Journal of Data and Information Science

J. of Data & Info. Sci. ONL

<div><italic>Journal of Data and Information Science</italic>, 2016, 1(4), 60-80. <related-article related-article-type="corrected-article" ext-link-type="doi" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="10.20309/jdis.201625"/>10.20309/jdis.201625In this paper, the third author’s last name is Rath and first Name is Manasa. Her name has been reversed in order.</div>

<article-title>Open Peer Review in Scientific Publishing: A Web Mining Study of <italic>PeerJ</italic> Authors and Reviewers</article-title>

Open Peer Review in Scientific Publishing: A Web Mining Study of  Authors and Reviewers

Journal of Data and Information Science is covered by the following services: <ul> <li> SCOPUS </li> <li> Web of Science - Emerging Sources Citation Index </li> <li> Baidu Scholar </li> <li> Cabell's Whitelist </li> <li> CNKI Scholar (China National Knowledge Infrastructure) </li> <li> CNPIEC - cnpLINKer </li> <li> Dialnet </li> <li> Dimensions </li> <li> DOAJ (Directory of Open Access Journals) </li> <li> EBSCO (relevant databases) </li> <li> EBSCO Discovery Service </li> <li> Google Scholar </li> <li> Inspec </li> <li> J-Gate </li> <li> JournalTOCs </li> <li> KESLI-NDSL (Korean National Discovery for Science Leaders) </li> <li> Latindex </li> <li> Microsoft Academic </li> <li> MyScienceWork </li> <li> Naver Academic </li> <li> Naviga (Softweco) </li> <li> Primo Central (ExLibris) </li> <li> ProQuest (relevant databases) </li> <li> Publons </li> <li> QOAM (Quality Open Access Market) </li> <li> ReadCube </li> <li> SCImago (SJR) </li> <li> Semantic Scholar </li> <li> Summon (ProQuest) </li> <li> TDNet </li> <li> Ulrich's Periodicals Directory/ulrichsweb </li> <li> WanFang Data </li> <li> WorldCat (OCLC) </li> <li> Zentralblatt Math (zbMATH) </li> </ul>

Journal of Data and Information Science ist in den folgenden Services indiziert: <ul> <li> SCOPUS </li> <li> Web of Science - Emerging Sources Citation Index </li> <li> Baidu Scholar </li> <li> Cabell's Whitelist </li> <li> CNKI Scholar (China National Knowledge Infrastructure) </li> <li> CNPIEC - cnpLINKer </li> <li> Dialnet </li> <li> Dimensions </li> <li> DOAJ (Directory of Open Access Journals) </li> <li> EBSCO (relevant databases) </li> <li> EBSCO Discovery Service </li> <li> Google Scholar </li> <li> Inspec </li> <li> J-Gate </li> <li> JournalTOCs </li> <li> KESLI-NDSL (Korean National Discovery for Science Leaders) </li> <li> Latindex </li> <li> Microsoft Academic </li> <li> MyScienceWork </li> <li> Naver Academic </li> <li> Naviga (Softweco) </li> <li> Primo Central (ExLibris) </li> <li> ProQuest (relevant databases) </li> <li> Publons </li> <li> QOAM (Quality Open Access Market) </li> <li> ReadCube </li> <li> SCImago (SJR) </li> <li> Semantic Scholar </li> <li> Summon (ProQuest) </li> <li> TDNet </li> <li> Ulrich's Periodicals Directory/ulrichsweb </li> <li> WanFang Data </li> <li> WorldCat (OCLC) </li> <li> Zentralblatt Math (zbMATH) </li> </ul>

