Peking: On October 10, the National Engineering Laboratory of Big Data Analysis and Applied Technology at Peking University released Big Data Ecosystem Index of 2020 in Beijing, China. The project objectively evaluate the status of big data ecosystems in different regions across China, and provide an appropriate innovative platform that is used for digital analysis and information sharing. The goal of the project is to propel digital economy and build China into a digitalized country.
Zhang Pingwen, vice president of Peking University and director of the National Engineering Laboratory, said that GDP can no longer adequately rank and evaluate the development of a country/region’s digital economy in the modern age. Nowadays, big data ecosystems have encompassed countless areas such as economy and politics. Big data ecosystems allow different social and economic entities, particularly governments, enterprises and individuals, to connect, communicate, interact and trade through the means of technology, thereby creating a socio-economic ecosystem which emphasizes the importance of data flow and interaction.
As part of the Big Data Ecosystem Index of 2020, a general framework consisting of three categories, i.e. big data foundation, big data capabilities, big data applications, were set up with each having individual sub-criteria providing detailed summaries with different focal points. Big Data Ecosystem Index of 2020 collected statistics from 31 provincial-level administrative regions (excluding Hong Kong, Macao and Taiwan regions of China) and some major cities. Its purpose is to monitor the progress of national, local and industrial digital development and transformation, provide decision-making support for relevant government bodies, and help build a new think tank for sci-tech development and a platform for social services.
Zhang stressed that in order to portray the digital ecosystem comprehensively, fully and accurately, the characteristics and advantages of big data must be fully utilized, which means the evaluation process should be carried out from a multi-dimensional perspective based on multi-source data. Therefore, the National Engineering Laboratory of Big Data Analysis and Applied Technologies of Peking University has jointly co-founded a digital ecology collaborative platform with 14 other institutions, including enterprises, Internet platforms, universities, research institutes and third-party organizations.
The results of the index divided respective Chinese provinces into four types – comprehensive leading type, surpassing type, growing type, and the potential breakthrough type. Each province is highly differentiated from one another, which indicated that data ecological studies could provide diversified and vast quantities of data useful for analyzing a province or region’s comprehensive development.
Zhang said that the Big Data Ecosystem Index is a complex project which requires long-term follow-up studies. Big Data Ecosystem Index of 2020 is only the initial outcome of the study. Limitations and problems still remain. In the future, the research team will take the digital ecology collaborative platform as the carrier, uphold the principle of win-win cooperation, and improve various areas such as the theoretical system, data sources, intelligent computing, and more.