Open Access—What's New, What's Worked, What Hasn't
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Gies for Increasing Citations
CORE Metadata, citation and similar papers at core.ac.uk Provided by International SERIES on Information Systems and Management in Creative eMedia (CreMedia) Maximized Research Impact: Effective Strate- gies for Increasing Citations Nader Ale Ebrahim*1, Hossein Gholizadeh2, Artur Lugmayr3 1Research Support Unit, Centre for Research Services, Institute of Research Management and Monitoring (IPPP), University of Malaya, Malaysia, Email: [email protected], *Corresponding author 2Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia 3VisLab., School of Media, Culture and Creative Arts, Curtin University, Perth, Australia Abstract The high competitive environment has forced higher education authori- ties to set their strategies to improve university ranking. Citations of published pa- pers are among the most widely used inputs to measure national and global uni- versity ranking (which accounts for 20% of QS, 30% of THE, and etc.). Therefore, from one hand, improving the citation impact of a search is one of the university manager’s strategies. On the other hand, the researchers are also looking for some helpful techniques to increase their citation record. This chapter by reviewing the relevant articles covers 48 different strategies for maximizing research impact and visibility. The results show that some features of article can help predict the num- ber of article views and citation counts. The findings presented in this chapter could be used by university authorities, authors, reviewers, and editors to maxim- ize the impact of articles in the scientific community. Keywords: University ranking, Improve citation, Citation frequency, Research impact, Open access, h-index Introduction The research output is an essential part of an institution’s measure and evaluation of research quality. -
Causes for the Persistence of Impact Factor Mania
PERSPECTIVE Causes for the Persistence of Impact Factor Mania Arturo Casadevall,a Ferric C. Fangb Departments of Microbiology & Immunology and Medicine, Albert Einstein College of Medicine, Bronx, New York, USAa; Departments of Laboratory Medicine and Microbiology, University of Washington School of Medicine, Seattle, Washington, USAb ABSTRACT Numerous essays have addressed the misuse of the journal impact factor for judging the value of science, but the prac- tice continues, primarily as a result of the actions of scientists themselves. This seemingly irrational behavior is referred to as “impact factor mania.” Although the literature on the impact factor is extensive, little has been written on the underlying causes of impact factor mania. In this perspective, we consider the reasons for the persistence of impact factor mania and its pernicious effects on science. We conclude that impact factor mania persists because it confers significant benefits to individual scientists Downloaded from and journals. Impact factor mania is a variation of the economic theory known as the “tragedy of the commons,” in which scien- tists act rationally in their own self-interests despite the detrimental consequences of their actions on the overall scientific enter- prise. Various measures to reduce the influence of the impact factor are considered. IMPORTANCE Science and scientists are currently afflicted by an epidemic of mania manifested by associating the value of re- search with the journal where the work is published rather than the content of the work itself. The mania is causing profound distortions in the way science is done that are deleterious to the overall scientific enterprise. In this essay, we consider the forces responsible for the persistence of the mania and conclude that it is maintained because it disproportionately benefits elements of the scientific enterprise, including certain well-established scientists, journals, and administrative interests. -
How Frequently Are Articles in Predatory Open Access Journals Cited
