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3 - Managing linked open data across discovery systems

Published online by Cambridge University Press:  08 June 2018

Ali Shiri
Affiliation:
University of Alberta, Edmonton
Danoosh Davoodi
Affiliation:
University of Alberta
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Summary

Introduction

This chapter examines and explores linked open data in the context of the current digital data landscape, drawing on recent developments associated with digital data: big data, research data, open data and web of data. A specific goal of this chapter is to draw attention to the importance of the ways in which linked open data can provide libraries with opportunities to enhance the findability of their data and information resources, and to support seamless and unified access in heterogeneous content repositories, such as digital libraries and integrated discovery systems. The first part of the chapter addresses the key concepts of big data, research data, the Semantic Web and open data. The second part of the chapter focuses on the definition and importance of linked data and its current applications in various settings. Specific examples of libraries and major projects associated with using and implementing linked open data are briefly reviewed. BIBFRAME is reviewed as a popular framework to support the transformation of library data into linked open data. An overview of publishing linked data is presented, along with a reference to useful resources for publishing, browsing and linking linked open data tools.

Big data

The vast volume, variety and complexity of digital data available on the web has resulted in the emergence of what is called ‘big data’. Digital libraries, search engines, social media sites, cloudbased computing infrastructures, as well as virtual collaboratories, e-science, e-humanities and e-social-science projects produce massive volumes of data that call for proper management and preservation planning approaches and strategies in order to provide users with effective and efficient data access. Many terms used in the literature refer to, or are associated with, the phenomenon of big data, including ‘digital data’, ‘research data’, ‘linked data’, ‘open data’, ‘web of data’ and ‘data repositories’ (Borgman, 2012; Hodson, 2012; Lyon, 2007; National Science Foundation, 2012). The availability and discourse of these data types presents new research and development opportunities as well as challenges. To provide a coherent and contextualized understanding of big data, one approach would be to place big data in the context of digital libraries, as the latter have been well researched and share a number of similarities with big data.

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Publisher: Facet
Print publication year: 2016

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