Journal of Data and Information Science
SCI一区
EI同步收录
月刊
高认可度
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期刊基础介绍
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
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
期刊核心参数
通讯方式
Tel: +86-10-82627304 Fax: +86-10-82627304 E-mail: jdis@mail.las.ac.cn Add:P.O. Box 2704, Beijing 100190 P.R. China
涉及的研究方向
INFORMATION SCIENCE & LIBRARY SCIENCE-
出版国家或地区
China
出版语言
English
年文章数
36
PubMed Central (PMC)链接
CITESCORE
| CiteScore | SJR | SNIP | CiteScore排名 | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3.70 | 0.514 | 1.058 |
|
WOS期刊JCR分区
WOS分区等级:2区| 按JIF指标学科分区 | 收录子集 | JIF分区 | JIF排名 | JIF百分位 |
| 学科:INFORMATION SCIENCE & LIBRARY SCIENCE | ESCI | Q2 | 66/166 |
|
| 按JCI指标学科分区 | 收录子集 | JCI分区 | JCI排名 | JCI百分位 |
| 学科:INFORMATION SCIENCE & LIBRARY SCIENCE | ESCI | Q2 | 66/166 |
|
期刊分区表预警名单
2025年03月发布的2025版:不在预警名单中2024年02月发布的2024版:不在预警名单中
2023年01月发布的2023版:不在预警名单中
2021年12月发布的2021版:不在预警名单中
2020年12月发布的2020版:不在预警名单中
中科院2025年3月升级版
点击查看中国科学院期刊分区趋势图| 大类学科 | 小类学科 | Top期刊 | 综述期刊 | ||||
|---|---|---|---|---|---|---|---|
| 计算机科学 2区 |
| 否 | 否 |
中科院2023年12月旧的升级版
| 大类学科 | 小类学科 | Top期刊 | 综述期刊 | ||
|---|---|---|---|---|---|
| 管理学 3区 |
| 否 | 否 |