Authenticity characteristics of agricultural big data

1. From the field point of view, it takes agriculture as the core (covering sub-industries such as planting, forestry and animal husbandry) and gradually expands to related upstream and downstream industries (feed production, fertilizer production, agricultural machinery production, slaughtering industry, meat processing industry, etc.). ), and the integration of macroeconomic background data, including statistical data, import and export data, price data, production data, and even meteorological data.

2. Geographically, taking domestic regional data as the core and drawing lessons from international agricultural data as an effective reference. It includes not only national data, but also provincial and municipal data, even prefecture-level data, which provides a basis for accurate regional research.

3. In terms of granularity, it should include not only statistical data, but also basic information, investment information, shareholder information, patent information, import and export information, recruitment information, media information and GIS coordinate information.

4. From a professional point of view, it should be implemented step by step, that is, the construction of professional data resources in the agricultural field, and the data resources in professional sub-fields should be planned step by step, such as the professional monitoring data of pigs, broilers, laying hens, beef cattle, cows and mutton sheep.