Modeling and Linked Data Publishing of multilingual KOSs in

theAgricultural Domain

Mauro Dragoni

Fondazione Bruno Kessler (FBK)

Shape and Evolve Living Knowledge Unit (SHELL)

https://shell.fbk.eu/index.php/Mauro_Dragoni - dragoni@fbk.eu

Organic.Lingua Closure Workshop, Rome, Italy – February 6th, 2014

Background

Knowledge Organization Systems

Knowledge Organization Systems (KOSs), encompass all types of schemes for organizing information and promoting knowledge management.

They have been introduced to reduce the ambiguity of natural language when describing and retrieving information.

KOSs include various classification types & schemes (Glossaries, Taxonomies, Thesauri, Classifications, Ontologies).

The importance of KOS

… in general Common dictionary of terms.

A shared and formal interpretation of the domain.

Solve ambiguities;

Share knowledge (not only between humans, but also between machines)

… in Information Access Different people may use different words for the same

concept or employ different concepts to refer to the same scientific terms.

KOSs may improve access to (mostly digitally) stored information, by offering structured ways to represent and model it.

Challenges

Evolution of existing KOSs (revisions, additions/deletions of concepts);

Multilinguality issues (KOSs available in multiple languages);

Collaborative working (groups of experts based in different countries with different competencies working on the same tasks/scenarios).

Exposure of the modeled information and linking with third-party KOSs

Evolution

Changes in conceptualization

Increasing/decreasing the granularity of the representation

Knowledge enrichment

Multilinguality

Break the language barriers

Make contents accessible transparently with respect to the language

Increasing the capability of sharing knowledge

Collaboration

Exposure and Linking

Make knowledge consumable by third-party services

Avoiding the replication of the knowledge

Contextualize the modeled knowledge within the domain

An architecture for collaborative modeling, evolution, and exposure of multilingual KOSs

MoKi basic features

It is based on the use of wikis

It implements different views built based on the expertise of different users

It stores information both in unstructured and structured ways

Different views for different roles

Support for multilingual ontology management

Modelling toolDomain expert

Knowledge Engineer

Knowledge Engineer

Domain expert

Translation Services

Language ExpertLanguage Expert

Connections with external components and data exposure

Automatic suggestions of mappings between ontologies

Managing ontology evolution

Entity workflow management

Exposure service in different formats (OWL, SKOS, …)

Terms/Concepts extractor

…

What happened in the Organic.Lingua project

What does Organic.Lingua MoKi include?o The connection with three different machine

translation services.

o An ontology enrichment service for retrieving suggestions about new concepts based on the analysis of external textual resources.

o A mapping suggestion service allowing the creation of linking between the Organic.Lingua ontology and external ontologies.

o The support for entity evolution workflow in order to control the update of each entity defined in the Organic.Lingua ontology.

o An ontology service providing an API Rest Service for the exposure of the ontology in Linked Open Data

What happened in the Organic.Lingua project

How the Organic.Lingua ontology evolved during the project:o entity creation: 54

o entity update: 2160

o entity deletion: 25

o entity translation: 2136

o discussion creation: 218

o discussion update: 492

o 2 languages added: Italian and Latvian

o description added for all languages

o 260 concepts have been mapped with AGROVOC

Mauro Dragonihttps://shell.fbk.eu/index.php/Mauro_Dragoni dragoni@fbk.eu