Linguistic Data Science and Technologies

This area of research concerns the study of models, methods, and systems for the systematic cross-lingual discovery, exploration, exploitation, of linguistic data on the Web. Particularly, we focus on linguistic linked data technologies, and in the transformation and linking of multilingual language resources for the Web of Data.

PROJECTS

We list below the projects or lines of work and their funded projects:

CURRENT

PAST

OBSERVER (1995-1998)	Ontology Based System Enhanced with Relationships for Vocabulary hEterogeneity Resolution.
AIMS (1991 - 1994)	Advanced Information Management System: BITUB (Basque Interface to Translate Using BACK) MAGIC (MApping Generator InterfaCe)

OBSERVER (1995-1998)	Ontology Based System Enhanced with Relationships for Vocabulary hEterogeneity Resolution.
AIMS (1991 - 1994)	Advanced Information Management System: BITUB (Basque Interface to Translate Using BACK) MAGIC (MApping Generator InterfaCe)

FUNDING PROJECTS

Título del proyecto: Prêt-à-LLOD - Ready-to-use Multilingual Linked Language Data for Knowledge Services across Sectors
Entidades participantes: National University of Ireland Galway (Ireland), Universidad Politécnica de Madrid (Spain), Universidad de Zaragoza (Spain), Goethe Universität Frankfurt (Germany), University of Bielefeld (Germany), DFKI (Germany), Semantic Web Company (Austria), Semalytix (Germany), Oxford University Press (United Kingdom), Derilinx (Ireland)
Duración, desde 01-01-2019 hasta: 31-12-2021 (3 años)
Investigador principal: IP1: Jorge Gracia (IP nodo Univ. Zaragoza), John McCrae (Project coordinator, National University of Ireland) Galway (Ireland))
Número de investigadores participantes: >40
Importe total: 2.997.181€
Importe nodo Univ. Zaragoza: 195.000€

Objetivos: The main aim of this project is to promote synergies across Europe between linguists, computer scientists, terminologists, and other stakeholders in industry and society, in order to investigate and extend the area of linguistic data science. Funded by COST.

Título del proyecto: Nexuslinguarum

Objetivos: In this project we aim to increase the uptake of language technologies by exploiting the combination of linked data and language technologies, that is Linguistic Linked Open Data (LLOD), to create ready-to-use multilingual data. Prêt-à-LLOD aims to achieve this by creating a new methodology for building data value chains applicable to a wide-range of sectors and applications and based around language resources and language technologies that can be integrated by means of semantic technologies, in particular the usage of Linguistic Linked Open Data (LLOD).

Título del proyecto: Lynx

Objetivos: he main objective of Lynx is to create an ecosystem of smart cloud services to better manage compliance, based on a legal knowledge graph (LKG) which integrates and links heterogeneous compliance data sources including legislation, case law, standards and other private contracts.