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:
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):
Knowledge discovery and data mining
Knowledge integration and fusion
Semantic Web metrics
Analytic and diagnostic informetrics
Social network analysis and metrics
Semantic and interactively analytic retrieval
Evidence-based policy analysis
Intelligent knowledge production
Knowledge-driven workflow management and decision-making
Knowledge-driven collaboration and its management
Domain knowledge infrastructure with knowledge fusion and analytics
Training for data & information scientists
Development of data and information services
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).
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.
The editorial board is participating in a growing community of Similarity Check System's 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.
Co-Editors-in-Chief Xiaolin Zhang National Science Library, the Chinese Academy of Sciences, China
Ronald Rousseau University of Leuven, Belgium
Ying Ding Indiana University, USA
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 Per Ahlgren KTH Royal Institute of Technology, Sweden
Judit Bar-Ilan Bar-Ilan University, Israel
Christine L. Borgman University of California, Los Angeles, USA
Kevin Boyack SciTech Strategies Inc., USA
Chaomei Chen Drexel University, USA
Dar-Zen Chen National Taiwan University, Taiwan, China
Ling Chen Peking University, China
Cinzia Daraio Sapienza University of Rome, Italy
Nees-Jan van Eck Leiden University, the Netherlands
Haiyan Hou Dalian University of Technology, China
Tao Jia Southweat University, China
Renaud Lambiotte University of Namur, Belgium
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
Everard Noyons University of Leiden, the Netherlands
José Miguel Baptista Nunes Sun Yat-Sen University, China
Han Woo Park Yeung Nam University, South Korea
Jian Qin Syracuse University, USA
Qing Qian Institute of Medical Information/Medical Library, CAMS, China
Gunnar Sivertsen Nordic Institute for Studies in Innovation, Research and Education, Norway
Min Song Yonsei University, South Korea
Neil Smalheiser University of Illinois at Chicago, USA
Xinning Su Nanjing University, China
Tan Sun Agriculture Information Institute, CAAS, China
Jie Tang Tsinghua University, China
Li Tang Fudan University, China
Mike Thelwall University of Wolverhampton, UK
Yuefen Wang Nanjing University of Science and Technology, China
Fang Wang Nankai University, China
Jevin West Washington University, USA
Dietmar Wolfram University of Wisconsin-Milwaukee, USA
Dan Wu Wuhan University, China
Yishan Wu Chinese Academy of Science and Technology for Development, China
Feng Xia Dalian University of Technology, China
Erjia Yan Drexel University, USA
Liying Yang National Science Library, CAS, China
Ying Ye (Fred Y. Ye) Nanjing University, China
Jan Youtie Georgia Institute of Technology, USA
Marcia Lei Zeng Kent State University, USA
Lin Zhang Wuhan University
Zhixiong Zhang National Science Library, CAS, China
Dangzhi Zhao University of Alberta, Canada
Yuxiang Zhao Nanjing University of Science and Technology, China
Donghua Zhu Beijing Institute of Technology, 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: email@example.com Website: www.jdis.org
Publisher De Gruyter Poland Bogumiła Zuga 32A Str. 01-811 Warsaw, Poland T: +48 22 701 50 15