Cloud-Based Big Data Management and Analytics for Scholarly Resources: Current Trends, Challenges and Scope for Future Research

Authors : Samiya Khan, Kashish A. Shakil, Mansaf Alam

With the shifting focus of organizations and governments towards digitization of academic and technical documents, there has been an increasing need to use this reserve of scholarly documents for developing applications that can facilitate and aid in better management of research.

In addition to this, the evolving nature of research problems has made them essentially interdisciplinary. As a result, there is a growing need for scholarly applications like collaborator discovery, expert finding and research recommendation systems.

This research paper reviews the current trends and identifies the challenges existing in the architecture, services and applications of big scholarly data platform with a specific focus on directions for future research.

URL : https://arxiv.org/abs/1606.01808

Big Data Refinement

Author : Eerke A. Boiten

“Big data” has become a major area of research and associated funding, as well as a focus of utopian thinking. In the still growing research community, one of the favourite optimistic analogies for data processing is that of the oil refinery, extracting the essence out of the raw data. Pessimists look for their imagery to the other end of the petrol cycle, and talk about the “data exhausts” of our society.

Obviously, the refinement community knows how to do “refining”. This paper explores the extent to which notions of refinement and data in the formal methods community relate to the core concepts in “big data”. In particular, can the data refinement paradigm can be used to explain aspects of big data processing?

URL : http://arxiv.org/abs/1606.02017

Proceedings of the 20th International Conference on Electronic Publishing

Editors : Fernando Loizides, Birgit Schmidt

The field of electronic publishing has grown exponentially in the last two decades, but we are still in the middle of this digital transformation. With technologies coming and going for all kinds of reasons, the distribution of economic, technological and discursive power continues to be negotiated.

This book presents the proceedings of the 20th Conference on Electronic Publishing (Elpub), held in Göttingen, Germany, in June 2016.

This year’s conference explores issues of positioning and power in academic publishing, and it brings together world leading stakeholders such as academics, practitioners, policymakers, students and entrepreneurs from a wide variety of fields to exchange information and discuss the advent of innovations in the areas of electronic publishing, as well as reflect on the development in the field over the last 20 years.

Topics covered in the papers include how to maintain the quality of electronic publications, modeling processes and the increasingly prevalent issue of open access, as well as new systems, database repositories and datasets. This overview of the field will be of interest to all those who work in or make use of electronic publishing.

URL : Proceedings of the 20th International Conference on Electronic Publishing

Alternative location : http://ebooks.iospress.nl/ISBN/978-1-61499-648-4

Why Most Published Research Findings Are False

Author : John P. A. Ioannidis

There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field.

In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance.

Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.

URL : Why Most Published Research Findings Are False

Alternative location : http://dx.doi.org/10.1371/journal.pmed.0020124

Looking for the Impact of Open Access on Interlibrary Loan

Authors : Collette Mak, Tina Baich

The purpose of this paper is to analyze interlibrary loan (ILL) article requests for evidence of a decrease that could be attributed to the spread of open access. The authors collected and analyzed the interlibrary loan data of two Indiana academic libraries for requests submitted during October and November (peak ILL months) from 2006-2015.

The requests were assigned to one of four categories: general, humanities, social sciences, and sciences based on Library of Congress classification, and the relative age of each article was calculated, where the relative age is the difference between year of publication and year of request.

Assuming an embargo period of 12-18 months for traditional publications, a change in articles of relative age 0-2 would suggest that scholars were obtaining that material from other sources.

The authors then looked for trends that might indicate the impact of open access on interlibrary loan requests. This paper will present the results and discuss the other environmental factors that may influence the number of requests placed within a field of study.

URL : Looking for the Impact of Open Access on Interlibrary Loan

Alternative location : http://library.ifla.org/1358/1/095-mak-en.pdf

Towards a paradigm for open and free sharing of scientific data on global change science in China

Authors : Changhui Peng, Xinzhang Song, Hong Jiang, Qiuan Zhu, Huai Chen, Jing M. Chen, Peng Gong, Chang Jie, Wenhua Xiang, Guirui Yu, Xiaolu Zhou

Despite great progress in data sharing that has been made in China in recent decades, cultural, policy, and technological challenges have prevented Chinese researchers from maximizing the availability of their data to the global change science community.

To achieve full and open exchange and sharing of scientific data, Chinese research funding agencies need to recognize that preservation of, and access to, digital data are central to their mission, and must support these tasks accordingly.

The Chinese government also needs to develop better mechanisms, incentives, and rewards, while scientists need to change their behavior and culture to recognize the need to maximize the usefulness of their data to society as well as to other researchers.

The Chinese research community and individual researchers should think globally and act personally to promote a paradigm of open, free, and timely data sharing, and to increase the effectiveness of knowledge development.

URL : Towards a paradigm for open and free sharing of scientific data on global change science in China

DOI : http://dx.doi.org/10.1002/ehs2.1225

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

Authors : Ying Huang, Yi Zhang, Jan Youtie, Alan L. Porter, Xuefeng Wang

How do funding agencies ramp-up their capabilities to support research in a rapidly emerging area?

This paper addresses this question through a comparison of research proposals awarded by the US National Science Foundation (NSF) and the National Natural Science Foundation of China (NSFC) in the field of Big Data.

Big data is characterized by its size and difficulties in capturing, curating, managing and processing it in reasonable periods of time. Although Big Data has its legacy in longstanding information technology research, the field grew very rapidly over a short period.

We find that the extent of interdisciplinarity is a key aspect in how these funding agencies address the rise of Big Data. Our results show that both agencies have been able to marshal funding to support Big Data research in multiple areas, but the NSF relies to a greater extent on multi-program funding from different fields.

We discuss how these interdisciplinary approaches reflect the research hot-spots and innovation pathways in these two countries.

URL : How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

DOI : 10.1371/journal.pone.0154509