publications Article How Frequently Are Articles in Predatory Open Access Journals Cited Bo-Christer Björk 1,*, Sari Kanto-Karvonen 2 and J. Tuomas Harviainen 2 1 Hanken School of Economics, P.O. Box 479, FI-00101 Helsinki, Finland 2 Department of Information Studies and Interactive Media, Tampere University, FI-33014 Tampere, Finland; Sari.Kanto@ilmarinen.fi (S.K.-K.); tuomas.harviainen@tuni.fi (J.T.H.) * Correspondence: bo-christer.bjork@hanken.fi Received: 19 February 2020; Accepted: 24 March 2020; Published: 26 March 2020 Abstract: Predatory journals are Open Access journals of highly questionable scientific quality. Such journals pretend to use peer review for quality assurance, and spam academics with requests for submissions, in order to collect author payments. In recent years predatory journals have received a lot of negative media. While much has been said about the harm that such journals cause to academic publishing in general, an overlooked aspect is how much articles in such journals are actually read and in particular cited, that is if they have any significant impact on the research in their fields. Other studies have already demonstrated that only some of the articles in predatory journals contain faulty and directly harmful results, while a lot of the articles present mediocre and poorly reported studies. We studied citation statistics over a five-year period in Google Scholar for 250 random articles published in such journals in 2014 and found an average of 2.6 citations per article, and that 56% of the articles had no citations at all. For comparison, a random sample of articles published in the approximately 25,000 peer reviewed journals included in the Scopus index had an average of 18, 1 citations in the same period with only 9% receiving no citations. -
Journal List Emerging Sources Citation Index (Web of Science) 2020
JOURNAL TITLE ISSN eISSN PUBSLISHER NAME PUBLISHER ADDRESS 3C EMPRESA 2254‐3376 2254‐3376 AREA INNOVACION & DESARROLLO C/ELS ALZAMORA NO 17, ALCOY, ALICANTE, SPAIN, 03802 3C TECNOLOGIA 2254‐4143 2254‐4143 3CIENCIAS C/ SANTA ROSA 15, ALCOY, SPAIN, 03802 3C TIC 2254‐6529 2254‐6529 AREA INNOVACION & DESARROLLO C/ELS ALZAMORA NO 17, ALCOY, ALICANTE, SPAIN, 03802 3D RESEARCH 2092‐6731 2092‐6731 SPRINGER HEIDELBERG TIERGARTENSTRASSE 17, HEIDELBERG, GERMANY, D‐69121 3L‐LANGUAGE LINGUISTICS LITERATURE‐THE SOUTHEAST ASIAN JOURNAL OF ENGLISH LANGUAGE STUDIES 0128‐5157 2550‐2247 PENERBIT UNIV KEBANGSAAN MALAYSIA PENERBIT UNIV KEBANGSAAN MALAYSIA, FAC ECONOMICS & MANAGEMENT, BANGI, MALAYSIA, SELANGOR, 43600 452 F‐REVISTA DE TEORIA DE LA LITERATURA Y LITERATURA COMPARADA 2013‐3294 UNIV BARCELONA, FACULTAD FILOLOGIA GRAN VIA DE LES CORTS CATALANES, 585, BARCELONA, SPAIN, 08007 AACA DIGITAL 1988‐5180 1988‐5180 ASOC ARAGONESA CRITICOS ARTE ASOC ARAGONESA CRITICOS ARTE, HUESCA, SPAIN, 00000 AACN ADVANCED CRITICAL CARE 1559‐7768 1559‐7776 AMER ASSOC CRITICAL CARE NURSES 101 COLUMBIA, ALISO VIEJO, USA, CA, 92656 A & A PRACTICE 2325‐7237 2325‐7237 LIPPINCOTT WILLIAMS & WILKINS TWO COMMERCE SQ, 2001 MARKET ST, PHILADELPHIA, USA, PA, 19103 ABAKOS 2316‐9451 2316‐9451 PONTIFICIA UNIV CATOLICA MINAS GERAIS DEPT CIENCIAS BIOLOGICAS, AV DOM JOSE GASPAR 500, CORACAO EUCARISTICO, CEP: 30.535‐610, BELO HORIZONTE, BRAZIL, MG, 00000 ABANICO VETERINARIO 2007‐4204 2007‐4204 SERGIO MARTINEZ GONZALEZ TEZONTLE 171 PEDREGAL SAN JUAN, TEPIC NAYARIT, MEXICO, C P 63164 ABCD‐ARQUIVOS -
Tracking the Popularity and Outcomes of All Biorxiv Preprints
1 Meta-Research: Tracking the popularity and outcomes of all bioRxiv 2 preprints 3 Richard J. Abdill1 and Ran Blekhman1,2 4 1 – Department of Genetics, Cell Biology, and Development, University of Minnesota, 5 Minneapolis, MN 6 2 – Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, 7 MN 8 9 ORCID iDs 10 RJA: 0000-0001-9565-5832 11 RB: 0000-0003-3218-613X 12 13 Correspondence 14 Ran Blekhman, PhD 15 University of Minnesota 16 MCB 6-126 17 420 Washington Avenue SE 18 Minneapolis, MN 55455 19 Email: [email protected] 1 20 Abstract 21 The growth of preprints in the life sciences has been reported widely and is 22 driving policy changes for journals and funders, but little quantitative information has 23 been published about preprint usage. Here, we report how we collected and analyzed 24 data on all 37,648 preprints uploaded to bioRxiv.org, the largest biology-focused preprint 25 server, in its first five years. The rate of preprint uploads to bioRxiv continues to grow 26 (exceeding 2,100 in October 2018), as does the number of downloads (1.1 million in 27 October 2018). We also find that two-thirds of preprints posted before 2017 were later 28 published in peer-reviewed journals, and find a relationship between the number of 29 downloads a preprint has received and the impact factor of the journal in which it is 30 published. We also describe Rxivist.org, a web application that provides multiple ways 31 to interact with preprint metadata. 32 Introduction 33 In the 30 days of September 2018, four leading biology journals – The Journal of 34 Biochemistry, PLOS Biology, Genetics and Cell – published 85 full-length research 35 articles. -
