The traditional data governance system is mainly oriented to structured data and serves the enterprise's decision-making operations (Business Intelligence). For a long time, the large amount of unstructured data in enterprises has not been well managed and utilized. With the rapid development of general artificial intelligence, unstructured data such as text and pictures have become the core elements of large model training. The scale and quality of data sets have become key factors in promoting the progress of AI technology. According to statistics, the latest large model training uses The size of the data set is nearly a thousand times that of the training data five years ago. The industry has also proposed the concept of data-centered (Data-Centric AI) artificial intelligence development, and the boundaries between data and algorithms have become more blurred. However, the exploration of data governance for artificial intelligence has just begun, and its concepts and connotations are still changing. A good theoretical framework and practical methods have not yet been formed. Data governance for general artificial intelligence, in addition to focusing on data quality issues in large model training, There is also a need to address the challenges of security and privacy protection, and there is an urgent need to establish governance capabilities for synthetic data to eliminate risks such as copyright infringement and discrimination.
This journal is soliciting papers with the theme of "Artificial Intelligence Data Governance", focusing on displaying technical and theoretical research results in artificial intelligence data governance. , including: high-quality data set construction, multi-modal data management, unstructured data management, artificial intelligence data engineering, large model data security and privacy security, artificial intelligence data ethics, etc.
Special Topic:Artificial Intelligence Data Governance
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Scope of call for papers
Includes but is not limited to the following topics:
1) Artificial intelligence data governance issues and theoretical framework
2) Artificial intelligence data set quality evaluation system
3) Large model data security and privacy protection practices
4) Artificial intelligence data governance technology and engineering practice
5) Multimodal data governance
6) Intelligent data governance technology practice
7) Synthetic data management practices
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Call for Papers
1. The manuscript should be the author’s original scientific research result, the data should be authentic and reliable, and have important academic value and promotion and application value; it should not have been published or read in publicly distributed publications or conferences at home and abroad, nor should it have been published in other publications or conferences. During the review process, there is no problem of multiple submissions.
2. Manuscripts should include Chinese and English title, author information, abstract, keywords, fund project name, references, Chinese text and author introduction (including photos). Manuscripts must be submitted in Word documents.
3. When submitting, please indicate the author's contact information (email, phone number, mailing address) and "Submission on the topic of 'Artificial Intelligence Data Governance'" and the direction.
4. Manuscripts are submitted through the official website of "Big Data"http://www.j-bigdataresearch.com.cn/, Other submission methods are not currently supported. Please refer to the website instructions for submission instructions and manuscript templates.
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important dates
Deadline for submission of papers: April 30, 2024
Review completion date: June 30, 2024
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Big data journal
"Big Data Research (BDR)" bimonthly is a journal supervised by the Ministry of Industry and Information Technology of the People's Republic of China, sponsored by the People's Posts and Telecommunications Publishing House, under the academic guidance of the Big Data Expert Committee of the China Computer Society, and published by Beijing Xintong Media Co., Ltd. , has been successfully selected into the core journals of Chinese science and technology, the Journal of the China Computer Federation, the recommended Chinese science and technology journals by the China Computer Federation, as well as the hierarchical catalog of high-quality scientific and technological journals in the field of information and communication, the hierarchical catalog of high-quality scientific and technological journals in the field of computing, and has been rated as a national The most popular journals in the "Comprehensive Humanities and Social Sciences" discipline of the Academic Journal Database of the Philosophy and Social Sciences Documentation Center.
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