期刊档案
Big Data
— · ISSN 2167-6461 · COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
数据可追溯 · letpub-v6 · 更新于 2026-08-25期刊简介
研究范围与定位
Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government.Big Data coverage includes:Big data industry standards,New technologies being developed specifically for big data,Data acquisition, cleaning, distribution, and best practices,Data protection, privacy, and policy,Business interests from research to product,The changing role of business intelligence,Visualization and design principles of big data infrastructures,Physical interfaces and robotics,Social networking advantages for Facebook, Twitter, Amazon, Google, etc,Opportunities around big data and how companies can harness it to their advantage.
结构化分区
学科分区明细
不同版本、大类与小类分别展示,不将不同评价口径合并为一个分区值。
《新锐期刊分区表》( 2026年3月发布)
2026-03 · 3 个学科记录
| 类别 | 学科 | 分区 |
|---|---|---|
| 大类 | 计算机科学 | 4区 |
| 小类 | 计算机:跨学科应用COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | 4区 |
| 小类 | 计算机:理论方法COMPUTER SCIENCE, THEORY & METHODS | 4区 |
期刊分区表( 2025年3月升级版)
2025-03 · 3 个学科记录
| 类别 | 学科 | 分区 |
|---|---|---|
| 大类 | 计算机科学 | 4区 |
| 小类 | 计算机:跨学科应用COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | 4区 |
| 小类 | 计算机:理论方法COMPUTER SCIENCE, THEORY & METHODS | 4区 |
期刊分区表( 2023年12月旧的升级版)
2023-12 · 3 个学科记录
| 类别 | 学科 | 分区 |
|---|---|---|
| 大类 | 计算机科学 | 4区 |
| 小类 | 计算机:跨学科应用COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | 4区 |
| 小类 | 计算机:理论方法COMPUTER SCIENCE, THEORY & METHODS | 4区 |
期刊档案
出版与身份
- 期刊ISSN
- 2167-6461
- E-ISSN
- 2167-647X
- 是否OA开放访问
- No
- 通讯方式
- 140 HUGUENOT STREET, 3RD FL, NEW ROCHELLE, USA, NY, 10801
- 出版商
- Mary Ann Liebert Inc.
- 出版国家或地区
- UNITED STATES
- 出版语言
- English
- 出版年份
- 0
期刊档案
研究范围
- 期刊简介
- Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government.Big Data coverage includes:Big data industry standards,New technologies being developed specifically for big data,Data acquisition, cleaning, distribution, and best practices,Data protection, privacy, and policy,Business interests from research to product,The changing role of business intelligence,Visualization and design principles of big data infrastructures,Physical interfaces and robotics,Social networking advantages for Facebook, Twitter, Amazon, Google, etc,Opportunities around big data and how companies can harness it to their advantage.
- 涉及的研究方向
- COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
期刊档案
指标与活跃度
- 2025-2026最新IF(数据来源于网友提供)
- 注册或登录后,查看IF
- 实时影响因子
- 截止2026年5月06日:1.83
- 2025-2026自引率
- 5.0%点击查看自引率趋势图
- 五年IF(数据来源于网友提供)
- 4.196数据由网友[湖泊purple42]收集提供
- h-index
- 17
- CiteScore ( 2026年6月最新版)
- CiteScoreSJRSNIPCiteScore排名6.800.4540.822学科分区排名百分位大类:Decision Sciences小类:Information Systems and ManagementQ146 / 222 79% 大类:Decision Sciences小类:Computer Science ApplicationsQ2261 / 1022 74% 大类:Decision Sciences小类:Information SystemsQ2138 / 519 73%
- 年文章数
- 15点击查看年文章数趋势图
- Gold OA文章占比
- 2.56%
- 研究类文章占比:文章 ÷(文章 + 综述)
- 100.00%
期刊档案
分区、收录与风险
- WOS期刊JCR分区 ( 2025-2026年最新版)
- 注册或登录后,查看WOS分区等级
- 期刊分区表预警名单
- 2026年03月发布的新锐学术版:不在预警名单中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
- SCI期刊收录coverage
- Science Citation Index Expanded (SCIE) (2020年1月,原SCI撤销合并入SCIE,统称SCIE)Scopus (CiteScore)
- PubMed Central (PMC)链接
- 访问官方页面 ↗
期刊档案
投稿与评审
- 期刊官方网站
- 访问官方页面 ↗
- 平均审稿速度
- 网友分享经验:
- 平均录用比例
- 网友分享经验:
来源与统计口径
来源:LetPub 原始详情页 ↗。投稿经验仅展示聚合统计,不公开第三方正文或用户标识。当前聚合样本:暂无。