Large agricultural data and new opportunities for development

Recently, two things about large data are worthy of attention: first, in the middle of May, our school set up a large agricultural data research center. The second is the middle of June, the first domestic agricultural data industry technology Innovation Strategic Alliance was established in our school. These two events will have an important impact on the next development of the school, and also bring new opportunities for the development of the subject.


at present, large data research and application in the domestic just started, agricultural large data related research has not been deeply involved, it should be said that our school in this area to grab the first mover. We must cherish and grasp this opportunity, and actively carry out relevant research, as soon as possible to achieve results.


a full understanding of the role and influence of large data on future development


What is big data? What's the use of big data? This is the first question most people ask. Large data is a concentrated reflection of the new generation of information technology, is a strong application-driven service domain, is unable to use the existing software tools to extract, store, search, share, analysis and processing of a vast, complex data collection. The characteristics of large data, the industry commonly used five V to represent: first, the large amount of data (Volume), the second is fast processing speed (velocity), the third is more data types (produced), four is the value of large (values), five is high precision (veracity).


in fact, large data is not simply referring to the form of "digital" information. With the rapid development of computer technology, information technology, network technology (mainly cloud computing and the development of modern network technology), all over the world, various industries, units every day, including digital, text, video, audio and so on, such as the mass of information, these vast amounts of information collectively referred to as large data. In the ocean of large data, it is one of the important contents of large data application to use "Shari" technology to distill the useful data. Large data application technology can be divided into the following steps: Database collection and mining, data quality screening and correction, information processing (mathematical model establishment and correction), large data analysis and the formation of results. Of course, the issue is a prerequisite to solve the problem, large data research is based on the economic and social development of the problem to set up a database, and the final analysis of the large data results are to solve the economic and social problems (also known as customer) services. Large Data application research the whole chain needs a team-type research to complete, at least the following elements: Customers (ask questions), it experts, mathematicians, analysts, and so on. These steps (areas) can be performed in tandem or separately, such as establishing a database for a particular industry.


The use of large data can be summarized as follows: The use of information technology and computational methods of progress, the different formats, different business areas of the massive data into a standard unified data source, analysis and application, then produce great economic and social value. The larger purpose of large data is to predict the occurrence of an event in the future based on the established model, and to make human intervention to develop it in the desired direction. Take the weather forecast, as the saying goes, "There are accidents in the sky." Now we can measure it. This is the role of large data. Large data is first used in meteorology. It is now possible to establish models of weather identification by using computer operations and meteorological data over the past 60 years, and then comparing these models with current climatic conditions and using predictive analysis for weather forecasting. This new model of predicting the future through the past, its prediction time longer, more accurate, the longest can be 40 days in advance to generate hot and cold weather probability. In the dry season, sometimes cloudy, a variety of rainfall elements are basically available, but it is not raining, this may be due to the formation of raindrops, the lack of condensation nuclei, which can be human intervention-artificial rainfall (cloud in dry ice or silver iodide). This principle can now be used in the management decision support of economic development. We can forecast the future economic gross trend according to the analysis of economic data, and carry out the correct human intervention (regulation) at the critical moment. For example, the State Administration for industry and commerce according to the relevant data of registration of enterprises, through a series of research and analysis methods to generate the capital activity (CRI) index, and this index and the main indicators of economic gross domestic growth and revenue change rate are positive correlation, and the regularity before the two indicators several cycles. The scientific prediction of economic total has played a positive role in supplementary verification, and provided scientific basis for the timing and means of macro-control.


