Factors for Improving the Research Publications and Quality Metrics
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MAJ 04/2021, Cf. Feuilletage Ci-Dessous
Recherche d’informations sur Internet (perfectionnement) méthodologie et outils disponibles A. Bouchard 04/2021 Pour commencer Principes Moteurs de recherche Sites internet Bases de données bibliographiques Autres bases de données textuelles Images et multimédia Web social Actualités et temps réel Quelques outils complémentaires Veille automatisée Exercices de synthèse Bibliographie Principes Internet ? web ? • internet • réseau de réseaux • fin des années 1960 • protocole TCP/IP • applications et services divers : courrier électronique (mail), messagerie instantanée (IM), forums de discussion, transfert de fichiers (FTP), pair à pair (P2P), web (www)… • données • utilisateurs : 5,1 MM. dans le monde (Internet World Stats, 2020) • langues : 61 % du contenu en anglais, 2,8 % en français (W3Techs, 2021) • voir également Internet live stats Internet ? web ? • Web • World Wide Web (www) • milieu des années 1990 • ensemble de pages HTML (textes, images, liens…) avec une URL et accessibles avec le protocole HTTP • web visible / web invisible • web invisible ou web profond (deep web) : partie du web non indexée et qui ne peut être trouvée par les moteurs de recherche (pages protégées par un mot de passe, pages générées dynamiquement à la suite d’une requête…), voire dark web (web illégal) : 95 % du total ? • taille • 1,2 MM. de sites (Netcraft) • web indexé : au moins 5,3 milliards de pages (Worldwidewebsize) • taille du web identifié (URL connues) ? web général ? Internet ? web ? Ascodocpsy ConceptArt multimédia, 2010 Les âges du web du web âges Les Méthodologie • DEBUSQUER l’information Différents outils Esprit critique Bookmark organisé URL significative Syntaxe de recherche Questions préalables Utilisation réfléchie Evaluation Règles à respecter d’après Eduscol. Rechercher sur internet Méthodologie 1° définir le sujet (contexte de la recherche et mots-clés) Questions Prendre du temps au départ pour en gagner par la suite.. -
Mapping the Future of Scholarly Publishing
THE OPEN SCIENCE INITIATIVE WORKING GROUP Mapping the Future of Scholarly Publishing The Open Science Initiative (OSI) is a working group convened by the National Science Communi- cation Institute (nSCI) in October 2014 to discuss the issues regarding improving open access for the betterment of science and to recommend possible solutions. The following document summa- rizes the wide range of issues, perspectives and recommendations from this group’s online conver- sation during November and December 2014 and January 2015. The 112 participants who signed up to participate in this conversation were drawn mostly from the academic, research, and library communities. Most of these 112 were not active in this conversa- tion, but a healthy diversity of key perspectives was still represented. Individual participants may not agree with all of the viewpoints described herein, but participants agree that this document reflects the spirit and content of the conversation. This main body of this document was written by Glenn Hampson and edited by Joyce Ogburn and Laura Ada Emmett. Additional editorial input was provided by many members of the OSI working group. Kathleen Shearer is the author of Annex 5, with editing by Dominque Bambini and Richard Poynder. CC-BY 2015 National Science Communication Institute (nSCI) www.nationalscience.org [email protected] nSCI is a US-based 501(c)(3) nonprofit organization First edition, January 2015 Final version, April 2015 Recommended citation: Open Science Initiative Working Group, Mapping the Future of Scholarly -
What Is Peer Review?
