In the future, the digital economy will be the engine of global economic growth and a new economic form, following the agricultural and industrial economies. It is based on information technology and industry and considers data as the key production factor, the network as the carrier, and the application of information technology as the key driving force. The development and utilization of big data as a new data source will infuse new vitality into the digital economy. The development of a digital economy and its deep integration with the real economy will promote the industrialization of digital science and technology and the digitization of industry, accelerate the construction of a modern industrial system, and usher the human economy and society into a new stage of economic development.

Cities, as the nodes and centers of human society's economic, cultural, and political systems, should pay attention not only to the coordination of their system structure and function but also to their leading role in sustainable development and the impact on the overall system, especially in the era of economic globalization. Routine statistics and census data have poor spatial completeness, are not real time, and vary in data quality, resulting in relatively low spatial and temporal resolution of urban sustainability assessment results, questioned reliability and timeliness. Big data is critical for overcoming the deficiencies of traditional statistical data in the assessment of urban sustainable development. It can provide a new impetus for urban sustainable development assessment with its macro, dynamic, and diverse advantages, which can provide support for sustainable urban development in terms of data products, technical methods, case analysis, and decision support.

Climate change is a long-term problem that mankind will have to confront. For the impacts caused by climate change, particularly extreme weather and climate events, how to accurately monitor extreme climate events and disasters, monitor and evaluate disaster processes in real time, and provide strong data and scientific support for climate change response and disaster prevention and control has become a major scientific question that must be addressed urgently. The majority of existing research on relevant disaster indicators is limited by the lack of spatial data and multilevel analysis, making it difficult to form guidance and early warning for disaster risk reduction. Big data is conducive to reducing the uncertainty of research and evaluation results and can meet the urgent needs of scientific data to conduct climate change and disaster risk research with a high degree of synergy and integration. It can effectively monitor climate extremes and disasters on a large scale, mitigate climate change threats, and provide decision support for improving human adaptive capacity.

Biodiversity is an inseparable material basis for human social and economic development, and big data provides an important channel for a comprehensive understanding of biodiversity. Massive species distribution data bolsters biodiversity conservation and research, significantly advancing research on biodiversity conservation planning, the response of biodiversity to global ecosystem changes, the form of large-scale biodiversity patterns, and the forecast of alien species invasion, etc. Currently, significant progress has been made in the use of big data to draw biodiversity maps as well as to combine niche models and artificial intelligence models to identify species. In the future, it will investigate the establishment of a sound scientific data exchange and sharing system and promote the output of key biodiversity achievements within the paradigm of big data scientific research to better serve biodiversity conservation.