Supporting Semantics-aware Analysis in Linked Open Data-enabled Information Systems

Résultats de recherche: Contribution à un événement scientifique (non publié)ArticleRevue par des pairs


In recent years, open data is becoming an important trend, especially in government data context (i.e., Open Government Data), since it offers citizens and public institutions a transparent, free and customized access to such information as well as more public services and commercial re-use [1, 2].Open Government Data (OGD) may contain multiple datasets, including budget and spending, population, census, geographical, parliament minutes, etc. It also includes data that is indirectly ‘’owned’’ by public administrations (e.g. through subsidiaries or agencies), such as data related to climate/pollution, public transportation, congestion/traffic, child care/education. These data are considered as a lever to achieve: (i) more transparency in decision-making, (ii) increased collaboration of citizens and organizations in government policies, and (iii) innovation leading to a public and private value [3].Hence, the appearance of Linked Open Data (LOD) that refers to data, which is published on the Web for use by public administrations, business and citizens. Such data apart from being machine-readable, is also linked to other external datasets. LOD is the process of following a set of best practices for publishing and connecting structured data on the
langue originaleAnglais
Etat de la publicationPublié - 15 nov. 2019
EvénementGrascomp Doctoral Day 2019 - Université de Namur (Faculté d'informatique), Namur, Belgique
Durée: 22 nov. 201922 nov. 2019


ColloqueGrascomp Doctoral Day 2019
La villeNamur
Adresse Internet


  • Open Source, Open Data

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