Journal Of Data And Information Science

杂志介绍

Journal Of Data And Information Science杂志介绍

《Journal Of Data And Information Science》是一本以English为主的开放获取国际优秀期刊，中文名称数据与信息科学杂志，本刊主要出版、报道管理学-INFORMATION SCIENCE & LIBRARY SCIENCE领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为1.5，最新CiteScore 指数为3.5。

英文介绍

Journal Of Data And Information Science杂志英文介绍

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