Exploring open government data ecosystems across data, information, and business.

Autor: Fang, Jun1 (AUTHOR), Zhao, Longwen1 (AUTHOR) lwzhao_scut@163.com, Li, Shuting1 (AUTHOR)
Předmět:
Zdroj: Government Information Quarterly. Jun2024, Vol. 41 Issue 2, pN.PAG-N.PAG. 1p.
Abstrakt: Although the Open Government Data (OGD) movement is flourishing globally, the large-scale utilization and value creation of OGD has not really opened yet, which is far from the goal and expectation of data openness. Guiding the practice of OGD with the concept of "ecosystem" can help promote the efficient utilization and value realization of data. From the perspective of the whole process of OGD utilization, ecosystems have various types of ecological characteristics such as data flow, information expression and value realization. To this end, this paper proposes a new perspective of viewing OGD ecosystems across data, information and business based on the theories of supernetworks, data value chains, information ecosystems and business ecosystems, and further explores the ecosystems through a case study in Guizhou, China. We conclude that the hierarchical division of OGD ecosystems as a whole is clearer, and the focus of each layer is more focused; the cross-level dynamics mechanism of the ecosystem, and the information transmission mechanism assumed by the information ecosystem make the three layers interact with each other; and the different actors play different roles in the three layers and occupy different ecological position. This study provides useful reference for OGD practice and also expands new ideas and space for theoretical research and application practice of the ecosystem approach. • Reviews open government data (OGD) ecosystem challenges. • Emphasizes the process of utilizing and creating value from OGD. • Develops a hybrid ecosystem model of data, information and business. • Applies the model to case study of Guizhou, China. • Suggests further testing and additional research. [ABSTRACT FROM AUTHOR]
Databáze: Library, Information Science & Technology Abstracts