A complete and up to date presentation of IEML can be found at: https://intlekt.io/ieml/

A Scientific Language

IEML is an acronym for Information Economy MetaLanguage. IEML is the result of several years of fundamental research under the direction of Pierre Lévy, fourteen years of which were funded by the Canadian federal government through the Canada Research Chair in Collective Intelligence at the University of Ottawa (2002-2016).

For whom is it intended?

IEML is a multidisciplinary project at the confluence of AI, data science, linguistics and digital humanities. Because the metalanguage IEML has computable semantics it will be of interest to people working in the fields of artificial intelligence, business intelligence, and data science. This metalanguage proposes new uses and theory of metadata also relevant to researchers in the fields of heritage conservation (libraries, museums), digital humanities, and data journalism. Finally, since IEML increases collective intelligence, it will be of interest to practitioners in knowledge management, collaborative learning, and digital communications.

In this day and age, semantic interoperability among databases, languages, disciplines, etc. is a problem for a lot of professionals and researchers in the above-mentioned fields. In addition, after several years of deep learning frenzy, there is a renewed interest in symbolic AI (or at least in a synthesis between statistic and symbolic AI), and IEML is a powerful symbolic tool.

Main properties

In 2020, IEML is the only language that has the following three properties:

– it has the expressive power of a natural language;

– it has the syntax of a regular language;

– its semantics is unambiguous and computable, because it is aligned with its syntax.

In other words, it is a “well-formed symbolic system”, which comprises a bijection between a set of relations between signifieds, or meanings (a language) and a set of relations between signifiers (an algebra) and which can be manipulated by a set of symmetrical and automatic operations. 

On the basis of these properties, IEML can be used as a concept coding system that solves the problem of semantic interoperability in an original way, lays the foundations for a new generation of artificial intelligence and allows collective intelligence to be reflexive. IEML complies with Web standards and can be exported in RDF. IEML expressions are called USLs (Uniform Semantic Locators). They can be read and translated into any natural language. Semantic ontologies – sets of IEML expressions linked by a network of relations – are interoperable by design. IEML provides the coordinate system of a common knowledge base that feeds both automatic reasoning and statistical calculations. In sum, IEML fulfills the promise of the Semantic Web through its computable meaning and interoperable ontologies. IEML’s grammar consists of four layers: elements, words, sentences and texts. Examples of elements and words can be found at https://intlekt.io/

In short, IEML is a language with computable semantics that can be considered from three complementary points of view: linguistics, mathematics and computer science. Linguistically, it is a philological language, i.e. it can translate any natural language. Mathematically, it is a topos, that is, an algebraic structure (a category) in isomorphic relation with a topological space (a network of semantic relations). Finally, on the computer side, it functions as the indexing system of a virtual database and as a programming language for semantic networks.

Philosophical and anthropological perspective

The human species can be defined by its special ability to manipulate symbols. Each great augmentation in this ability has brought enormous economic, social, political, religious, epistemological, educational (and so on) changes.

There have been only four of these big changes. The first one is related to the invention of writing, when symbols became permanent and reified. The second one corresponds to the invention of the alphabet, Indian numerals and other small groups of symbols able to represent “almost everything” by their combination. The third one is the invention of the printing press and the subsequent invention of electronic mass media. In this case, the symbols were reproduced and transmitted by industrial machines. We are currently at the beginning of a fourth big anthropological change because the symbols can now be transformed by massively distributed automata in the digital realm. We still do not have invented the symbolic systems and cultural institutions fitting the new algorithmic medium. So my research in the past 20 years has been devoted to the invention of a symbolic system able to exploit the computational power, the capacity of memory and the ubiquity of the Internet.

This is the main motivation behind my work on IEML: I took up the challenge of inventing a symbolic system that makes the most of the new digital environment to serve human cognitive augmentation.

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For scientific publications, reports and other documents, look here.

Prof. Pierre Lévy, PhD., University of Montreal
Fellow of the Royal Society of Canada

CEO and founder of INTLEKT Metadata Inc.