In today's society, data has become as important strategic resource as natural resources and human resources. How to use data resources to explore knowledge, enhance efficiency, promote innovation, make it serve for national governance, enterprise decision and even personal life, is the goal of large data technology. Now some countries have taken more possession of data, scientifically analyzing and refining data, as an important opportunity to compete for the commanding heights of future development. More recently, the "PRISM" surveillance scandal that came out of Snowden is actually a case of America using big data to guarantee its national interests, and it fully illustrates the intensification of the war on defence and national security. We must have the awareness of data mining and protection. China as the world's largest population, the amount of data produced is also very large, but the real data stored in North America is only 7%, Japan's 60%. More than half of the country's data is not properly protected, there is a risk of data leakage, the need to continue to rescue mining and protection. In recent years, China has also attached great importance to the research and utilization of large data. Not long ago, the Ministry of Science and Technology, Ministry of Education and other special conferences held large data for the future of China's orderly development of large data technology, pragmatic push related industry development combed the train of thought. It can be said that a data-king of the Big Data era has come.


second, carry out agricultural large data research, improve scientific research level and service ability


Agricultural Large data is the practice of large data ideas, techniques and methods in the field of agriculture. Agricultural data related to farmland, breeding, sowing, fertilization, plant protection, harvesting, storage and transportation, agricultural products processing, marketing, livestock production and other links, is cross-industry, multidisciplinary data analysis and excavation, food security and food safety is of great significance.


the characteristics of large agricultural data include the following:


from the field, take the agricultural field as the core (covering planting, forestry, animal husbandry and other sub-industries), and gradually expand to the relevant upstream and downstream industries (seeds, feed, fertilizers, agriculture, agricultural machinery, grain and oil processing, fruit and vegetable processing, animal products processing industry, etc.), and integrate macro-economic background data, Import and export data, price data, production data, and even meteorological data.


second, from the point of view of the region, taking the domestic regional data as the core, drawing on the international agricultural data as an effective reference, not only the national level data, but also the provincial and municipal data, and even the city-level data, to provide the basis for accurate regional research.


three is from the grain size, not only includes statistical data, but also includes the basic information of the agricultural economy, investment information, shareholder information, patent information, import and export information, recruitment information, media information, GIS coordinate information.


From the point of view of professionalism, we should implement it in a step-by-step way, first of all, to construct professional data resources in agricultural field, and then to plan professional sub domain data resources gradually. Dynamic monitoring data, such as cultivated land tenure, soil environmental protection, market supply and demand information, etc., for animal breeds such as pig, broiler, hen, beef cattle, cow, mutton sheep and other dynamic monitoring data, even including bioinformatics research.


we have produced a lot of data in the years of agricultural production and research. The integration and future excavation and use of these data will play an extremely important role in the development of modern agriculture. There are many problems in agricultural field, such as food security, soil management, pest and disease prediction and control, animal and plant breeding, agricultural structure adjustment, agricultural product price, agriculture and sideline products consumption, small town construction and other fields, can be predicted and intervened through the application research of large data. The combination of large data application and related scientific research in agriculture can provide new methods and new ideas for agricultural scientific research, government decision, agriculture enterprise development, etc.


as a higher agricultural university, it has broad prospect to carry out agricultural large data research. We have accumulated a large amount of data in the long run of practice and scientific research, and government departments have retained the census and statistics of agriculture for many years. Most of this data is dormant in the database and does not play its part. If these data are used in large data technology, it will play an inestimable role in directing production and scientific research. We should combine the characteristics of school running, vigorously carry out large data research. To give full play to the advantages of the alliance and the school's disciplinary advantages, talent advantages, in the study to form the characteristics and improve the level. At present, should focus on the following areas to do a good job.


