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:
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.
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.
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.
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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.