<DIV align=left> Please submit your aritcle via: <A href="http://www.jdis.org/">www.jdis.org</A>. Peer Review Process All submissions for JDIS will be checked first by the Scientific Editors for the composition and arrangement against JDIS’s Author Guidelines, as well as for the plagiarism detection. Then the Editor-in-Chief will evaluate them for suitability in the journal on the basis of scope and quality, with possible consultation from other members of the Editorial Board. Contributions deemed unsuitable can be rejected without further review. Articles and reviews deemed in scope and of sufficient quality will be sent to external reviewers (typically two or three) for an in-depth review. The names of the authors will be disclosed to reviewers. Reviewers will be kept anonymous unless they choose to disclose their identity to the authors.　 JDIS asks that the review report should include the following parts: <OL> <LI>A summary identifying the specific strengths and weaknesses of the work, including where appropriate, the novelty of the study and the conceptual advance over previously published works.　</LI> <LI>Comments on the quality of the scientific content and writing. </LI> <LI>Suggestions as to what additional changes might be required in order to support the claims being made. </LI> <LI>Whether the authors make appropriate citations to the pre-existing literature.　 </LI></OL> The types of decisions are accept without revision, minor revision, major revision and reject. It takes about 28 days from submission to first decision. For the manuscripts with high quality, JDIS provides a Pub-Express channel which means the submissions through this channel can be directly sent to the Co-EICs for a quick but comprehensive evaluation without entering the external peer-review process. The final decision on whether the manuscript is accepted or not for publication by JDIS is normally made within 72 hours. Authors who think their manuscript worthy of quick publication are encouraged to apply to the Pub-Express by stating the exact reasons in Cover Letter when submitting. Please note: entering into the Pub-Express does not mean final acceptance.　 Open Access Statement The journal is an Open Access journal that allows a free unlimited access to all its contents without any restrictions upon publication to all users. <A href="https://sciendo-parsed-data-feed.s3.eu-central-1.amazonaws.com/JDIS/Open_Access_License.pdf">Open Access License</A> </DIV>

<DIV align=left> Journal of Data and Information Science (JDIS, formerly Chinese Journal of Library and Information Science), sponsored by the Chinese Academy of Sciences (CAS) and published quarterly by the National Science Library of CAS, is the first internationally published English-language academic journal in Library and Information Science and related fields from China. JDIS devotes itself to the study and application of the theories, methods, techniques, services, and infrastructural facilities using big data to support knowledge discovery for decision and policy making. The basic emphasis is research that focuses on big data, analytics, and knowledge discovery, and supports decision making. Special attention is given to knowledge discovery to detect and predict structures, trends, behaviors, relations, and evolutions and disruptions in scientific research. This includes issues of innovation, business, politics, security, media and communications, and social development. The big data topics may include metadata or full content data, text or non-textural data, structured or non-structural data, domain specific or cross-domain data, and dynamic or interactive data. The main areas of interest are: <OL> </OL> 1. New theories, methods, and techniques of big data-based data mining, knowledge discovery, and informatics, including but not limited to scientometrics, communication analysis, social network analysis, tech and industry analysis, competitive intelligence, knowledge mapping, evidence-based policy analysis, and predictive analysis. 2. New methods, architectures, and facilities to develop or improve knowledge infrastructure that can support knowledge organization and sophisticated analytics, including but not limited to ontology construction, knowledge organization, semantic linked data, knowledge integration and fusion, semantic retrieval, domain-specific knowledge infrastructure, and semantic sciences. 3. New mechanisms, methods, and tools to embed knowledge analytics and knowledge discovery into actual operation, service, or managerial processes, including but not limited to knowledge-assisted scientific discovery, and data mining-driven intelligent workflows in learning, communications, or management. Specific topic areas may include (but are not limited to): <UL> <LI>Knowledge organization </LI> <LI>Knowledge discovery and data mining </LI> <LI>Knowledge integration and fusion </LI> <LI>Semantic Web metrics </LI> <LI>Scientometrics </LI> <LI>Analytic and diagnostic informetrics </LI> <LI>Competitive intelligence </LI> <LI>Predictive analysis </LI> <LI>Social network analysis and metrics </LI> <LI>Semantic and interactively analytic retrieval </LI> <LI>Evidence-based policy analysis </LI> <LI>Intelligent knowledge production </LI> <LI>Knowledge-driven workflow management and decision-making </LI> <LI>Knowledge-driven collaboration and its management </LI> <LI>Domain knowledge infrastructure with knowledge fusion and analytics </LI> <LI>Training for data &amp; information scientists </LI> <LI>Development of data and information services </LI></UL> JDIS publishes theoretical and empirical work. Systematic reviews are welcome and applied research in development of advanced methods, services, and best practices is also an important part. But simple application of established informetrics on a specific research field or country is out of the scope. Welcome to submit your papers to JDIS. Why subscribe and read JDIS is the first and only English journal from China in Library and Information Science and related fields. With an aim to disseminate the cutting-edge research in these fields, it is devoted to the study and application of the theories, methods, techniques, services, and infrastructural facilities using big data to support knowledge discovery for decision and policy making. The basic emphasis is big data-based, analytics centered, knowledge discovery driven, and decision making supporting. JDIS has gathered a big body of high profile experts across the world who contribute their research to the journal. The international authors account for around 62% in its first publication year (2016). Why submit JDIS is the first and only English journal from China in Library and Information Science and related fields. It owns a number of world front-line scholars as editorial board members or reviewers. The turnaround time on average for a manuscript from submission to final decision is less than two and a half months. Archiving Sciendo archives the contents of this journal in <A href="https://www.portico.org/">Portico</A>- digital long-term preservation service of scholarly books, journals and collections.</A> Plagiarism Policy The editorial board is participating in a growing community of <A href="https://www.crossref.org/services/similarity-check/">Similarity Check System's</A> users in order to ensure that the content published is original and trustworthy. Similarity Check is a medium that allows for comprehensive manuscripts screening, aimed to eliminate plagiarism and provide a high standard and quality peer-review process.</DIV>