A Reference Bacterial Genome Dataset Generated on the Miniontm Portable Single-Molecule Nanopore Sequencer Joshua Quick1,2, Aaron R Quinlan3 and Nicholas J Loman1*
Quick et al. GigaScience (2015) 4:6 DOI 10.1186/s13742-015-0043-z ERRATUM Open Access Erratum: A reference bacterial genome dataset generated on the MinIONTM portable single-molecule nanopore sequencer Joshua Quick1,2, Aaron R Quinlan3 and Nicholas J Loman1* Recently we noticed that we could not reproduce Author details Figure three (Figure 1 here) while analysing this data as 1Institute of Microbiology and Infection, University of Birmingham, Birmingham, B15 2TT, UK. 2NIHR Surgical Reconstruction and Microbiology part of a new experiment [1]. This was due to a modifica- Research Centre, University of Birmingham, B15 2TT, Birmingham, UK. 3Center tion to the script used for extracting sequence alignment for Public Health Genomics, University of Virginia, Virginia, Charlottesville, VA profiles from the dataset [2]. On further investigation we 22908, US. found that an error in this script had been reported and Received: 31 December 2014 Accepted: 5 January 2015 a fix supplied by an anonymous online contributor on October 27th 2014 via Github [3]. The error prevented mismatches from being properly counted in the calcu- References lation of read accuracy (insertions and deletions were). 1. Quick J, Quinlan AR, Loman NJ. A reference bacterial genome dataset generated on the minion™ portable single-molecule nanopore We therefore present updated versions of Figures three sequencer. GigaScience. 2014;3:22. (Figure 1 here) and four (Figure 2 here) generated by the 2. Quinlan AR. 2014. https://github.com/arq5x/nanopore-scripts/blob/ corrected script. We are grateful to the anonymous con- master/count-errors.py.Github 3. Anon. 2014. https://github.com/arq5x/nanopore-scripts/pull/1.Github tributor who noticed this error. -
Open Science and the Role of Publishers in Reproducible Research
Open science and the role of publishers in reproducible research Authors: Iain Hrynaszkiewicz (Faculty of 1000), Peter Li (BGI), Scott Edmunds (BGI) Chapter summary Reproducible computational research is and will be facilitated by the wide availability of scientific data, literature and code which is freely accessible and, furthermore, licensed such that it can be reused, inteGrated and built upon to drive new scientific discoveries without leGal impediments. Scholarly publishers have an important role in encouraGing and mandating the availability of data and code accordinG to community norms and best practices, and developinG innovative mechanisms and platforms for sharinG and publishinG products of research, beyond papers in journals. Open access publishers, in particular the first commercial open access publisher BioMed Central, have played a key role in the development of policies on open access and open data, and increasing the use by scientists of leGal tools – licenses and waivers – which maximize reproducibility. Collaborations, between publishers and funders of scientific research, are vital for the successful implementation of reproducible research policies. The genomics and, latterly, other ‘omics communities historically have been leaders in the creation and wide adoption of policies on public availability of data. This has been throuGh policies, such as Fort Lauderdale and the Bermuda Principles; infrastructure, such as the INSDC databases; and incentives, such as conditions of journal publication. We review some of these policies and practices, and how these events relate to the open access publishinG movement. We describe the implementation and adoption of licenses and waivers prepared by Creative Commons, in science publishinG, with a focus on licensing of research data published in scholarly journals and data repositories. -
Citation Databases for Legal Scholarship
