natural languages (semantic adressing systems of human memory) are designed by biological evolution to be processed by brains, not by computers. (2) Cultural opportunity: Interconnected automatic symbol manipulators compose the global medium of human language and cultural signs. (1) AND (2) => Problem: what semantic addressing for the virtual memory of collective intelligence ? Response to the problem: A computable symbolic system able to address any concept. IEML semantic numbers. Result : Fully automatable exploitation of the semantic content of information across linguistic, cultural and disciplinary barriers.

The Five Laws of Computational Semantics

1. 2. 3.

4.

5.

No patent : Semantic numbers are public domain. No exclusion : Semantic numbers address a virtually infinite variety of concepts. No ontological hierarchy : Semantic numbers provide a peer to peer relation between concepts and ontologies.

No arbitrary authorithy : The IEML dictionary is built and discussed publicly by a multidisciplinary and multicultural community of ontology managers and metalaguage specialists. No mystery : The IEML community develops a rational methodology to connect semantic numbers to concepts in natural languages.

SYMBOLIC WORK

OPEN TOOLS

COMMON WEALTH

INFORMATION ECONOMY

RESEARCHERS COMMUNITIES People - Applications

COMPUTATIONAL SEMANTICS Concepts: search - relations - analysis - synthesis - inference - measurement

MATHEMATICAL SYSTEM FOR SEMANTIC ADRESSING SEMANTIC WEB IEML RDF - SPARKL - Information Economy Meta Language OWL - other norms - XML - UNICODE WWW : URL - HTTP - HTML

Internet : TCP-IP

DIGITAL MEMORY documents

INFORMATION FLUX

creation

création

aspiration

collective

intelligence

aspiration

creation

Collective intelligence dynamics

création

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Why current social sciences could be better at promoting human development

Sciences of nature since the scientific revolution – Universal physical space – High tech observation instruments – Formalized and consistent languages – High computability – High testability –    Explicit    shareable, cumulative knowledge => strong knowledge management

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Current Sciences of culture – Fragmentation among disciplines and paradigms. No integrated causal model of human development. – Low tech observation instruments – Non-formalized languages or different formalizations according to cultures, disciplines and paradigms – Low computability – Low testability –    Tacit    knowledge (non- shareable, non-cumulative) => weak knowledge management

cultural sciences

natural sciences

MATHEMATICAL CALCULUS

hardware

SL

classical computing

software

semantic computing

conceptware

 EEREVEL HY PLEABURASME GAAM &RPIT CMENAAOMENPHENTIC ABUR SLEASME HT SICAL & BIOLOGICLAP EHONEMAN 

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Human Language

Syntax – Combinations of elements – Multi-leveled articulation Semantic – Potentially infinite # of distinct representations – Hierarchically organized in sets and subsets Pragmatic – Ability to tie and untie a potentatially infinite # of human relationships, using syntax and semantic. ==> Reflexive consciousness ==> Culture ( human collective intelligence)