Abstract:As a data-driven intelligent management tool in enterprise management, business intelligence can significantly improve the decision-making level and management ability of enterprises. As a brother field of enterprise management, science and technology management has a big gap compared with the former in terms of informatization and intelligence. Today, with the vigorous development of big data and artificial intelligence technology, can science and technology management learn from the tools of business intelligence and business thinking mode, give better play to the role of data in science and technology management, and determine whether science and technology management can better serve the development needs of China's science and technology in the future. This paper puts forward and combs the concept of scientific research intelligence, summarizes the theoretical origin and development path of scientific research intelligence, introduces the overall framework and key technologies of scientific research intelligence, and expounds the academic value and practical significance of scientific research intelligence.

Key words:scientific research intelligence; business intelligence; science of science and technology management; scientific research information; scientometrics

Abstract: Human society is entering an era which is filled of informationization, big data and intelligence. New concepts such as artificial intelligence, data intelligence, organizational intelligence, and business intelligence are emerging in endlessly. Among them, business intelligence, as the most mature, specific and widely used concept has undergone several connotation evolutions since it been put forward in the late 1980 s, which has become an important data analysis and display system for enterprise decision support, and can solve the problem of data support in decision-making and operation for enterprises, greatly improving the level and efficiency of enterprise management. So, in science management, can we use business intelligence thinking and tools to provide decision-making assistance and management support for science management? In this context, we put forward a concept of "science intelligence". The theoretical origin of the concept of science intelligence mainly includes the following two points. Firstly, science intelligence is the application of business intelligence technology in scientific research. It borrows mature technologies and solutions to solve the specific problems in science managementin the field of business intelligence. Secondly, science intelligence is needed by the times for the development of scientific informatization and scientometrics. At present, we already have a relatively complete scientific research data infrastructure. The key issue that needs to be focused on in the following part is how to upgrade and transform at the software level and integrate scattered scientific research data.Based on the thoughts and technologies of business intelligence, the research designed the overall framework of science intelligence. It integrates modern data warehousing technology, data mining technology and data dashboard technology, and integrates semantic information processing, knowledge search and recommendation, chart dashboard, mapping knowledge domains and other modules. In this framework, the bottom layer is a multi-source heterogeneous science database, which is built through scientific research big data analysis, entity relationship diagram construction, index system design, etc.; the middle is science intelligence concepts, theories, methods, and the toolset root in business intelligence; the upper layer is the application layer, which not only includes the specific functions of science intelligence such as data filtering, data drill-down, and association charts, but also specific functions in science monitoring, evaluation, and diagnosis. Among them, the key technologies in the opening of science intelligence systems is how to build a multi-source heterogeneous database for semi-structured and unstructured data and how to realize the transformation from a static non-interactive knowledge graph to a dynamic interactive visualization graph, and how to establish science intelligence modules and processes for science and technology policy and science management. Science intelligence has important theoretical and practical significance for future-oriented science of science and S.&T. management. Since the reform and opening up, especially the 18 th National Congress of the Communist Party of China, China has made great achievements in science and technology and has achieved remarkable results. However, there are still some shortcomings which restrict the further improvement of technological innovation capabilities and global competitiveness in the development of science and technology of China. One of the important ways to solve the problem is to rely on the science intelligence technology to improve the modern informatization level of science and technology management. At the same time, at the micro level, with the help of science intelligence, only continuously improve the level of intelligence in the management of science and technology in universities or research institutes, can we provide better services for scientists. Business administration and technology management are the sibling fields in management disciplines. Under the environment of market economy, the research interest in business management is rising, while the research on science and technology management in universities and scientific research institutes is declining, and both academic research and specific applications are beginning to lag behind business management. Whether can use the successful experience of business management and learn from mature tools such as business intelligence to reshape the fields of science of science and S.&T. management will become a necessary path for the development of it.

Keyword：science intelligence; business intelligence; science and technology management; e-science; scientometrics