Characteristics of Agricultural Big Data

Agricultural big data is a collection of data with wide sources, diverse types, complex structure and potential value. It is difficult to process and analyze with the usual methods after integrating its own characteristics such as regional, seasonal, diverse and periodic agriculture.

The characteristics of agricultural big data conform to the five characteristics of big data, namely, large data volume, fast processing speed, diverse data types, high value and high precision. Includes the following contents:

(1) From the field point of view, it takes the agricultural field 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 integrated the data of macroeconomic background, 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 of agricultural economic entities, investment information, shareholder information, patent information, import and export information, recruitment information, media information, GIS coordinate information, etc.

(4) From a professional point of view, it should be implemented step by step. First of all, we should build professional data resources in the agricultural field, and then plan professional data resources in different fields step by step, such as professional monitoring data of pigs, broilers, laying hens, beef cattle, dairy cows and mutton sheep of domestic animals.