Navigating among Educational Resources in the Web of Linked Data

2014 ◽  
pp. 185-190
Author(s):  
Dimitrios A. Koutsomitropoulos ◽  
Georgia D. Solomou ◽  
Aikaterini K. Kalou
Keyword(s):  
Linked Data ◽  
Educational Resources ◽  
The Web

scholarly journals Linking Educational Resources on Data Science

2019 ◽  
Vol 33 ◽  
pp. 9404-9409
Author(s):  
José Luis Ambite ◽  
Jonathan Gordon ◽  
Lily Fierro ◽  
Gully Burns ◽  
Joel Mathew
Keyword(s):  
Big Data ◽  
Linked Data ◽  
Data Science ◽  
Resource Discovery ◽  
Educational Resources ◽  
Machine Learning Techniques ◽  
Biomedical Data ◽  
Centers Of Excellence ◽  
Training Resources ◽  
The Web

The availability of massive datasets in genetics, neuroimaging, mobile health, and other subfields of biology and medicine promises new insights but also poses significant challenges. To realize the potential of big data in biomedicine, the National Institutes of Health launched the Big Data to Knowledge (BD2K) initiative, funding several centers of excellence in biomedical data analysis and a Training Coordinating Center (TCC) tasked with facilitating online and inperson training of biomedical researchers in data science. A major initiative of the BD2K TCC is to automatically identify, describe, and organize data science training resources available on the Web and provide personalized training paths for users. In this paper, we describe the construction of ERuDIte, the Educational Resource Discovery Index for Data Science, and its release as linked data. ERuDIte contains over 11,000 training resources including courses, video tutorials, conference talks, and other materials. The metadata for these resources is described uniformly using Schema.org. We use machine learning techniques to tag each resource with concepts from the Data Science Education Ontology, which we developed to further describe resource content. Finally, we map references to people and organizations in learning resources to entities in DBpedia, DBLP, and ORCID, embedding our collection in the web of linked data. We hope that ERuDIte will provide a framework to foster open linked educational resources on the Web.

scholarly journals Specifying and Executing User Agents in an Environment of Reasoning and RESTful Systems Using the Guard-Stage-Milestone Approach

2021 ◽  
Author(s):  
Tobias Käfer ◽  
Benjamin Jochum ◽  
Nico Aßfalg ◽  
Leonard Nürnberg
Keyword(s):  
Linked Data ◽  
Operational Semantics ◽  
Workflow Management ◽  
Management Systems ◽  
Workflow Management Systems ◽  
The Web

AbstractFor Read-Write Linked Data, an environment of reasoning and RESTful interaction, we investigate the use of the Guard-Stage-Milestone approach for specifying and executing user agents. We present an ontology to specify user agents. Moreover, we give operational semantics to the ontology in a rule language that allows for executing user agents on Read-Write Linked Data. We evaluate our approach formally and regarding performance. Our work shows that despite different assumptions of this environment in contrast to the traditional environment of workflow management systems, the Guard-Stage-Milestone approach can be transferred and successfully applied on the web of Read-Write Linked Data.

Introductory AI educational resources on the web

intelligence ◽  
2001 ◽  
Vol 12 (4) ◽  
pp. 15-17
Author(s):  
Robert St. Amant ◽  
R. Michael Young
Keyword(s):  
Educational Resources ◽  
The Web

How to consume linked data on the web

2010 ◽  
Author(s):  
Olaf Hartig ◽  
Juan Sequeda ◽  
Jamie Taylor ◽  
Patrick Sinclair
Keyword(s):  
Linked Data ◽  
The Web

scholarly journals The read–write Linked Data Web

2013 ◽  
Vol 371 (1987) ◽  
pp. 20120513 ◽  
Author(s):  
Tim Berners-Lee ◽  
Kieron O’Hara
Keyword(s):  
Future Development ◽  
Linked Data ◽  
Open Data ◽  
Linked Open Data ◽  
The Future ◽  
The Web

This paper discusses issues that will affect the future development of the Web, either increasing its power and utility, or alternatively suppressing its development. It argues for the importance of the continued development of the Linked Data Web, and describes the use of linked open data as an important component of that. Second, the paper defends the Web as a read–write medium, and goes on to consider how the read–write Linked Data Web could be achieved.

scholarly journals Use of Linked Data principles for semantic management of scanned documents

2016 ◽  
Vol 28 (2) ◽  
pp. 241-251 ◽  
Author(s):  
Luciane Lena Pessanha Monteiro ◽  
Mark Douglas de Azevedo Jacyntho
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Web Application ◽  
Linked Data ◽  
World Wide ◽  
Decision Making Process ◽  
Whole Process ◽  
The World ◽  
Scanned Documents ◽  
The Web