University at Buffalo School of Law Digital Commons @ University at Buffalo School of Law Law Librarian Journal Articles Law Librarian Scholarship 3-19-2020 Citation Databases for Legal Scholarship John R. Beatty University at Buffalo School of Law, [email protected] Follow this and additional works at: https://digitalcommons.law.buffalo.edu/law_librarian_articles Part of the Law Commons, Law Librarianship Commons, and the Scholarly Communication Commons Recommended Citation John R. Beatty, Citation Databases for Legal Scholarship, 39 Legal Ref. Servs. Q. 56 (2020). Available at: https://digitalcommons.law.buffalo.edu/law_librarian_articles/50 This is an Accepted Manuscript of an article published by Taylor & Francis in Legal Reference Services Quarterly on March 19, 2020, available online: https://www.tandfonline.com/doi/full/10.1080/0270319X.2020.1738198. This Article is brought to you for free and open access by the Law Librarian Scholarship at Digital Commons @ University at Buffalo School of Law. It has been accepted for inclusion in Law Librarian Journal Articles by an authorized administrator of Digital Commons @ University at Buffalo School of Law. For more information, please contact [email protected]. Citation Databases for Legal Scholarship John R. Beatty a* a Charles B. Sears Law Library, University at Buffalo, State University of New York, Buffalo, NY, USA John Beatty, Charles B. Sears Law Library, O’Brian Hall, Buffalo, NY 14260, [email protected], ORCID ID: 0000-0002-4940-8483 John R. Beatty is the Faculty Scholarship Outreach Librarian at the Charles B. Sears Law Library at the University at Buffalo. This is an Accepted Manuscript of an article published by Taylor & Francis in Legal Reference Services Quarterly on March 19, 2020, available online: https://www.tandfonline.com/doi/full/10.1080/0270319X.2020.1738198. -
Citations and Gamed Metrics: Academic Integrity Lost
Acad. Quest. (2021) 34.1 DOI 10.51845/34s.1.18 10.51845/34s.1.18 Articles Citations and Gamed Metrics: Academic Integrity Lost Jaime A. Teixeira da Silva Author-based metrics (ABMs) and journal-based metrics (JBMs), as well as citations, are the dominant currency of intellectual recognition in academia. These metrics and citations continue to be dominated by the Clarivate Analytics Journal Impact Factor (JIF) and are still widely used as a surrogate to determine prestige, scientific credit, and influence.1 However, their dominance in this area needs to be rethought, especially in China, which accounts for approximately 19 percent of total scientific research papers globally.2 China, like several other countries, games the JIF for financial compensation in pay-to-publish schemes based on JIF-carrying journals.3 A competing metric, CiteScore, is also showing signs of being gamed.4 It is possible that CiteScore may have evolved, following Goodhart’s Law, as JIF’s relevance as an “academic” metric began to fray. 5 The culture of metrics, especially the JIF, to measure success, reputation, and productivity, or JIF-based praise platforms such as Clarivate Analytics’ “Highly Cited Researchers” report inflate the problem because they elevate the perceived excellence of single individuals above all others, when in fact most publishing success is collaborative.6 The survival of many academics and journals in this publish-or-perish culture depends on such metrics, as authors seek journals with higher JIFs in which to publish their findings. In the gold 1 Erin C. McKiernan, Lesley A. Schimanski, Carol Muñoz Nieves, Lisa Matthias, Meredith T. -
Assessing the Impact and Quality of Research Data Using Altmetrics and Other Indicators
Konkiel, S. (2020). Assessing the Impact and Quality of Research Data Using Altmetrics and Other Indicators. Scholarly Assessment Reports, 2(1): 13. DOI: https://doi.org/10.29024/sar.13 COMMISSIONED REPORT Assessing the Impact and Quality of Research Data Using Altmetrics and Other Indicators Stacy Konkiel Altmetric, US [email protected] Research data in all its diversity—instrument readouts, observations, images, texts, video and audio files, and so on—is the basis for most advancement in the sciences. Yet the assessment of most research pro- grammes happens at the publication level, and data has yet to be treated like a first-class research object. How can and should the research community use indicators to understand the quality and many poten- tial impacts of research data? In this article, we discuss the research into research data metrics, these metrics’ strengths and limitations with regard to formal evaluation practices, and the possible meanings of such indicators. We acknowledge the dearth of guidance for using altmetrics and other indicators when assessing the impact and quality of research data, and suggest heuristics for policymakers and evaluators interested in doing so, in the absence of formal governmental or disciplinary policies. Policy highlights • Research data is an important building block of scientific production, but efforts to develop a framework for assessing data’s impacts have had limited success to date. • Indicators like citations, altmetrics, usage statistics, and reuse metrics highlight the influence of research data upon other researchers and the public, to varying degrees. • In the absence of a shared definition of “quality”, varying metrics may be used to measure a dataset’s accuracy, currency, completeness, and consistency. -
