Journal Title：Journal Of Data And Information Science

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

數據與信息科學雜志致力于研究和應用大數據理論、方法、技術、服務、基礎設施，為決策和政策制定提供知識發現支持。基本重點是基于大數據、以分析為中心、以知識發現為驅動、以決策為支撐。特別致力于知識發現，以檢測和預測研究、創新、商業、政治、安全、媒體和通信以及社會發展中的結構、趨勢、行為、關系、演變和中斷，其中大數據可能包括元數據或完整內容數據、文本或非文本數據、結構化或非結構化數據、領域特定或跨領域數據以及動態或交互式數據。

主要感興趣的領域是：

（1）基于大數據的數據挖掘、知識發現和信息學的新理論、方法和技術，包括但不限于科學計量學、通信分析、社交網絡分析、技術和行業分析、競爭情報、知識圖譜、基于證據的政策分析和預測分析。

（2）開發或改進能夠支持知識組織和復雜分析的知識基礎設施的新方法、架構和設施，包括但不限于本體構建、知識組織、語義鏈接數據、知識集成和融合、語義檢索、領域特定知識基礎設施和語義科學。

(3) 將知識分析和知識發現嵌入實際運營、服務或管理過程的新機制、方法和工具，包括但不限于知識輔助的科學發現、數據挖掘驅動的學習、通信和管理中的智能工作流。

具體主題領域可能包括：

知識組織

知識發現和數據挖掘

知識集成與融合

語義網度量

科學計量學

分析和診斷信息計量學

競爭情報

預測分析

社交網絡分析和度量

語義和交互式分析檢索

基于證據的政策分析

智能知識生產

知識驅動的工作流管理和決策

知識驅動的協作及其管理

具有知識融合和分析的領域知識基礎設施

數據和信息服務的開發

Journal Of Data And Information Science由Beijing Magtech Co.ltd出版商出版，收稿方向涵蓋INFORMATION SCIENCE & LIBRARY SCIENCE全領域，此刊是中等級別的SCI期刊，所以過審相對來講不是特別難，但是該刊專業認可度不錯，仍然是一本值得選擇的SCI期刊 。平均審稿速度約about 28 days from submission to first decision. 15 Weeks ，影響因子指數1.5，該期刊近期沒有被列入國際期刊預警名單，廣大學者值得一試。