In today’s interconnected global landscape, the seamless circulation of data across borders has emerged as a pivotal factor underpinning the global economy, scientific research, and technological advancements. It is imperative to enable a secure data-sharing ecosystem that ensures trustworthiness, which, in the cross-border context, refers to traceability, accountability, and multiparty compliance. However, a significant challenge remains: the lack of a universally applicable framework tailored to these scenarios, one could provide a trust foundation and corresponding assurances. To address this, we have taken “traceable, accountable, and multiparty compliant data-sharing” as design principles and propose a Trans-border Trusted Data Spaces (TTDS) framework. TTDS adopts the International Data Spaces (IDS) information model used in EU data-sharing projects to ensure interoperability and leverage the existing tools and standards to establish trustworthiness of participant identities. Building upon this, the framework provides traceability and accountability for data usage through security features including IP layer traffic monitoring, zero-trust identity management, smart contracts, etc. It also offers multi-party compliance support through a natural language processing (NLP) based rule interpretation framework. Compared to existing data-sharing frameworks, TTDS provides a more reliable and general “infrastructure” tailored to the specific needs of cross-border scenarios. In this paper, we present the functional and technical architecture as well as the core components of TTDS. And then propose a system implementation based on IPv6 for the more urgently needed aspects of data traceability, empirically demonstrating its effectiveness in achieving robust traceability and provided effective evidence to support accountability.