What is Peer Review? Scholarly peer review is the process of evaluation of scientific, academic, or professional work by others working in the same field. The process is designed to ensure that academic publications make substantial contributions to the state of knowledge about a subject and meet minimum standards of reliability. Fundamentals Is it worth it to do the extra work to find peer reviewed sources? When researching, it is important to look at articles recently published in top tier peer Keep in Mind reviewed or refereed journals to understand the current issues and developments of a Many scholarly journals only peer review original topic. research. The standards of peer review for editorials, literature review/survey articles, and How can I tell if an article is peer book reviews may be less stringent (or non- reviewed? existent) even if they are published in refereed Follow these steps: journals. • Check the UlrichsWeb database for the journal (is it refereed, is the content type listed as academic/scholarly). • If the journal is not in UlrichsWeb, try googling it. On the publisher’s website, look for the About page or submission guidelines. These pages will usually explicitly say whether a journal is peer reviewed or refereed and often will describe the process. The Process What is “blind” peer review? Usually the refereeing process involves what is called “blind” peer review. This is when the reviewers do not know who wrote the article they are reviewing. This encourages reviewers to evaluate the sources according to the norms of their community rather than the reputation of the author. -
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. -
How to Review Papers 2 3 for Academic Meta-Jokes
How to Review Papers 2 3 For academic meta-jokes: https://www.facebook.com/groups/reviewer2/ 4 “How not to be Reviewer #2 (https://amlbrown.com/2015/11/10/how-not-to-be-reviewer-2/)” - Ashley Brown, U. of Utaha Who is the Reviewer #2? ✘ “Literally, Reviewer 2 is the anonymised moniker given to the second peer to review a research paper. In common parlance, Reviewer 2 can be summarised as possessing the following qualities: ○ Grumpy, aggressive ○ Vague, unhelpful, inflexible ○ Overbearingly committed to a pet discipline ○ Overly focused on a particular methodology ○ Unwilling to give the benefit of the doubt ○ Unwilling to view the authors of a submitted paper as peers” 5 6 What is peer review? ✘ Evaluation of work by one or more people of similar competence to the producers of the work (=peers) – Wikipedia ✘ Scholarly peer review helps editors and program chairs to decide whether to publish/accept specific work ✘ Reviewers work for free (also editors and chairs) – perhaps the weirdest part of any academic’s job to laymen’s eyes ✘ It has appeared 300 years ago (Philosophical Transactions of Royal Society, editor Henry Oldenburg 1618-1677) 7 Why should we do peer review? ✘ Ensures and even improves the quality, value, and integrity of scientific communication ✘ Only the experts in the same domain can provide sufficiently detailed yet impartial opinions ✘ If you do not care about quality of other’s work, eventually everyone will stop caring about your work as well 8 Why should we do peer review? ✘ Scientific ideals aside, certain events just -
Do You Speak Open Science? Resources and Tips to Learn the Language
Do You Speak Open Science? Resources and Tips to Learn the Language. Paola Masuzzo1, 2 - ORCID: 0000-0003-3699-1195, Lennart Martens1,2 - ORCID: 0000- 0003-4277-658X Author Affiliation 1 Medical Biotechnology Center, VIB, Ghent, Belgium 2 Department of Biochemistry, Ghent University, Ghent, Belgium Abstract The internet era, large-scale computing and storage resources, mobile devices, social media, and their high uptake among different groups of people, have all deeply changed the way knowledge is created, communicated, and further deployed. These advances have enabled a radical transformation of the practice of science, which is now more open, more global and collaborative, and closer to society than ever. Open science has therefore become an increasingly important topic. Moreover, as open science is actively pursued by several high-profile funders and institutions, it has fast become a crucial matter to all researchers. However, because this widespread interest in open science has emerged relatively recently, its definition and implementation are constantly shifting and evolving, sometimes leaving researchers in doubt about how to adopt open science, and which are the best practices to follow. This article therefore aims to be a field guide for scientists who want to perform science in the open, offering resources and tips to make open science happen in the four key areas of data, code, publications and peer-review. The Rationale for Open Science: Standing on the Shoulders of Giants One of the most widely used definitions of open science originates from Michael Nielsen [1]: “Open science is the idea that scientific knowledge of all kinds should be openly shared as early as is practical in the discovery process”. -
A History and Development of Peer-Review Process
