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The aim of this paper is to present an initiative to apply the principles of Linked Data to enhance the search and discovery of OpenCourseWare (OCW) contents created and shared by the universities.

This paper is a case study of how linked data technologies can be applied for the enhancement of open learning contents.

Results presented under the umbrella of OCW-Universia consortium, as the integration and access to content from different repositories OCW and the development of a query method to access these data, reveal that linked data would offer a solution to filter and select semantically those open educational contents, and automatically are linked to the linked open data cloud.

The new OCW-Universia integration with linked data adds new features to the initial framework including improved query mechanisms and interoperability.

Linked data is a technical standard to structure complex information and relate independent sets of data. Recently, governments have started to use this technology for bridging separated data “(silos)” by launching linked open government data (LOGD) portals. The purpose of this paper is to explore the role of LOGD as a smart technology and strategy to create public value. This is achieved by enhancing the usability and visibility of open data provided by public organizations.

In this study, three different LOGD governance modes are deduced: public agencies could release linked data via a dedicated triple store, via a shared triple store or via an open knowledge base. Each of these modes has different effects on usability and visibility of open data. Selected case studies illustrate the actual use of these three governance modes.

According to this study, LOGD governance modes present a trade-off between retaining control over governmental data and potentially gaining public value by the increased use of open data by citizens.

This study provides recommendations for public sector organizations for the development of their data publishing strategy to balance control, usability and visibility considering also the growing popularity of open knowledge bases such as Wikidata.

These projects aim to improve library services for users in the future by combining Link Open Data (LOD) technology with data visualization. It displays and analyses search results in an intuitive manner. These services are enhanced by integrating various LOD technologies into the authority control system.

The technology known as LOD is used to access, recycle, share, exchange and disseminate information, among other things. The applicability of Linked Data technologies for the development of library information services is evaluated in this study.

Apache Hadoop is used for rapidly storing and processing massive Linked Data data sets. Apache Spark is a free and open-source data processing tool. Hive is a SQL-based data warehouse that enables data scientists to write, read and manage petabytes of data.

The distributed large data storage system Apache HBase does not use SQL. This study’s goal is to search the geographic, authority and bibliographic databases for relevant links found on various websites. When data items are linked together, all of the data bits are linked together as well. The study observed and evaluated the tools and processes and recorded each data item’s URL. As a result, data can be combined across silos, enhanced by third-party data sources and contextualized.

The purpose of this paper is to investigate connected data through the use of open-source technology. It demonstrates the transformation process from library bibliographic data to linked data, which allows for easy searching across numerous collections of information.

In generating this file, a high-level operating system such as Ubuntu, which is based on the LAMP architecture, is used. It is required to use open-source strategies in building the relevant information. LODRefine is being used to convert all of Koha's bibliographic data into linked data that is now available on the Web. This framework has been conceptualized and formulated based on linked data principles and search algorithms accordingly.

Linked data services have been made publicly available to library users by using a variety of different forms of data. Information may be sought quickly and easily using this interface built on numerous search structures. Aside from that, it also meets the needs of users who use the linked data search mechanism to find information. Through modern scripts and algorithms, it is now possible for library users to easily search the linked data enables services.

This paper demonstrates how quickly and easily related data from bibliographic details may be developed and generated using a spreadsheet. The entire procedure culminates in the presence of specialists in the library setting. A further advantage of the SPARQL system is that it allows visitors to group distinct concepts and aspects using independent URIs and URLs instead of the SPARQL endpoint.

The silos of library cataloging data have long been recognized as barriers to the seamless discovery of library resources via the Web and to the interaction of library data with Web data and other uses. In order to better serve users, library cataloging data must be available in a more open environment, and libraries are looking to linked data to present library resources in the data stream of the Web in a way that is seamless to users. This entails changing cataloging formats and tools to Web standards. While there is a lot of discussion and activity around linked data, this chapter approaches the highly technological topic in a way that is geared more toward a general and practical cataloging perspective.

The purpose of this paper is to identify the concepts, component parts and relationships between vocabularies, linked data and knowledge graphs (KGs) from the perspectives of data and knowledge transitions.

This paper uses conceptual analysis methods. This study focuses on distinguishing concepts and analyzing composition and intercorrelations to explore data and knowledge transitions.

Vocabularies are the cornerstone for accurately building understanding of the meaning of data. Vocabularies provide for a data-sharing model and play an important role in supporting the semantic expression of linked data and defining the schema layer; they are also used for entity recognition, alignment and linkage for KGs. KGs, which consist of a schema layer and a data layer, are presented as cubes that organically combine vocabularies, linked data and big data.

This paper first describes the composition of vocabularies, linked data and KGs. More importantly, this paper innovatively analyzes and summarizes the interrelatedness of these factors, which comes from frequent interactions between data and knowledge. The three factors empower each other and can ultimately empower the Semantic Web.