First, to be a good government think-tank. It is an important function of colleges and universities to provide guidance for the development of production and to make good staff for government decision-making. Many of the past decisions are based on experience, "Follow the Feeling", and with large agricultural data to guide, will provide scientific and accurate basis for production development and government decision-making. For example, vegetable cheap injury of agricultural events in recent years, has seriously affected the income of farmers, dampened the enthusiasm for production. Because the information is not spirit, lack of guidance, what the market is selling, farmers on what kind of, such as the discovery of oversupply, product unsalable is too late. The integration of weather information, food safety, consumer demand, production costs, market stalls and other data and scientific analysis, can more effectively predict the trend of agricultural prices, to help farmers advance, and help the Government to introduce guidance measures. For example, food security issues, including the number of arable land, farmland quality, climate, crop varieties, cultivation techniques, average yield, industrial structure adjustment, agricultural prices, agricultural machinery, production costs, mode of operation, food processing, international market prices and other factors, if the data can be analyzed to establish a model, will be able to make a judgment on food production, timely warning, to help the government to take action. To carry out the research and application of large data, we should first become a think-tank of agriculture in Shandong province, and will become a think-tank for the development of agriculture in the future with the deepening of research. Our Alliance has 6 provincial departments, which cover almost all aspects of agriculture, and can provide large amounts of data and other support related to farming. We need to develop research and production on large data, the market sales, the new countryside construction and so on closely unifies, strengthens the basic data construction, the consummation data collection system, the establishment data monitoring system, the continuous collection related data, and establishes the mathematics model for the specific topic, predicts certain aspect development tendency, for the government formulation policy, Macro-control provides the basis. The influence of the school can be enhanced only by the continuous contributions and achievements in social services.


Second, to provide support for enterprises. The combination of politics, production, study and research is an important feature of the Alliance of technological innovation in agricultural large data industry, and it is also an important objective for us to carry out research. An enterprise's products, when the need to upgrade, when the product market saturation, how to adjust the market structure, and so on, can be used to analyze and forecast the means of large data to provide advisory guidance to enterprises. For example, fertilizer production, predicting when the demand for organic fertilizer will exceed the chemical fertilizer, enterprises can prepare for transformation in advance, cultivate organic fertilizer industry. The advantage of large data lies in: Discovering Opportunities and optimizing implementation, assisting decision-making, promoting business development, and assessing risk. Such analysis, prediction and evaluation can be carried out in aquaculture, seed industry, food processing, plant protection and other industries. For example, through the weather, crop growth, pesticide use, natural enemies and other data analysis, can be made to forecast the occurrence of pests and diseases, but also can guide the production of pesticide enterprises. These analyses are strategic and have important guiding significance to the development of enterprise decision. We have a group of well-known enterprises in the league, involving seeds, fertilizers, food processing, aquaculture and other industries, the relevant professional experts to go out of the school, understand the needs of enterprises, strengthen cooperation with enterprises, in cooperation to broaden their horizons, improve the level and ability to serve the community.


Third, to provide a platform for the promotion and transformation of disciplines. Large data can greatly enhance the academic level of various disciplines. Here refers to the "academic" connotation, in the previous article I have made a statement. I often mention the "education-oriented, academic supremacy" is the requirements of our staff. Whether teaching, scientific research or social services, we need to have real skills, real skills, really academic. People who are not good at learning, accepting, and applying new knowledge are not really capable. We should not only use the knowledge of large data in scientific research, but also in teaching. Now it seems, "learn physics, traveled all over the world are not afraid of" the argument is still very far-sighted. The basis of most of our school's disciplines is physics, without which our discipline will be subject to development constraints. We have been emphasizing the use of information science and life sciences to upgrade traditional disciplines. In the use of life sciences to upgrade the traditional disciplines, we have made progress, now the study of agricultural science can achieve molecular level, but in the use of information science to upgrade the traditional disciplines have not essay, no way to find a combination. And the large data is the combination of information science and traditional discipline brings great opportunities and potential. The explosive growth of data brings new methods and new Horizons to the discovery of scientific research. Like the microscope that was invented by humans 4 centuries ago, the microscope advances human observation and measurement of nature to the level of "cell", bringing about historical progress and revolution to human society. And the big data will be our next "microscope" to observe and detect nature. This new microscope will once again expand the scope of human scientific exploration and improve the level of innovation. We have accumulated a great deal of data in previous studies, the value of which is far from being shown in the paper, because we do not recognize its other values. But if these data and other similar studies are collected as a whole, it is very likely that some laws will be discovered or predicted, and further research can be conducted under the guidance of such predictions. For example, through the data Analysis database integrated by the Ministry of Agriculture, the NDRC and the customs-related data, I proofread the recent changes in the number of dairy cows and found that the sale data of the adult cows are highly correlated with the cost profit margin of the beef, which is always the former two analysis cycle. This has played a very good supporting role in the formulation and macro-control of the related dairy cattle and beef cattle breeding policy.


