Big Data Mining and Analytics

ISSN 2096-0654 e-ISSN 2097-406X CN 10-1514/G2
Editors-in-Chief: Yi Pan, Weimin Zheng
Open Access
Journal Home > Notice List > CFP-Special Issue on AI-enhanced Big Data Governance
Release Time:2024-03-12 Views:325
CFP-Special Issue on AI-enhanced Big Data Governance

In the modern era of technological advancement, big data has become a pivotal asset for organizations across various domains, providing valuable insights and driving innovation. However, effective management and utilization of vast amount of data poses significant challenges, highlighting the crucial importance of big data governance.

Big data governance encompasses a broad range of technical components, each being crucial in ensuring the integrity, security, and reliability of the data. Firstly, data integration techniques are essential for combining disparate data sources into a unified repository, enabling comprehensive analysis and insight discovery. Data quality management ensures that data is accurate, consistent, and trustworthy, avoiding the pitfalls of working with incorrect or outdated information. Furthermore, data security and privacy are paramount concerns in big data governance.

With the advent of Artificial Intelligence (AI), there is now an opportunity to revolutionize traditional data governance practices and unlock the full potential of big data. AI algorithms can automate data management tasks, improve data quality through intelligent data cleansing and validation techniques, and enhance data security by detecting and responding to threats in real-time. Moreover, AI-driven analytics can unlock hidden patterns and insights buried deep within big data.

This special issue is organized to bring together a wealth of research and practical applications that delve into the intersection of AI and big data governance. It highlights the importance of data governance in maximizing the value of big data and showcases how AI technologies can revolutionize data management practices. By presenting a holistic view of the current landscape in AI-enhanced big data governance, this special issue will provide readers with a comprehensive understanding of the current landscape and future trends in AI-enhanced big data governance.

Prospective submissions may fall into, but are not limited to the following topics:

  • Metadata Management and Master Data Management
  • Data Discovery and Acquisition
  • Big Data Integration
  • Data Preparation Utilizing Large Language Models
  • Big Data Quality Assessment and Data Cleaning
  • Big Data Ownership Determination and Data Flow
  • Big Data Trading and Pricing
  • Data Association and Deep Mining
  • Information Protection and Data Security

Authors are requested to submit their full research papers complying with the general scope of the journal. Submitted papers will undergo peer review before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.

SUBMISSION GUIDELINES

Papers submitted to this journal for publication must be original and must not be under consideration for publication in any other journals. Prospective authors should submit an electronic copy of their completed manuscript to https://mc03.manuscriptcentral.com/bdma with manuscript type “Special Issue on AI-enhanced Big Data Governance”.

IMPORTANT DATES

Deadline for submissions: December 31, 2024

GUEST EDITORS

Prof. Hongzhi Wang, Harbin Institute of Technology, China. E-mail: wangzh@hit.edu.cn

Prof. Jianzhong Qi, The University of Melbourne, Australia. E-mail: jianzhong.qi@unimelb.edu.au

Prof. Xiaoou Ding, Harbin Institute of Technology, China. E-mail: dingxiaoou@hit.edu.cn