Abstract:

Based on data reusability and low-carbon computing, this paper redefines the term data for algorithm. With techniques like data preprocessing, pre-training, desensitization and encryption, a proper standard system is built to produce normalized ways of management and application. According to the properties and values of data for algorithm, this paper introduces FAIRDNS principle and offers suggestions on its research boundary, classification and storage methods. Then, it provides the thoughts about standardization, repository and ecosystem.

Key words: data for algorithm, low-carbon computing, standardization