Semantic annotation and harvesting of federated scholarly data using ontologies

DOIhttps://doi.org/10.1108/DLP-12-2018-0038
Published date11 November 2019
Pages157-171
Date11 November 2019
AuthorDimitrios A. Koutsomitropoulos
Subject MatterLibrary & information science,Librarianship/library management,Library technology,Records management & preservation,Information repositories
Semantic annotation and
harvesting of federated
scholarly data using ontologies
Dimitrios A. Koutsomitropoulos
High Performance Information Systems Laboratory (HPCLab),
Department of Computer Engineering and Informatics, School of Engineering,
University of Patras, Patras-Rio, Greece
Abstract
Purpose Effective synthesis of learning material is a multidimensional problem, which often relies on
handpickingapproaches and human expertise. Sources of educationalcontent exist in a variety of forms, each
offering proprietarymetadata information and search facilities. This paper aims to show that it is possible to
harvest scholarly resources from various repositories of open educational resources (OERs) in a federated
manner. In addition, their subject can be automatically annotated using ontology inference and standard
thematicterminologies.
Design/methodology/approach Based on a semantic interpretation of their metadata, authors can
align external collections and maintain them in a shared knowledge pool known as the Learning Object
Ontology Repository (LOOR).The author leverages the LOOR and show that it is possible to search through
various educational repositoriesmetadata and amalgamate their semantics into a common learningobject
(LO) ontology. The author then proceeds with automatic subject classication of LOs using keyword
expansionand referencing standard taxonomic vocabulariesfor thematic classication,expressed in SKOS.
Findings The approach for automatic subject classication simply takes advantage of the implicit information
in the searching and selection process and combines them with expert knowledge in the domain of reference
(SKOS thesauri). This is shown to improve recall by a considerable factor, while precision remains unaffected.
Originality/value To the best of the authors knowledge, the idea of subject classication of LOs
through the reuse of search queryterms combined with SKOS-based matching and expansion has notbeen
investigatedbefore in a federated scholarly setting.
Keywords Thesauri, Open educational repositories, Ontologies, Learning objects,
Subject classication, Keywords expansion
Paper type Research paper
1. Introduction
Todays libraries and institutions are striving to repurpose their role from centralized
information providers to curators and mediators of educational content. The ination of
open courses and the Massive Online Open Courses (MOOCs)trend are tantalizing business-
model seekers lookingfor monetization (Kerres and Heinen, 2015).
Yet, there is still a lot of potential in edu cational content providers, including OER repositories
and aggregators worldwide, that can form the gold-standardof reference for digital learning-
object consumers. For this kind of applications, we see three major standing problems:
Content searching and reuse requires careful and elaborate selection, more often
than not backed by a manual process.
As rich as the objects metadata may be, there is still a considerable semantic gap
between annotations originating from different sources.
Semantic
annotation of
federated
scholarly data
157
Received9 December 2018
Revised7 April 2019
Accepted28 July 2019
DigitalLibrary Perspectives
Vol.35 No. 3/4, 2019
pp. 157-171
© Emerald Publishing Limited
2059-5816
DOI 10.1108/DLP-12-2018-0038
The current issue and full text archive of this journal is available on Emerald Insight at:
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