The continuous innovation of science and technology has greatly expanded the research scale and the amount of data available. When the ordinary computing power is no longer enough to cope with the increasingly huge data analysis, the emerged cloud computing helps to solve the data bottleneck problem, improves the operation efficiency and points out a new direction for the future laboratory data analysis. Characteristics of natural science big data: high speed, large capacity and diversity. Big data can help us more accurately predict health trends and make population and regional specific analysis of diseases. Big data is the result of the rapid development of emerging technologies, such as gene sequencing. In turn, it also supports disease diagnosis and drug target screening, and helps personalized medicine.

In the era of big data, scientific research data needs to make breakthroughs in storage mode, technical architecture, shared transmission, global collaboration, efficient processing and so on. Local computing cluster is the foundation, and computing grid is the "cluster of clusters", which needs to integrate computing resources. Cloud computing pays more attention to the universality of the platform and improves resource utilization. It is a process of big science, big demand, big data, big computing and big discovery. It requires a variety of computing technologies and promotes the development of information technology, which is a complementary process.

The essence of artificial intelligence science and technology is to extend, simulate and develop some basic human functions through intelligent systems and intelligent machines. It is a new technology formed with the support of multi-disciplinary theories. Artificial intelligence technology is not only the inevitable product of the information age, but also the inevitable demand of the information society. For example, artificial intelligence technology will play a great role in the Internet, information education, information highway and so on.

Data mining is a step in database knowledge discovery. It is a process of searching information hidden in a large amount of data through algorithms. Data mining is usually related to computer science, and achieves the above objectives through statistics, online analysis and processing, information retrieval, machine learning, expert system (relying on past experience rules) and pattern recognition. Scientific database technology includes reasoning technology, searching technology, knowledge representation and knowledge base technology, induction technology, association technology, classification technology, clustering technology and so on. The three most basic technologies, namely, knowledge representation, reasoning and searching, have been reflected in data mining.