As agricultural production, management, operations, and services enter the big data era, standardization is becoming increasingly important in ensuring the comparability between the collected results generated by diverse devices and instruments, compatibility between multi-source data, integrability between multiple types of data analysis systems, the quality of agricultural products at a global scale, and the coherence between different production and management processes. This article summarizes the domestic and foreign standards in the field of agricultural big data. There are currently few standards and norms that can directly guide the development of agricultural big data. Research studies for a big data standards framework are critically needed to guarantee and promote the continuous and in-depth development of agricultural big data applications. This paper draws on the methods proposed by the International Organization for Standardization and International Electrotechnical Commission to analyze the standard system for a framework from the perspectives of enterprice, information, computation, engineering, and technology. From informational and computational perspectives, the needs in developing agricultural big data standards were analyzed, and a framework for an agricultural big data standard system is proposed. This framework contains standards for fundamental guidelines, general practice, and applications. Among these needs, the fundamental guidelines for agricultural big data are the basis for the formulation and coordination of agricultural big data standards, including national big data-related laws, regulations, policies, and national standards related to big data. The general standards for agricultural big data include four categories of common agricultural standards: i.e., agricultural big data foundation, agricultural big data collection and processing, agricultural big data management, and agricultural big data-sharing services. The agricultural big data application standards are the agriculture standards and regulations formulated for specific parts of the whole process of agricultural big data, such as agricultural elements and ownership information, agricultural production processes, and agricultural operation and management. The design of the agricultural big data standard system is a complex and huge systematic project that requires the participation of multisector and multidisciplinary personnel, and it is one of the top priorities in agricultural big data development.