The study addresses the use of the Semantic Web and Linked Data principles proposed by the World Wide Web Consortium for the development of Web application for semantic management of scanned documents. The main goal is to record scanned documents describing them in a way the machine is able to understand and process them, filtering content and assisting us in searching for such documents when a decision-making process is in course. To this end, machine-understandable metadata, created through the use of reference Linked Data ontologies, are associated to documents, creating a knowledge base. To further enrich the process, (semi)automatic mashup of these metadata with data from the new Web of Linked Data is carried out, considerably increasing the scope of the knowledge base and enabling to extract new data related to the content of stored documents from the Web and combine them, without the user making any effort or perceiving the complexity of the whole process.

scholarly journals A bibliometric mapping of open educational resources

2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Airton Zancanaro ◽  
José Leomar Todesco ◽  
Fernando Ramos
Keyword(s):  
Educational System ◽  
Web Of Science ◽  
Scientific Production ◽  
Open Educational Resources ◽  
Educational Resources ◽  
System Quality ◽  
Face To Face ◽  
Scientific Databases ◽  
Number Of Publications ◽  
The Web

Open educational resources (OER) is a topic that has aroused increasing interest by researchers as a powerful contribution to improve the educational system quality and openness, both in face to face and distance education. The goal of this research is to map publications related to OER, dating from 2002 to 2013, and available through the Web of Science and Scopus scientific databases as well as in the OER Knowledge Cloud open repository. Data were used to explore relevant aspects related to the scientific production in OER, such as: (i) number of publications per year; (ii) most cited publications; (iii) authors with higher number of publications; (iv) institutions and countries with more publications and (v) most referenced bibliography by the authors. The analysis has included 544 papers, written by 843 authors, from 338 institutions, from 61 different countries. Moreover, the analysis has included the publications referenced and the author’s keywords, considering 6,355 different publications and 929 different keywords. Besides presenting a bibliographic mapping of the research on OER, this paper also intends to contribute to consolidate the idea that OER is a promising field for researchers, in line with the spreading of the Open movement.

scholarly journals Linked Data in a Nutshell: A Starter Kit of Selected Annotated Bibliography and Resources for Academic Librarians: Part One

2018 ◽  
Vol 3 (1) ◽  
pp. 36
Author(s):  
Weiling Liu
Keyword(s):  
Information Retrieval ◽  
Case Studies ◽  
Linked Data ◽  
Annotated Bibliography ◽  
Academic Librarians ◽  
English Only ◽  
Current State ◽  
The Many ◽  
Data Evolution ◽  
The Web

It has been a decade since Tim Berners-Lee coined Linked Data in 2006. More and more Linked Data datasets have been made available for information retrieval on the Web.  It is essential for librarians, especially academic librarians, to keep up with the state of Linked Data.  There is so much information about Linked Data that one may wonder where to begin when they want to join the Linked Data community. With this in mind, the author compiled this annotated bibliography as a starter kit.  Due to the many resources available, this list focuses on literature in English only and of specific projects, case studies, research studies, and tools that may be helpful to academic librarians, in addition to the overview of Linked Data concept and the current state of Linked Data evolution and adoption.

scholarly journals TAXREF-LD: A Reference Thesaurus for Biodiversity on the Web of Linked Data

2017 ◽  
Vol 1 ◽  
pp. e20232
Author(s):  
Franck Michel ◽  
Catherine Faron-Zucker ◽  
Sandrine Tercerie ◽  
Gargominy Olivier
Keyword(s):  
Linked Data ◽  
The Web

scholarly journals Improving the Quality of Linked Data Using Statistical Distributions

2018 ◽  
pp. 1638-1664 ◽  
Author(s):  
Heiko Paulheim ◽  
Christian Bizer
Keyword(s):  
Knowledge Base ◽  
Linked Data ◽  
Relational Databases ◽  
Knowledge Bases ◽  
Structured Data ◽  
Data Sources ◽  
Data Sets ◽  
Statistical Distributions ◽  
The Web

Linked Data on the Web is either created from structured data sources (such as relational databases), from semi-structured sources (such as Wikipedia), or from unstructured sources (such as text). In the latter two cases, the generated Linked Data will likely be noisy and incomplete. In this paper, we present two algorithms that exploit statistical distributions of properties and types for enhancing the quality of incomplete and noisy Linked Data sets: SDType adds missing type statements, and SDValidate identifies faulty statements. Neither of the algorithms uses external knowledge, i.e., they operate only on the data itself. We evaluate the algorithms on the DBpedia and NELL knowledge bases, showing that they are both accurate as well as scalable. Both algorithms have been used for building the DBpedia 3.9 release: With SDType, 3.4 million missing type statements have been added, while using SDValidate, 13,000 erroneous RDF statements have been removed from the knowledge base.

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