Research in the area of technology‐enhanced learning (TEL) throughout the last decade has largely focused on sharing and reusing educational resources and data. This effort has led to a fragmented landscape of competing metadata schemas, or interface mechanisms. More recently, semantic technologies were taken into account to improve interoperability. The linked data approach has emerged as the de facto standard for sharing data on the web. To this end, it is obvious that the application of linked data principles offers a large potential to solve interoperability issues in the field of TEL. This paper aims to address this issue.

In this paper, approaches are surveyed that are aimed towards a vision of linked education, i.e. education which exploits educational web data. It particularly considers the exploitation of the wealth of already existing TEL data on the web by allowing its exposure as linked data and by taking into account automated enrichment and interlinking techniques to provide rich and well‐interlinked data for the educational domain.

So far web‐scale integration of educational resources is not facilitated, mainly due to the lack of take‐up of shared principles, datasets and schemas. However, linked data principles increasingly are recognized by the TEL community. The paper provides a structured assessment and classification of existing challenges and approaches, serving as potential guideline for researchers and practitioners in the field.

Being one of the first comprehensive surveys on the topic of linked data for education, the paper has the potential to become a widely recognized reference publication in the area.

The paper aims to investigate issues surrounding publishing thesauri as linked data and explores a systematic way for publishing linked open thesauri

Based on the four principles of linked data, a novel approach is proposed to incorporate terminology services with thesauri and provide more descriptive information about thesauri and relating services. A proof-of-concept system was built for demonstrating the approach.

Carefully designed URIs and terminology services are necessary for publishing linked open thesauri. However, there is still a lack of standards for describing linked open thesauri and terminology services. Since it is possible to publish thesauri at the hands of creators and maintainers, distributed thesauri may be a good complement to the traditional registry approach.

Only a simple knowledge organisation system (SKOS) core model is considered in the paper. There may be some adjustment for applying the findings to thesauri using the SKOS extended model and other models.

The paper proposes a more systematic way for publishing linked open thesauri. It is important to consider a linked open thesaurus as a dynamic system rather than a static data dump. In addition, functionality for using thesauri is equally important for publishing thesauri.

This paper aims to describe how linked data technologies can change the digital library collections, what are the benefits of linked data applications in digital libraries and what are the challenges of digital libraries in linked data environment.

The present study is based on substantial literature review on the applications of linked data technologies in digital libraries. The search engines such as Google, Yahoo and Google Scholar were used to find the relevant literature for the study. Online databases such as Pro Quest, Science Direct, Emerald and JSTORE were also used to find the relevant literature of the study. Databases of Library Sciences Library and Information Science and Technology Abstracts and Library Information Science Abstracts were also used to find the relevant literature of the study. Library, linked data technologies, Semantic Web, digital library and digital collections were the main keywords which were used to find the relevant literature for the study.

The evolution of linked data technologies and Semantic Web has changed the traditional role of the libraries. Traditional libraries are converting into digital libraries and digital libraries are in a struggle to publish their resources on the Web using XML-based metadata standards. It has made capable the digital collections to be viewed by machines on the Web just like human. On the emergence of linked data applications in digital libraries, Web visibility of the libraries has been enhanced to provide the opportunities for the users to find their required quality information of libraries round-the-clock on the Web. National Library of France, National Library of Spain, Europeana, Digital Public Library of Americana, Library of Congress and The British Library have taken the initiatives to publish their resources on the Web using linked data technologies.

This study present several key issues for policy makers, software developers, decision makers and library administrators about linked data technologies and its implementations in digital libraries. The present study may play its role to facilitate the users of the Web who are enthusiastically interested to exploit the quality and authentic library resources on the Web round-the-clock. Search engines will also achieve their longstanding goal to exploit the quality resources of the libraries for their Web users to make their Web appearance more credible and trustworthy.

With the progressive trends in Open Data, this paper aims to underscore the significance of Open Linked Statistical Data (OLSD) and identifies the trajectory of development of OLSD besides underlining the prospects and challenges underlying OLSD.

Being exploratory in nature, this viewpoint seeks to present a trajectory of OLSD which seeks to emphasize upon the futuristic trend in the development of OLSD.

Eight stages have been identified in the OLSD trajectory. The opening of more and more data results in new possibilities for combining data and gaining new insights. In the future, data will automatically be opened and streamed and could be used in using OLSD algorithms. Algorithms will mention the shortcomings and limitations of data and help to interpret the data in such a way that the user is in the driver’s seat.

While the paper follows an exploratory approach, there are a couple of implications for the practitioners and academicians. For instance, government may become more accountable with the adoption of advanced OLSD algorithms. Further research on OLSD may be required in appreciating the impact of OLSD in different settings, and this would be helpful in providing novel insights to the concerned stakeholders.

While Big and Open Linked Data (BOLD) has gained prominence in academic research, the focus on OLSD has remained scanty. This paper seeks to underline the futuristic trends in OLSD.