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Linked Open Data of Bibliometric Networks : Analytics Research for Personalized Library Services


Overview

Library High Tech seeks original manuscripts for a Special Issue on “Linked Open Data of Bibliometric Networks : Analytics Research for Personalized Library Services, scheduled to appear in mid-2018.

The Integration of smart library services in the urban context is a bold movement towards sustainable and Smart Cities. The capacity of emerging technologies, like Data Mining, Advanced Analytics, Scientometrics, Cognitive Computing and immersive interfaces, to set up flexible, personalized spaces for content, context and community integration enhance the traditional value adding models of Libraries. In our perception, we are entering a new era of collective human wisdom, facilitated by intelligent library services promoting the role of libraries as hubs of collaboration and community enhancement.

Aims and Scope

The Web is emerging as a preferred platform to publish open data and to interlink it together. This is resulting in the Web of Documents to be emerged as Web of Data. The resulting Web of Data is termed as Linked Open Data (LOD) and consists of interlinked open datasets that are being published in different domains such as government, news, health, and geography. Also, the trend of publishing LOD over comes the limitations of publishing data from bounded group of domain specific data access boundaries to global data space. Even though the trend of publishing LOD has got potential in several domains such as government, music, health, but still data from various domains such as digital libraries (and digital documents in general), scientific publications, archives, and scholarly communications still needs to be processed to make it part of global data space. If we consider only scientific publications/documents, the data about these millions of scientific documents that are published by different publishers is either untouched or a very minor fraction of it is added in LOD cloud. The main reason is that data about scientific documents is published as a bounded group of publisher specific templates. The same is true for data contained in digital documents, archives and in scholarly contributions. This opens doors for new methodologies, processes, tools and framework to be developed which can deal with challenges of data extraction, processing, interlinking and publication of data from human to machine understandable format. The goal of this special issue is also to publish such high quality, original research contributions that address challenges in extraction, processing, interlinking and publishing data from different sources, specifically focusing on the data in the digital libraries, scientific publications, archives and scholarly communications jointly are called Bibliometrics Networks

The purpose of the special issue is present state-of-the art approaches to, and examples of, of  Advanced Library systems and components for Smart Cities and Urban Applications.  Manuscripts are sought that address these areas. Novel approaches and sound technological solutions will be expected.

Topics

Topics of interest include, but are not limited to, the following:

  • Crawling different bibliometric data sources, extracting useful data and linking it other open datasets
  • Data extraction algorithms
  • Automated methods, techniques, frameworks for datasets linking
  • Frameworks for extracting and producing LOD data from different data sources
  • Tools and methods for assessing the quality of LOD
  • Business models for using LOD in digital libraries
  • Legal issues in extracting and producing LOD from different public data sources
  • Novel techniques and methods for datasets analysis
  • Techniques for search improvements over LOD
  • Interlinking multilingual datasets
  • Ontologies and information schemas
  • LOD based information systems

Smart Library applications integration in Urban Context

  • Systems and prototypes for Smart Library Services
  • Design development for Analytics in Libraries
  • Sophisticated context aware Library Systems
  • Personalization and Integration
  • Smart Cities Research for Sustainable Development
  • Community Projects for Smart Library Services in Urban Areas and Cities
  • Personalized Library Services and Advanced Analytics including:
  • Social Network Analysis in Publications
  • Automatic Semantic Annotation of Bibliographical Resources
  • Citation Networks 
  • Rising Stars Analysis
  • Research Matching
  • Integration of IoT, Cognitive Computing and Cloud Services
  • Design of context aware, ubiquitous library interfaces

Important Dates

Manuscript submission deadline: November, 28, 2017
Notification of Decision: January, 20, 2018
Submission of final revised paper: March, 10, 2018
Publication of special issue (tentative): Mid 2018

Submission Procedure

Submissions to Library Hi Tech are made using ScholarOne Manuscripts, the online submission and peer review system. Registration and access is available at http://mc.manuscriptcentral.com/lht. Indicate the Special Issue title in your submission.

Guest Editors

Miltiadis D. Lytras, The American College of Greece, Greece (mlytras@acg.edu)
Naif Radi Aljohani, King Abdulaziz University, Saudi Arabia (nraljohani@kau.edu.sa)
Ali Daud, King Abdulaziz University, Saudi Arabia (adfmohamad@kau.edu.sa)
Ahtisham Aslam, King Abdulaziz University, Saudi Arabia (maaslam@kau.edu.sa)
Saeed Ul Hassan, Information Technology University, Pakistan (saeed-ul-hassan@itu.edu.pk)