Co-Editors-in-Chief Xiaolin Zhang National Science Library, the Chinese Academy of Sciences, China Ronald Rousseau University of Leuven, Belgium Associate Editor-in-Chief Liying Yang National Science Library, the Chinese Academy of Sciences, China Managing Editor Ping Meng National Science Library, the Chinese Academy of Sciences, China Editorial Boards Judit Bar-Ilan (1958-2019) Bar-Ilan University, Israel Christine L. Borgman University of California, Los Angeles, USA Kevin Boyack SciTech Strategies Inc., USA Cong Cao University of Nottingham Ningbo, China Dar-Zen Chen National Taiwan University, Taiwan, China Cinzia Daraio Sapienza University of Rome, Italy Nees-Jan van Eck Leiden University, the Netherlands Tove Faber Frandsen, University of Southern Denmark, Denmark Jane Greenberg, Drexel University, USA Robin Haunschild, Max Plank Institute for Solid State Research, Germany Xiaojun Hu, Zhejiang University, China Tao Jia Southwest University, China Guangjian Li Peking University, China Yuelin Li Nankai University, China Wei Liu Library of Shanghai, China Wei Lu Wuhan University, China Xiaobin Lu Renmin University, China Hamid R. Jamali, Charles Sturt University, Australia Alberto Martin-Martin, University of Granada, Spain Eustache Megnigbeto, Bureau of Studies and Research in Information Science, Benin Olga Moskaleva, Saint-Petersburt State University, Russia Ed Noyons University of Leiden, the Netherlands José Miguel Baptista Nunes, Sun Yat-Sen University, China Han Woo Park, Yeung Nam University, South Korea Qing Qian, Institute of Medical Information/Medical Library, CAMS, China Jian Qin, Syracuse University, USA Elias Sanz-Casado, University Carlos III de Madrid, Spain Zhesi Shen, National Science Library, the Chinese Academy of Scienes, China Gunnar Sivertsen, Nordic Institute for Studies in Innovation, Research and Education, Norway Neil Smalheiser, University of Illinois at Chicago, USA Xinning Su, Nanjing University, China Sugimoto Shigeo, University of Tsukuba, Japan Tan Sun, Agriculture Information Institute, CAAS, China Li Tang, Fudan University, China Mike Thelwall, University of Wolverhampton, UK Lili Wang, Maastricht University, the Netherlands Yuefen Wang, Tianjin Normal University, China Fang Wang, Nankai University, China Jevin West, Washington University, USA Dietmar Wolfram, University of Wisconsin-Milwaukee, USA Dan Wu, Wuhan University, China Jinshan Wu, Beijing Normal University, China Yishan Wu, Chinese Academy of Science and Technology for Development, China Erjia Yan, Drexel University, USA Guoliang Yang, Institute of Science and Development, Chinese Academy of Sciences, China Ying Ye (Fred Y. Ye), Nanjing University, China Marcia Lei Zeng, Kent State University, USA Lin Zhang, Wuhan University, China Zhixiong Zhang, National Science Library, CAS, China Dangzhi Zhao, University of Alberta, Canada Yuxiang Zhao, Renmin University, China Contact: Editorial Office National Science Library, Chinese Academy of Sciences 33 Beisihuan Xilu, Haidian, Beijing 100190, P.R. China Tel(fax): +86-10-82627304 Email: <A href="mailto:jdis@mail.las.ac.cn">jdis<A href="mailto:chinalibraries@mail.las.ac.cn">@mail.las.ac.cn</A></A> Website: <A href="http://www.jdis.org/">www.jdis.org</A> Publisher De Gruyter Poland Bogumiła Zuga 32A Str. 01-811 Warsaw, Poland T: +48 22 701 50 15

Journal of Data and Information Science

Open Peer Review in Scientific Publishing: A Web Mining Study of PeerJ Authors and Reviewers

Peiling Wang,Peiling Wang
Sukjin You,Sukjin You
Rath Manasa and Rath Manasa
Dietmar Wolfram Dietmar Wolfram

Published Online: 22 Aug 2017

Page range: 112 - 112

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