Pierre Lévy proposes using a semantic language called IEML (Integrated Electronic MetaLanguage) to advance collective intelligence on the internet. IEML would allow for: 1) Semantic interoperability between different ontologies, folksonomies, and languages. 2) A transparent semantic addressing system to connect ideas rather than just documents. 3) Empowering writing and reading by generating texts automatically from concepts. IEML aims to enhance collective intelligence by making the underlying semantics of online information more explicit and manipulable.

1. Toward a Civiliza-on of
Collec-ve Intelligence
Prof. Pierre Lévy (Twi;er: @plevy)
Fellow of the Royal Society of Canada
Canada Research Chair in Collec-ve Intelligence
University of O;awa

2. Evolu-on of Media
(From 2000) Ubiquity, interconnection and animation
of cultural signs (software). Social Computing. New
sign systems. Knowledge economy.
(From 1500) massive technical self-reproduction and
diffusion of the alphabet and other cultural signs. New
languages (animated images, etc.) Scientific notation
progress. Industrial economy.
(From - 1000) Digitization and universalization of
writing reduced to thirty phonetic signs. Notation of
numbers by position, zero. Commercial economy.
(From - 3000) Autonomous technical memory of
language. Ideographic Signs. Numerals,
measurement units. Agricultural economy.
(From - 300 000) myths, rites, oral transmission,
memory inscribed in matter. Icons. Arts of
memory. Hunting-gathering economy.

3. Social Media / Social Compu-ng Features
• Global sharing : photo (Flickr), video (Youtube), music / P2P (Bi;orrent),
bookmarks (Delicious), knowledge (Wikipedia, Freebase)
• Distributed crea3on : user‐generated content, blogs (Wordpress), podcasts,
ci-zen journalism
• Social networking : social networks (Facebook, Myspace, Linkedin, Xing,
Pulse, NING...), virtual worlds (Second life), instant micro‐blogging (Twi;er)
• Streaming (Twi;er, Facebook, Friendfeed, Atom or RSS Feeds)
• Mass collabora3on : wikis, opensourcing, crowdsourcing
• Collabora3ve assessment : forums, ra-ngs, reviews (Bazaarvoice)
• Social bookmarking / tagging / categoriza3on (Digg, Delicious, Twine, Diigo,
Stumbleupon, Flickr, YouTube...)
• Cloud compu3ng : data and applica-ons are on‐line in huge distributed
data‐centers (Google, Yahoo, Facebook, Twi;er, Amazon...). SoZware as a
service. Scalability.

4. Web n.0, Social Compu-ng, Crowdsourcing : A Global Conversa-on ?
Yes, the digital conversa-on ! But what about seman-c interoperability:
different languages, folksonomies, classifica-ons, ontologies...?

5. Cyberspace Evolution
Semantic
Space
Interconnec-on between ideas (via seman-c tags). "
Uniform Seman-c Locator = IEML * concept address **
Collaborative societies of semantic agents, subject-centric computation.
2015 Collective intelligence growth. Augmentation of sense-making.
Web
Interconnec-on between documents (+ data)
Uniform Resource Locator = h;p:// page address.
Centralized search engines, browsers.
1995 Global multimedia public sphere.
Internet
Interconnec-on between computers.
Internet Protocol = server address.
Routers, user-friendly PC applications
1980 Personal computing. Virtual communities. "
Digital media convergence.
Computer
Interconnec-on between transistors.
Computer memory = bit address. "
Operating systems, programming languages
1950 Augmentation of arithmetical and logical processing.

6. Computational Collective Intelligence
Seman-c global meta‐ group of
Space IEML / USLs
language concepts
global meta‐
WWW linked data HTTP / URLs
database
global meta‐ society of
Internet computer automata
TCP / IP
symbolic pervasive comp.
Compu-ng Chips / OS
manipula-on (mobiles, things,
Bits addresses
automata robots...)
Augmenta-on Objects in Addressing
of CI rela-on system

7. Toward a CI Science
Cyberspace
scien-fic observatory / digital mirror of CI
Reflexive Collec-ve Intelligence
driver of human development
Human Development
prosperity, health, educa-on, security, peace,
environment, cultural heritages, research, innova-on...

