EduWebofData 2016 : Educational Applications on the Web of Data
Call For Papers
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Call for Papers
Telematics & Informatics
ISSN: ISSN: 0736-5853
2014 ISI Impact Factor: 1.120
Special Issue on
Educational Applications on the Web of Data: New trends and perspectives
Education has become a key component of any society since it is the means by which humanity functions and governs itself. It allows individuals to appropriately integrate and progress into a given community. For this reason, new ways of interaction between students and educational contents are emerging in order to improve the quality of education. From this perspective, information technologies are playing an increasingly crucial role in the delivery of digital education, which in turn is driving research into finding ever better technological solutions. The emergence of the Web of Data and its gradual adoption in learning or education-related settings has led to the creation of an embryonic “Web of Educational Data,” including institutional data from universities, as well as Linked Data about publicly available educational resources. However, while the very nature of the Linked Data approach offers promising solutions that can potentially transform education and learning, adoption and take-up is still hindered by issues which are both technical as well interdisciplinary. In this context, semantic-based technologies have emerged to afford a common and standard data model that eases the interoperability, integration, sharing and monitoring of knowledge-based systems. Furthermore, the Linked Data initiative as practical view of the Semantic Web has posed the baseline technology to easily integrate, exchange, enrich and consume data in a distributed/federated system.
In the education domain, knowledge management is becoming critical. From official education resources such as the ones available in Massive Open Online Courses (MOOC) platforms to those available on the web (blog posts, wiki, social network posts, web pages, digital newspaper, etc.), there is an increasing need of organizing, linking, discovering, evaluating, searching and suggesting educational contents. Moreover and due to this huge amount of information resources, it seems clear the need of establishing levels of confidence, trust and quality on such contents.
In the light of elevating the meaning of educational resources, semantic technologies are considered a cornerstone to provide a new user-centric and smart environment for Linked Data Education. Ontology models and standards for educational data, visual tools, career plans, curriculum preparation, searching and recommending systems, expertise ranking or e-Learning analytics techniques are examples of services that aim to improve and enhance existing e-Learning platforms through semantics and Linked Data.
Taking into account the emerging necessity of an intelligent and self-aware environment to manage educational resources and the need of providing user-centric educational services, this special issue aims to discuss the main approaches for semantic-based knowledge management in the context of e-Learning, as well as the principal methods, techniques and standards for leveraging Linked Data as a key-driver of the new Digital and Linked Education ecosystem.
The aim of this Special Issue is to investigate trends among innovative and high-quality research regarding the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models applying new perspectives for developing educational applications on the Web of Data.
The list of topics includes, but is not limited to:
-Access, navigation and (live) consumption of educational resources in the Web of Data
-Automatic learning paths using semantic technologies
-Collaborative and continuous learning based on Linked Data
-Social and smart environments for learning processes
-Novel user-interaction techniques to manage and consume educational resources through Linked Data
-Informal learning and Linked Data
-(Visual) learning analytics and educational data mining based on Linked Data
-Advanced techniques and architectures to understand students behavior and educational resources: deep learning, sentiment analysis, opinion mining, etc.
-Personalized educational resources based on Linked Data
-Education and Learner Knowledge Graphs
-Data-driven organizational learning and learning organizations
-Legal, ethical and economic aspects of Linked Data in science and education
-Open Science and Open Access publishing based Linked Data: vocabularies and ontologies
-Provenance, trust and quality of on-line educational resources
-Massive Open On-line Courses: discovery, search, recommendation and trustworthiness based on Linked Data
-Case studies on implementing Linked (Open) Data in education
-Algorithms and techniques to discover, search and recommend educational resources based on Linked Data
-Publishing and tagging educational resources in the Web of Data: vocabularies and ontologies
-Use of standard vocabularies for science and education in the Web of Data
-Reconciliation, mapping and alignment of educational resources
-Novel data-driven architectures to integrate and offer open educational resources
-Integration and interoperability of educational resources through Linked Data
-Abstract submission deadline (1 page): July 1, 2016
-Manuscript submission deadline: September 1, 2016
-Notification of Review: November 15, 2016
-Revision due: January 15, 2017
-Notification of Final Acceptance: March 15, 2017
-Expected Publication of the Special Issue: 2017
All submissions have to be prepared according to the Guide for Authors as published in the Journal website at http://www.journals.elsevier.com/telematics-and-informatics/ . Authors should select “SI: EduWebofData”, from the “Choose Article Type” pull-down menu during the submission process. All contributions must not have been previously published or be under consideration for publication elsewhere. A submission based on one or more papers that appeared elsewhere has to comprise major value-added extensions over what appeared previously (at least 50% new material). Authors are requested to attach to the submitted paper their relevant, previously published articles and a summary document explaining the enhancements made in the journal version.
All submitted papers will undergo a rigorous peer-review process that will consider programmatic relevance, scientific quality, significance, originality, style and clarity.
The acceptance process will focus on papers that address original scientific contributions in the form of theoretical and experimental research and case studies applying new perspectives for developing educational applications on the Web of Data.
Giner Alor-Hernández, Division of Research and Postgraduate Studies, Instituto Tecnológico de Orizaba, Oriente 9 #852 Emiliano Zapata, Orizaba, Veracruz, México. Email: firstname.lastname@example.org
Jose María Alvarez-Rodríguez, Department of Engineering and Computer Science. Carlos III University of Madrid, Avd. De la Universidad, 30, 28911, Leganés, Spain. Email: email@example.com