Mondeca Labs is our sandbox : we try things out to illustrate the potential of Semantic Web technologies and get feedback from the Semantic Web community

Our credibility in the Semantic Web space is built on our contribution to international standards.

Here we are always looking for new challenges.

"Academia has Questions and Answers. Industry has Problems and Solutions."

Paulo Urbano IHC'2014

"At MondecaLabs, we ask Questions on Problems and provide Solutions by finding good Answers. MondecaLabs Team Our Philosophy

Linked Open Vocabularies

Linked Open Vocabularies (LOV) for the linked data Web, featuring Vocabulary of a Friend (VOAF)

SPARQL Endpoints Status

See in one page public endpoints availability status.

SKOS Reader

View or print SKOS terminology terms in ISO 2788/5964 thesaurus format: alphabetic, hierarchical, or permuted views.

Temporal Knowledge Acquisition

Capture and semantically annotate temporal information. Display and edit results in text mode or in a calendar.

Knowledge Browser

Knowledge Browser (KB) is a web-based portal featuring powerful search capabilites combined with graphical visualizations. It provides intuitive, read-only access to broad audiences who need to visualize, search, navigate and browse collections of enterprise data.


The missing plugin for ontology engineering.


This application helps finding latitude and longitude of any place.

French Visu Debate Online

A visualization of 30 years of debate online based on the topicPage concept around the French Government Website vie-publique

Parrot Tool

An instance of the Parrot tool allowing creating RIF and OWL documentation.

Query Answering over LOV

An access to the Linked Open Vocabulary using natural language questions. The system is able to answer to many forms of questions related to metadata information.

TripleSlogS Demo

A Java-based Tool for Profiling Logs from RDF Stores. This is a web version with limited features.


This small program provides an API which tales as input a vocabulary and suggest a category based on LOV list of tags using machine learning model.

The model used is SVM saved in pickle format, and loaded by the API