On the construction of deep sharing mechanism of AI data in public domain
Data sharing in public domain is the key to the development of AI industry.The lack of sharing freedom caused by data hegemony at the platform level,the limitation of public domain caused by data barriers at the resource level,and the ambiguity of sharing standards caused by unclear ownership at the rule level,all have a series of negative effects on the public domain of data.AI data should practice the concept of"deep sharing".Based on such three dimensions as the platform,resources and rules,AI data aims to realize the paradigm transformation of sharing platform from single-layered closed hub to multi-layered open network,with resource sharing mode from single to multi-dimensional,and sharing rules from conservative to open.To build a deep sharing mechanism of AI data in the public domain,we should take"open source"as the premise,introduce the"FAIR principle"of data sharing,and adopt a dual-layered sharing model in the public domain,constructing role-modular data sharing ecology at the platform level to achieve data sharing freedom,setting Official Public Mark of the data public domain at the resource level to clarify the scope of the public domain,and improving data open source protocols at the rule level to establish data sharing standards,so as to eventually fulfill abundant and prosperous data resources in the AI public domain.
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