Archives des catégories : EN

Looking for the Impact of Open Access on Interlibrary Loan

Posté le par

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

Posté le par

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

Posté le par

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

Demographics of scholarly publishing and communication professionals

Posté le par

Authors : Albert N. Greco, Robert M. Wharton, Amy Brand

Scholarly publishing plays a pivotal role in the dissemination of research. While a great deal is known about the companies active in this sector, we need to know more about the employees of the firms that edit, produce, market, and distribute today’s scholarly books and journals.

To achieve this goal, the researchers conducted an international survey in late 2014 and early 2015 of approximately 6,121 scholarly publishing employees in 33 nations. The researchers received 828 usable questionnaires.

Some of the substantive findings about the respondents include: 90.79% identified themselves as white; 85.07% worked in scholarly publishing for more than 5 years; 60% held graduate or professional degrees; and 49% worked in editorial departments.

Key suggestions include the need for annual surveys of this type and that the majority of scholarly publishing firms need to address the issue of diversity.

URL : http://onlinelibrary.wiley.com/doi/10.1002/leap.1017/full

Small scholar-led scholarly journals: Can they survive and thrive in an open access future?

Posté le par

Author : Heather Morrison

This article presents early results of a research project designed to further our understanding of how to ensure that small scholar-led journals can survive and thrive in a global open access knowledge commons.

This phase of the research focuses on generation of ideas through interviews and focus groups with 15 participants involved in producing small scholar-led journals that either are or would like to become open access.

Although a couple of journals reported that they could survive in an open access future based on existing resources, most were concerned about survival and none expressed confidence that they could thrive in an open-access future.

These journals are far more diverse than one might imagine. Comparing the costs of article production from one journal with another might not make sense. A number of avenues for further research are discussed.

URL : Small scholar-led scholarly journals: Can they survive and thrive in an open access future?

Alternative location : http://onlinelibrary.wiley.com/doi/10.1002/leap.1015/full

Can we use altmetrics at the institutional level? A case study analysing the coverage by research areas of four Spanish universities

Posté le par

Authors : Daniel Torres-Salinas, Nicolas Robinson-Garcia, Evaristo Jiménez-Contreras

Social media based indicators or altmetrics have been under scrutiny for the last seven years. Their promise as alternative metrics for measuring scholarly impact is still far from becoming a reality.

Up to now, most studies have focused on the understanding of the nature and relation of altmetric indicators with citation data. Few papers have analysed research profiles based on altmetric data.

Most of these have related to researcher profiles and the expansion of these tools among researchers. This paper aims at exploring the coverage of the Altmetric.com database and its potential use in order to show universities’ research profiles in relationship with other databases.

We analyse a sample of four different Spanish universities.First, we observe a low coverage of altmetric indicators with only 36 percent of all documents retrieved from the Web of Science having an ‘altmetric’ score.Second, we observe that for the four universities analysed, the area of Science shows higher ‘altmetric’ scores that the rest of the research areas.

Finally, considering the low coverage of altmetric data at the institutional level, it could be interesting for research policy makers to consider the development of guidelines and best practices guides to ensure that researchers disseminate adequately their research findings through social media.

URL : Can we use altmetrics at the institutional level? A case study analysing the coverage by research areas of four Spanish universities

Alternative location : https://arxiv.org/abs/1606.00232

Revisiting the Data Lifecycle with Big Data Curation

Posté le par

Author : Line Pouchard

As science becomes more data-intensive and collaborative, researchers increasingly use larger and more complex data to answer research questions.

The capacity of storage infrastructure, the increased sophistication and deployment of sensors, the ubiquitous availability of computer clusters, the development of new analysis techniques, and larger collaborations allow researchers to address grand societal challenges in a way that is unprecedented.

In parallel, research data repositories have been built to host research data in response to the requirements of sponsors that research data be publicly available. Libraries are re-inventing themselves to respond to a growing demand to manage, store, curate and preserve the data produced in the course of publicly funded research.

As librarians and data managers are developing the tools and knowledge they need to meet these new expectations, they inevitably encounter conversations around Big Data. This paper explores definitions of Big Data that have coalesced in the last decade around four commonly mentioned characteristics: volume, variety, velocity, and veracity.

We highlight the issues associated with each characteristic, particularly their impact on data management and curation. We use the methodological framework of the data life cycle model, assessing two models developed in the context of Big Data projects and find them lacking.

We propose a Big Data life cycle model that includes activities focused on Big Data and more closely integrates curation with the research life cycle. These activities include planning, acquiring, preparing, analyzing, preserving, and discovering, with describing the data and assuring quality being an integral part of each activity.

We discuss the relationship between institutional data curation repositories and new long-term data resources associated with high performance computing centers, and reproducibility in computational science.

We apply this model by mapping the four characteristics of Big Data outlined above to each of the activities in the model. This mapping produces a set of questions that practitioners should be asking in a Big Data project

URL : Revisiting the Data Lifecycle with Big Data Curation

Alternative location : http://www.ijdc.net/index.php/ijdc/article/view/10.2.176