Four, provide the means to improve the management level. The research and application of large data are of great value not only in scientific research and social services, but also in management and other aspects. Our management decision-making, man-made factors accounted for a large extent, many rely on experience, some by feeling, rarely based on scientific data and models on the basis of the inevitable one-sided, error, also prone to policy discontinuity. In order to make scientific decision, management should be based on data analysis. Our country in the past 20 years of information construction, precipitated a lot of valuable data. These data are the digitized records of the whole social economic activity, and are the basis of management and decision-making. Once the "data-driven decision method" is implemented, our management will be more efficient, more open and more accountable, and data analysis can effectively monitor policy implementation and correct deviations and errors in a timely manner. Each of our management departments should be combined with the application of large data, the development of the Department's relevant management plan. For example, in the field of talent training, we can make the evaluation system of teaching quality, in human resources management, we can predict and evaluate the development potential of new recruits, and make a more scientific evaluation of staff performance. In financial management, we can optimize investment plan and establish risk early warning; in the management of scientific research, We can explore the regularity of various scientific research funds and achievements in our school and various colleges, and serve for scientific research planning. In alumni work, we can set up alumni database and analyze the law of Alumni's growth and development, and provide the basis for the reform of school teaching and so on. Our teachers, managers, as long as a certain aspect of the management of interest, willing to in-depth study, can be combined with the relevant professionals, with large data means for in-depth analysis. In the research and application of large data, we all stand on the same starting line, as long as you are willing to study, everyone has a good chance, everyone can become a certain aspect of the experts, everyone's value can be fully played.


Third, strengthen cooperative innovation and improve the research level of large agricultural data


The whole chain of agricultural data research applications cannot be accomplished by single-handedly, and a multidisciplinary team must be formed. The study of a problem, first of all the relevant professional personnel to raise questions, and computer, mathematical modeling and other experts to carry out a joint, data mining, sorting, screening, establishing a database and mathematical models, and then to verify. It's like we're looking for water. With the demand for water, it is necessary to find water (which can be likened to data sources and data quality screening and correction), to build a reservoir (comparable to a database), and then to plan the best diversion routes and build canals (comparable to data analysis and modelling). In this process to be involved in a number of areas, team members have to work together to complete the project. Of course, in the specific work of the chain is also carried out, such as the establishment of a database or mathematical models, and so on, each study can produce significant results. Our newly formed agricultural large data industry Technology Innovation Alliance is an open platform, open to every subject of our school, can also cooperate with the Scientific research Unit and enterprise personnel in the alliance to declare and complete the project.


to promote the development of large agricultural data, seize the opportunity, the school is to raise funds, the establishment of large-scale agricultural data research special funds, mainly for agricultural large data research software, hardware and database construction, research projects, the construction of the laboratory, and now has purchased 11 databases, and will continue to enrich and improve. Now the platform has been set up, we need to actively use their brains, combined with the field, the professional, the department's work, make full utilization of agricultural large data this platform, to carry out innovative research. Both teachers and managers should understand the relevant knowledge of large data, enhance the awareness of large data, become close friends with large data and think about our work with the view of large data. We also need to establish data precipitation and collection, data application and data sharing awareness, to carry out relevant research, the introduction of large-scale agricultural data application results. To use solid work to prove that our large agricultural data platform has the strength and connotation, is worthy of trust and reliance.


Although we are currently in the forefront of the study of agricultural data, but still need to enhance the sense of urgency, to broaden research ideas, increase research efforts, to strengthen cooperation with government departments, enterprises, scientific research units, brothers and universities, to play their own advantages and synergy , we also need to cultivate and introduce a large number of large-scale data research and development of high-level personnel, building research teams, and constantly improve research strength, as soon as possible to produce research results, for the development of modern agriculture to provide more intelligence and results support, in order to improve the level of school education to make greater contributions.