雜志介紹

Journal Of Data And Information Science雜志介紹

《Journal Of Data And Information Science》是一本以English為主的開放獲取國際優秀期刊，中文名稱數據與信息科學雜志，本刊主要出版、報道管理學-INFORMATION SCIENCE & LIBRARY SCIENCE領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為1.5，最新CiteScore 指數為3.5。

英文介紹

Journal Of Data And Information Science雜志英文介紹

JDIS devotes itself to the study and application of the theories, methods, techniques, services, infrastructural facilities using big data to support knowledge discovery for decision & policy making. The basic emphasis is big data-based, analytics centered, knowledge discovery driven, and decision making supporting. The special effort is on the knowledge discovery to detect and predict structures, trends, behaviors, relations, evolutions and disruptions in research, innovation, business, politics, security, media and communications, and social development, where the big data 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 & 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 capable to 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, data mining driven intelligent workflows in learning, communications, and management.

Specific topic areas may include:

Knowledge organization

Knowledge discovery and data mining

Knowledge integration and fusion

Semantic Web metrics

Scientometrics

Analytic and diagnostic informetrics

Competitive intelligence

Predictive analysis

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

Development of data and information services