Open Data for Education

Linked, Shared, and Reusable Data for Teaching and Learning

  • Dmitry Mouromtsev
  • Mathieu d’Aquin

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9500)

Also part of the Information Systems and Applications, incl. Internet/Web, and HCI book sub series (LNISA, volume 9500)

Table of contents

  1. Front Matter
    Pages I-VII
  2. State of Open and Linked Data for Education

    1. Front Matter
      Pages 1-1
    2. Davide Taibi, Giovanni Fulantelli, Stefan Dietze, Besnik Fetahu
      Pages 16-37
  3. Applications of Open and Linked Data in Education

    1. Front Matter
      Pages 39-39
    2. Vladimir Vasiliev, Fedor Kozlov, Dmitry Mouromtsev, Sergey Stafeev, Olga Parkhimovich
      Pages 41-66
  4. Teaching (with) Open and Linked Data

    1. Front Matter
      Pages 133-133
    2. Alexander Mikroyannidis, John Domingue, Maria Maleshkova, Barry Norton, Elena Simperl
      Pages 135-152
    3. Irina Radchenko, Anna Sakoyan
      Pages 153-165
  5. Back Matter
    Pages 189-189

About this book


This volume comprises a collection of papers presented at an Open Data in Education Seminar and the LILE workshops during 2014-2015.

In the first part of the book, two chapters give different perspectives on the current use of linked and open data in education, including the use of technology and the topics that are being covered.

The second part of the book focuses on the specific, practical applications that are being put in place to exploit open and linked data in education today.

The goal of this book is to provide a snapshot of current activities, and to share and disseminate the growing collective experience on open and linked data in education. This volume brings together research results, studies, and practical endeavors from initiatives spread across several countries around the world. These initiatives are laying the foundations of open and linked data in the education movement and leading the way through innovative applications.


big data ebooks educational content linked open data semantic Web analysis collaborative authoring community data science education educational ontology population learning linked data linked data for education linked learning massive open online courses open data open education open educational resources terminology extraction

Editors and affiliations

  • Dmitry Mouromtsev
    • 1
  • Mathieu d’Aquin
    • 2
  1. 1.ITMO UniversitySt. PetersburgRussia
  2. 2.Knowledge Media InstituteMilton KeynesUnited Kingdom

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science Computer Science (R0)
  • Print ISBN 978-3-319-30492-2
  • Online ISBN 978-3-319-30493-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
Industry Sectors
Chemical Manufacturing
IT & Software
Consumer Packaged Goods
Finance, Business & Banking
Energy, Utilities & Environment