Exploring the Role of Academic Social Networking Sites Amongst LIS Professionals: A Meta-Narrative Review

Academic Social Networking Sites (ASNS) has revolutionized the concept of knowledge sharing and publication pattern in academia. It offers a new paradigm to interrelate research scientists globally, influencing research communities\u27 structure and crescendos (dynamics). This changing trend has attracted considerable attention in the research domain and the consequent impact on library & information science professionals. Due to the high operationalizing ability of these networking sites, it provides online services of collaboration and knowledge sharing. The present study reviewed 23 studies from the past that highlights the methodologies, usage pattern of ASNs, impact on professionals, different categories of services, and issues related to academics and social networking in a researcher\u27s life. This study has implemented the ICA framework, a way forward to conduct meta-analysis studies in LIS, using the two most prominent citation and indexing databases, i.e., \u27Scopus\u27 and \u27Web of Science\u27. Moreover, this systematic review formulated four main research categories: Usage, Impact, Services, and Issues related to the ASNS. On further analysis of these four main research categories, eleven sub-categories evolved across four main categories. Finally, at the end of the study, specific suggestions and recommendations are provided for future studies

The NASA Astrophysics Data System: Architecture

The powerful discovery capabilities available in the ADS bibliographic services are possible thanks to the design of a flexible search and retrieval system based on a relational database model. Bibliographic records are stored as a corpus of structured documents containing fielded data and metadata, while discipline-specific knowledge is segregated in a set of files independent of the bibliographic data itself. The creation and management of links to both internal and external resources associated with each bibliography in the database is made possible by representing them as a set of document properties and their attributes. To improve global access to the ADS data holdings, a number of mirror sites have been created by cloning the database contents and software on a variety of hardware and software platforms. The procedures used to create and manage the database and its mirrors have been written as a set of scripts that can be run in either an interactive or unsupervised fashion. The ADS can be accessed at http://adswww.harvard.eduComment: 25 pages, 8 figures, 3 table

Legal Information and the Development of American Law: Writings on the Form and Structure of the Published Law

Robert C. Berring\u27s writings about the impacts of electronic databases, the Internet, and other communications technologies on legal research and practice are an essential part of a larger literature that explores the ways in which the forms and structures of published legal information have influenced how American lawyers think about the law. This paper reviews Berring\u27s writings, along with those of other writers concerned with these questions, focusing on the implications of Berring\u27s idea that in the late nineteenth century American legal publishers created a conceptual universe of thinkable thoughts through which U.S. lawyers came to view the law. It concludes that, spurred by Berring and others, the literature of legal information has become far reaching in scope and interdisciplinary in approach, while the themes struck in Berring\u27s work continue to inform the scholarship of newer writers

Visualizing latent domain knowledge

Knowledge discovery and data mining commonly rely on finding salient patterns of association from a vast amount of data. Traditional citation analysis of scientific literature draws insights from strong citation patterns. Latent domain knowledge, in contrast to the mainstream domain knowledge, often consists of highly relevant but relatively infrequently cited scientific works. Visualizing latent domain knowledge presents a significant challenge to knowledge discovery and quantitative studies of science. We build upon a citation-based knowledge visualization procedure and develop an approach that not only captures knowledge structures from prominent and highly cited works, but also traces latent domain knowledge through low-frequency citation chains. We apply this approach to two cases: (1) identifying cross-domain applications of Pathfinder networks (PFNETs) and (2) clarifying the current status of scientific inquiry of a possible link between Bovine spongiform encephalopathy (BSE), also known as mad cow disease, and a new variant Creutzfeldt-Jakob disease (vCJD), a type of brain disease in human

Library Cataloguing and Role and Reference Grammar for Natural Language processing Applications

Several potential application of natural language processing have proven to be intractable. In this paper, we provide and overview of methods from library cataloguing and linguistics that have not yet been adopted by the natural language processing community and which could be used to help solve some of these problems

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page