8. aspiration
creation
creation
collective
creation
Intelligence
creation
aspiration
Collec-ve Intelligence Dynamics

9. Governance / values
Rights / duties
Will networks
ETHICAL CAPITAL
Arts Finance
Sciences Competence
Knowledge networks
Power networks
EPISTEMIC PRACTICAL
CAPITAL CAPITAL
Collective
Intelligence
CULTURAL
CAPITAL BIOPHYSICAL
CAPITAL
Messages Equipment / technology
Medias Health / environment
Documentary networks
Bodily networks
SOCIAL CAPITAL
Trust
Social roles
Personal networks

10. WILL
COLLECTIVE
Collective
INTELLIGENCE
Intelligence
PEOPLE

11. Layers of Seman-c Processing
Points (USLs): 6 primi-ves, sequences of 3L primi-ves (0⩽L⩽6),
categories, catsets, USLs
FORM
(syntax)
Perspec-ves: series, matrices, trees
Terms: dic-onary = correspondence points/natural language +
network of seman-c rela-ons between terms
COLOR
(seman-cs)
Texts (USLs with a meaning): Gramma-cal rules for the
genera-on of texts automa-cally transl. into nat. languages
Circuits: networks of texts
LUMINOSITY
(pragma-cs)
Flows: circula-on of seman-c energyn in circuits, following the
rules of informa-on economy games

12. The Bodies of Collec-ve Intelligence
SEMANTIC BODY
Forms: Sets of USLs and perspec-ves
Colors: Meaning of the USLs
ENERGY BODY
Circuits: graphs of USLs
Flows: economic, electric, neural,... models
DATA BODY
Data Mul-‐Media
3D+t. Addresses Rep of VB User‐controlled
automatable
func-ons

13. The Nature of Collec-ve Intelligence
group of transforma-on seman-c space
DIGITAL MEDIA form : virtual essence
ECOSYSTEM
color : actual essence
(self‐observa-on) symbolic bodies
luminosity : virtual existence
data : actual existence
SYMBOLIC
CI
COGNITION subjec-ve experience : virtual presence
GAMES
(observer)
objec-vity : actual presence
techno‐biological environment
material bodies
3D MATERIAL molecular machines
ECOSYSTEM par-cles / waves
(phenomena)
group of transforma-on unified field

14. IEML and the « Seman-c Web »

15. Differences of nature between
IEML and XML / RDF / OWL
• OWL has no seman3c content in itself: no verbs, nouns, adjec-ves,
adverbs, preposi-ons, inflec-ons, etc. OWL is rather a file format for
descrip-on logics.
• IEML has a seman3c content in itself. Users can generate proposi-ons,
complex phrases with several proposi-ons and « texts » from the
syntax and dic-onary of IEML.
• IEML can be expressed in any file format, including XML, RDF and
OWL. There is currently an automa-c translator from a cursive
nota-on of IEML (called STAR), to binary and XML nota-ons of IEML.
IEML is not a data format!
• It is indeed possible to use IEML to describe OWL ontologies (and so
to decompartmentalize dis-nct ontologies), or to describe in OWL the
complex network of concepts of the IEML dic-onary (like wordnet has
– almost ‐ done for the english language).

16. Differences of goals between
IEML and XML / RDF / OWL
• 1) Seman-c interoperability
– Standardizing data formats is already done by the W3C and other standardiza-on
ins-tu-ons.
– But diversity of data formats is not the only obstacle to seman-c interoperability :
diversity of ontologies, folksonomies, classifica-on systems, natural languages...
– IEML can be used in the context of ontologies with very different hierarchies of
concepts
– Once expressed in IEML, a complex concept ‐ the meaning of a *tag ‐ can be
automa-cally translated to any natural language supported by the IEML dic3onary.
• 2) Transparency of seman-c addressing system
• 3) Empowerment of wri-ng / reading
• 4) Symbolic tool for self‐observa-on and self‐reference of collec-ve
intelligence
These goals have to be addressed by humani-es and social sciences, but
these sciences need the help of soZware engineering.

17. Toward a transparent
seman-c addressing system (1)
• Opacity by design of the URIs
– h;p://www.w3.org/TR/webarch/#uri‐opacity
• By contrast, IEML expressions form a group of
transforma3ons. Automatable algebraic transforma-ons
on IEML symbols correspond to automatable algebraic
transforma-ons on significa-ons (on “seman-cs”).
• The IEML seman-c space (the immense set of IEML
« texts », called USLs ) is in principle independent of the
URI address space just as it is independent of any physical
or telecommunica-on addressing system.

18. Toward a transparent
seman-c addressing system (2)
• IEML can bring to the system of URIs a general seman3c
interconnec3on and a full group of transforma3on on
seman3cs. IEML‐URIs can be directly used as concepts in
RDF or OWL. The IEML research program can offer an
alterna-ve grounding to the en--es of the Web of data,
mapping URIs to such IEML‐URIs.
• The power of IEML can be leveraged by the exis-ng
standards of the Web of data. Symmetrically, the
expressive and algebraic proper-es of IEML can leverage
the current Web of data by providing it with a novel
grounding that can make it more seman-c.