Introduction to a Web of Linked Data
Ref. 41013
- Effort: 12 hours
- Pace: Self paced
This MOOC introduces the Linked Data standards and principles that provide the foundation of the Semantic Web.
- Enrollment
- From April 20, 2022 to Dec. 31, 2022
- Course
- From April 20, 2022 to Dec. 31, 2022
- Languages
- English
What you will learn
At the end of this course, you will be able to:
- understand the principles of a Web of Linked Data
- publish linked data with RDF standard
- access data sources on the web with SPARQL query language
- exchange and integrate RDF data with other data and format sources
Description
Among its many evolutions, the Web became a way to exchange data between applications. Everyday we consume and produce these data through a growing variety of applications running on a growing variety of devices. This major evolution of the Web has applications in all domains of activity.
This MOOC introduces the Linked Data standards and principles that provide the foundation of the Semantic web. We divided this introduction into four parts:
- the fundamental principles of linked data on the Web
- the RDF recommendation that provides a standard data model and syntaxes to publish and link data on the Web
- an overview of the SPARQL query language that allows us to access data sources on the Web
- the standards supporting the exchange and integration of RDF data with other formats and data sources (R2RML, CSVW, JSON-LD, RDFa, GRDDL, LDP).
Each week alternates short videos and quizzes, as well as supplementary resources, to gradually progress through the different principles and standards.
Format
This course was initially designed and released in a 4-week format with the course content being accessible week after week and a workload of about 3 hours a week. Each week is divided into 5 to 7 sequences. Each sequence generally includes one short video with subtitles and the transcript available for download, one quiz related to the contents + some additionnal references and resources
At the end of each week, you will also find a PDF file of the slides displayed in the videos and some demos. Several end-of-week exercises allowing you to practice what has been presented in the different sequences of the week.
Prerequisites
Participants need to be acquainted with basic Web notions (e.g. browser) and be able to install software on their machine.
Assessment and certification
Students' work in the course is assessed through quizzes between each video and exercises at the end of every week. A certificate will be issued by FUN, confirming successful completion of the Mooc.
Course plan
- Week 1 : Principles of a Web of Linked Data
- Week 2 : The RDF Data Model
- Week 3 : SPARQL Query Language
- Week 4 : Integration with Other Data Formats and Sources
Course team
Fabien Gandon
Categories
Fabien GANDON est délégué scientifique adjoint d'Inria Sophia Antipolis, directeur de Recherche et responsable de l'équipe Wimmics (Inria, I3S, CNRS, UCA) qui étudie des modèles et algorithmes pour concilier le Web social et le Web sémantique.
Olivier Corby
Categories
Olivier CORBY est docteur en informatique (UNS), chercheur INRIA dans l'équipe Wimmics (INRIA, I3S, CNRS, UNS), il enseigne à Polytech Nice.Olivier CORBY est docteur en informatique (UNS), chercheur INRIA dans l'équipe Wimmics (INRIA, I3S, CNRS, UNS), il enseigne à Polytech Nice.Olivier CORBY est docteur en informatique (UNS), chercheur INRIA dans l'équipe Wimmics (INRIA, I3S, CNRS, UNS), il enseigne à Polytech Nice.
Catherine Faron Zucker
Categories
Catherine FARON ZUCKER est maître de conférence à l’Université Côte d'Azur, responsable de la filière Web Science de l’école d’ingénieurs Polytech Nice Sophia et du Master 2 IFI de l’UCA et responsable adjointe de l’équipe de recherche Wimmics (Inria, I3S, CNRS, UCA).
Organizations
License
License for the course content
Attribution-NonCommercial-NoDerivatives
You are free to:
- Share — copy and redistribute the material in any medium or format
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.
License for the content created by course participants
Attribution-NonCommercial-NoDerivatives
You are free to:
- Share — copy and redistribute the material in any medium or format
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- NonCommercial — You may not use the material for commercial purposes.
- NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.