Annals of Library and Information Studies Vol. 66, December 2019, pp. 152-162 A history and development of peer-review process Siladitya Jana Assistant Librarian, Indian Institute of Science Education and Research Kolkata, Mohanpur 741 246, India, Email: [email protected] Received: 24 July 2019; accepted 28 November 2019 The paper shows the importance of peer review process in the scholarly communication system and discusses both the closed and the newly emerging open peer review models. It also examines the peer review system at the scholarly academies or societies in their nomination systems for prizes, rewards, etc. It also discusses the various facets of the newly developed open peer review models now prevalent in various journals. The paper may help to understand and appreciate the role played by peer review in the scholarly communication system and the efforts being made to make it more transparent. Keywords : Double-blind peer review; Open access; Open peer review; Peer review; Scholarly communication; Single-blind peer review Introduction learned organisations to publish any material submitted by its members, etc. These factors resulted Peer review is the quality control mechanism in the in the uneven growth of peer review as a means of entire ecology of the scholarly communication 3 system. International Committee of Medical Journal controlling the quality of the publishable materials . Recent reports of peer review fraud also raise Editors (ICMJE) defines peer review as the critical 4,5,6 assessment of manuscripts submitted to journals by concerns about its efficacy and future . 1 experts who are usually not part of the editorial staff . -
Gender Bias in Research Teams and the Underrepresentation of Women in Science 2 Roslyn Dakin1* and T
bioRxiv preprint doi: https://doi.org/10.1101/741694; this version posted August 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Gender bias in research teams and the underrepresentation of women in science 2 Roslyn Dakin1* and T. Brandt Ryder2,3 4 1 Department of Biology, Carleton University, Ottawa, ON, K1S 5B6, Canada 6 2 Bird Conservancy of the Rockies, Fort Collins, Colorado, 80525, USA 3 Migratory Bird Center, Smithsonian Conservation Biology Institute, National Zoological Park, 8 Washington, DC 20013, USA 10 * Correspondence to: [email protected] 12 Abstract Why are females still underrepresented in science? The social factors that affect career choices 14 and trajectories are thought to be important but are poorly understood. We analyzed author gender in a sample of >61,000 scientific articles in the biological sciences to evaluate the factors 16 that shape the formation of research teams. We find that authorship teams are more gender- assorted than expected by chance, with excess homotypic assortment accounting for up to 7% of 18 published articles. One possible mechanism that could explain gender assortment and broader patterns of female representation is that women may focus on different research topics than men 20 (i.e., the “topic preference” hypothesis). An alternative hypothesis is that researchers may consciously or unconsciously prefer to work within same-gender teams (the “gender homophily” 22 hypothesis). Using network analysis, we find no evidence to support the topic preference hypothesis, because the topics of female-authored articles are no more similar to each other than 24 expected within the broader research landscape. -
Aggregating Research Papers from Publishers' Systems to Support Text
Aggregating Research Papers from Publishers’ Systems to Support Text and Data Mining: Deliberate Lack of Interoperability or Not? Petr Knoth, Nancy Pontika The Open University Walton Drive, Milton Keynes, United Kingdom [email protected], [email protected] Abstract In the current technology dominated world, interoperability of systems managed by different organisations is an essential property enabling the provision of services at a global scale. In the Text and Data Mining field (TDM), interoperability of systems offering access to text corpora offers the opportunity of increasing the uptake and impact of TDM applications. The global corpus of all research papers, i.e. the collection of human knowledge so large no one can ever read in their lifetime, represents one of the most exciting opportunities for TDM. Although the Open Access movement, which has been advocating for free availability and reuse rights to TDM from research papers, has achieved some major successes on the legal front, the technical interoperability of systems offering free access to research papers continues to be a challenge. COnnecting REpositories (CORE) (Knoth and Zdrahal, 2012) aggregates the world’s open access full-text scientific manuscripts from repositories, journals and publisher systems. One of the main goals of CORE is to harmonise and pre-process these data to lower the barrier for TDM. In this paper, we report on the preliminary results of an interoperability survey of systems provided by journal publishers, both open access and toll access. This helps us to assess the current level of systems’ interoperability and suggest ways forward. Keywords: Interoperability, publishers, standardisation 1. -
A New Method and Metric to Evaluate the Peer Review Process of Scholarly Journals
