Javascript must be enabled to continue!
Adding Meta Data to Documents for E-Learning: A Tool Evaluation
View through CrossRef
Adding Meta Data to Documents for E-Learning: A Tool Evaluation
doi: 10.52987/edc.2025.003
Harald Wahl
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
wahl@technikum-wien.at
Alexander Mense
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Martin Niederwieser
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Sonja Vollnhofer
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Shveta Sohal
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Sebastian Schwarz Mense
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
ABSTRACT
Modern Web 3.0 learning environments require a solution for making all related documents,
which may be stored and accessible through various systems, findable in a semantic way.
This paper deals with the requirements of such a solution, which are based on a project from
the University of Applied Sciences Technikum Wien and evaluates which of the existing
software solutions on the market meets the needs, while only ready-to-use software and
components are considered. Features and functionalities of four software solutions (Microsoft
SharePoint, W3C Annotea, Ontopia Knowledge Suite and Caringo CAStor) are compared
with the requirements. Possible usage scenarios provide hints and general thoughts for
putting the project’s concept into practice. An evaluation of all the software solutions
considered shows clearly the advantages and disadvantages of them. It turns out that no
considered software solution meets the needs perfectly, but this paper illustrates the best
usage for e-learning purposes.
KEYWORDS: E-learning, Topic maps, Annotation, Semantic technologies
Tomorrow People Organization
Title: Adding Meta Data to Documents for E-Learning: A Tool Evaluation
Description:
Adding Meta Data to Documents for E-Learning: A Tool Evaluation
doi: 10.
52987/edc.
2025.
003
Harald Wahl
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
wahl@technikum-wien.
at
Alexander Mense
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Martin Niederwieser
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Sonja Vollnhofer
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Shveta Sohal
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
Sebastian Schwarz Mense
University of Applied Sciences Technikum Wien
Hoechstaedtplatz 6, 1200 Vienna, Austria
ABSTRACT
Modern Web 3.
0 learning environments require a solution for making all related documents,
which may be stored and accessible through various systems, findable in a semantic way.
This paper deals with the requirements of such a solution, which are based on a project from
the University of Applied Sciences Technikum Wien and evaluates which of the existing
software solutions on the market meets the needs, while only ready-to-use software and
components are considered.
Features and functionalities of four software solutions (Microsoft
SharePoint, W3C Annotea, Ontopia Knowledge Suite and Caringo CAStor) are compared
with the requirements.
Possible usage scenarios provide hints and general thoughts for
putting the project’s concept into practice.
An evaluation of all the software solutions
considered shows clearly the advantages and disadvantages of them.
It turns out that no
considered software solution meets the needs perfectly, but this paper illustrates the best
usage for e-learning purposes.
KEYWORDS: E-learning, Topic maps, Annotation, Semantic technologies.
Related Results
Optimising tool wear and workpiece condition monitoring via cyber-physical systems for smart manufacturing
Optimising tool wear and workpiece condition monitoring via cyber-physical systems for smart manufacturing
Smart manufacturing has been developed since the introduction of Industry 4.0. It consists of resource sharing and networking, predictive engineering, and material and data analyti...
CREATING LEARNING MEDIA IN TEACHING ENGLISH AT SMP MUHAMMADIYAH 2 PAGELARAN ACADEMIC YEAR 2020/2021
CREATING LEARNING MEDIA IN TEACHING ENGLISH AT SMP MUHAMMADIYAH 2 PAGELARAN ACADEMIC YEAR 2020/2021
The pandemic Covid-19 currently demands teachers to be able to use technology in teaching and learning process. But in reality there are still many teachers who have not been able ...
Non-Recommended Publishing Lists: Strategies for Detecting Deceitful Journals
Non-Recommended Publishing Lists: Strategies for Detecting Deceitful Journals
Abstract
The rapid growth of open access publishing (OAP) has significantly improved the accessibility and dissemination of scientific knowledge. However, this expansion has also c...
Small Cell Lung Cancer and Tarlatamab: A Meta-Analysis of Clinical Trials
Small Cell Lung Cancer and Tarlatamab: A Meta-Analysis of Clinical Trials
Abstract
Introduction
Tarlatamab is a Delta-like ligand 3 (DLL3) -directed bispecific T-cell engager recently approved for use in patients with advanced small cell lung cancer (SCL...
Meta-Representations as Representations of Processes
Meta-Representations as Representations of Processes
In this study, we explore how the notion of meta-representations in Higher-Order Theories (HOT) of consciousness can be implemented in computational models. HOT suggests that consc...
Meta-Learning Based Classification Model for Cardiovascular Disease (Preprint)
Meta-Learning Based Classification Model for Cardiovascular Disease (Preprint)
BACKGROUND
Cardiovascular disease is a significant global health concern, being the leading cause of death and disability worldwide. The World Health Organi...
Selection of Injectable Drug Product Composition using Machine Learning Models (Preprint)
Selection of Injectable Drug Product Composition using Machine Learning Models (Preprint)
BACKGROUND
As of July 2020, a Web of Science search of “machine learning (ML)” nested within the search of “pharmacokinetics or pharmacodynamics” yielded over 100...
Structuration sématique de documents XML centres-documents
Structuration sématique de documents XML centres-documents
La numérisation des documents et le développement des technologies Internet ont engendré une augmentation permanente du nombre de documents et de types de documents disponibles. Fa...