Research Prioritization Through Prediction of Future Impact on Biomedical Science: a Position Paper on Inference-Analytics Ganapathiraju and Orii
Score Rank Re-rank by Predicted Impact on Future Science Score Rank Re-rank by Confidence Score Rank Re-rank by Resource Requirements or Reagent Availability Inference Analytics: A Necessary Next step to Big Data Analytics in Biology Research prioritization through prediction of future impact on biomedical science: a position paper on inference-analytics Ganapathiraju and Orii Ganapathiraju and Orii GigaScience 2013, 2:11 http://www.gigasciencejournal.com/content/2/1/11 Ganapathiraju and Orii GigaScience 2013, 2:11 http://www.gigasciencejournal.com/content/2/1/11 RESEARCH Open Access Research prioritization through prediction of future impact on biomedical science: a position paper on inference-analytics Madhavi K Ganapathiraju1,2* and Naoki Orii1,2 Abstract Background: Advances in biotechnology have created “big-data” situations in molecular and cellular biology. Several sophisticated algorithms have been developed that process big data to generate hundreds of biomedical hypotheses (or predictions). The bottleneck to translating this large number of biological hypotheses is that each of them needs to be studied by experimentation for interpreting its functional significance. Even when the predictions are estimated to be very accurate, from a biologist’s perspective, the choice of which of these predictions is to be studied further is made based on factors like availability of reagents and resources and the possibility of formulating some reasonable hypothesis about its biological relevance. When viewed from a global perspective, say from that of a federal funding agency, ideally the choice of which prediction should be studied would be made based on which of them can make the most translational impact. -
A Locally Funded Puerto Rican Parrot (Amazona Vittata) Genome Sequencing Project Increases Avian Data and Advances Young Researcher Education Oleksyk Et Al
Downloaded from https://academic.oup.com/gigascience/article-abstract/1/1/2047-217X-1-14/2656136 by University of Lethbridge user on 20 March 2020 A locally funded Puerto Rican parrot (Amazona vittata) genome sequencing project increases avian data and advances young researcher education Oleksyk et al. Oleksyk et al. GigaScience 2012, 1:14 http://www.gigasciencejournal.com/content/1/1/14 28 Oleksyk et al. GigaScience 2012, 1:14 http://www.gigasciencejournal.com/content/1/1/14 DATANOTE Open Access A locally funded Puerto Rican parrot Downloaded from https://academic.oup.com/gigascience/article-abstract/1/1/2047-217X-1-14/2656136 by University of Lethbridge user on 20 March 2020 (Amazona vittata) genome sequencing project increases avian data and advances young researcher education Taras K Oleksyk1*, Jean-Francois Pombert2, Daniel Siu3, Anyimilehidi Mazo-Vargas1, Brian Ramos1, Wilfried Guiblet1, Yashira Afanador1, Christina T Ruiz-Rodriguez1,4, Michael L Nickerson4, David M Logue1, Michael Dean4, Luis Figueroa5, Ricardo Valentin6 and Juan-Carlos Martinez-Cruzado1 Abstract Background: Amazona vittata is a critically endangered Puerto Rican endemic bird, the only surviving native parrot species in the United States territory, and the first parrot in the large Neotropical genus Amazona, to be studied on a genomic scale. Findings: In a unique community-based funded project, DNA from an A. vittata female was sequenced using a HiSeq Illumina platform, resulting in a total of ~42.5 billion nucleotide bases. This provided approximately 26.89x average coverage depth at the completion of this funding phase. Filtering followed by assembly resulted in 259,423 contigs (N50 = 6,983 bp, longest = 75,003 bp), which was further scaffolded into 148,255 fragments (N50 = 19,470, longest = 206,462 bp).