Pub Res Q (2014) 30:23–38 DOI 10.1007/s12109-013-9339-y A New Method and Metric to Evaluate the Peer Review Process of Scholarly Journals Adam Etkin Published online: 6 December 2013 Ó The Author(s) 2013. This article is published with open access at Springerlink.com Abstract This paper will propose a new system that produces a metric that is an indicator of the level of peer review conducted prior to the publication of scholarly material. A mathematical algorithm which incorporates weighted values of the roles within the peer review process is created. The h-index, which is a value that ‘‘measures the productivity and impact of a scientist or scholar,’’ is also incorporated. Each round of review is weighted using the square root as later rounds of peer review are often less rigorous than earlier rounds. Once a paper is accepted the calculation is conducted and a ‘‘peer review evaluation’’ metric, or ‘‘Peer Review Evaluation Score’’ (pre-SCORE) is available. It is clear that such a metric would prove beneficial to all engaged parties (authors, publishers, readers, libraries). Authors will know that their work is being evaluated by a trustworthy publication and by experts in their field. Legitimate, ethical publishers will be recognized as such. Readers would have the ability to filter out material which was not properly vetted, and libraries/consortia would have further assurance that their limited funds are spent wisely. Future studies to see if there is a correlation between the pre-SCORE and Impact Factor or highly cited material is possible. -
Exposing Dmps: Use Cases, Workflows and Guidelines
Exposing DMPs: Use cases, workflows and guidelines Case statement for community review July 2017 Contributors David Carr - The Wellcome Trust John Chodacki, California Digital Library John Faundeen, Earth Resources Observation Center, USGS Bev Jones University of Lincoln Natalie Meyers, Centre for Open Science/ University of Notre Dame Paul Millar, DESY Fiona Murphy, MMC Ltd Kathryn Unsworth, Australian National Data Service Angus Whyte, Digital Curation Centre (Editor) Elena Zudilova-Seinstra, Elsevier Working Group Charter A variety of stakeholders are showing growing interest in exposing data management plans (*) to other actors (human/machine) in the research lifecycle, beyond their creator and the funder or institution that mandates their production. Interested stakeholders include researchers themselves, funders, institutions, and a variety of service providers and community organisations including repositories, institutions, journals, publishers, and providers of tools for writing and maintaining plans. Implementation and adoption is currently hampered by two problems: ● A lack of standards for expression and interchange of DMPs ● Insufficient understanding of the needs of users and the benefits and risks of different modes of action This proposed working group will address both of these issues; the issue of a standardised form of expression for DMPs is the concern of the proposed DMP Common Standards Working Group. The group’s output will include a reference model and alternative strategies for exposing plans, to best serve community interests in meeting FAIR principles,1 based on shared experience of ‘early adopters’ in test implementations. It will be supported by work to gauge user needs and motivations for exposing DMPs as well as perceived risks and disbenefits. -
Ad Hominem Arguments in the Service of Boundary Work Among Climate Scientists
SISSA – International School for Advanced Studies Journal of Science Communication ISSN 1824 – 2049 http://jcom.sissa.it/ RECEIVED: October 12, 2011 PUBLISHED: February 15, 2012 Article Ad hominem arguments in the service of boundary work among climate scientists Lawrence Souder, Furrah Qureshi ABSTRACT: Most accounts of an ideal scientific discourse proscribe ad hominem appeals as one way to distinguish it from public discourse. Because of their frequent use of ad hominem attacks, the Climategate email messages provoked strong criticisms of climate scientists and climate science. This study asks whether the distinction between public and scientific discourse holds in this case and thus whether the exclusion of ad hominem arguments from scientific discourse is valid. The method of analysis comes from the field of informal logic in which argument fallacies like the ad hominem are classified and assessed. The approach in this study focuses on a functional analysis of ad hominem—their uses rather than their classification. The analysis suggests three distinct functional uses of ad hominem remarks among the Climategate emails: (1) indirect, (2) tactical, and (3) meta-. Consistent with previous research on ad hominem arguments in both public and scientific discourse, these results reinforce the common opinion of their fallacious character. Only the remarks of the last type, the meta- ad hominem, seemed to be non-fallacious in that they might help to preempt the very use of ad hominem attacks in scientific discourse. “In this case, de Freitas is such a poor scientist that he may simply disappear.” (Tom Wigley, Climategate email, 1051230500.txt)1 “Pielke wouldn't understand independence if it hit him in the face.” (Phil Jones, Climategate email, 1233249393.txt) Introduction2 As scientists-in-training, Chris de Freitas and Roger Pielke, Sr., may have suffered appropriately the sting of such remarks from an overbearing advisor on their dissertation committees in a moment of impatience.