Automated Contract Negotiation in Data Spaces: Practitioner Needs Assessment and Negotiation Framework

Data spaces provide governed ecosystems for sovereign data exchange among organizations. However, current implementations rely on static, accept-or-reject contract mechanisms that limit agreement flexibility and constrain ecosystem adoption through suboptimal or failed negotiations. This work presents an automated and bilateral negotiation framework for multi-issue contracts in data spaces, aligned with the Dataspace Protocol (DSP) and the Open Digital Rights Language (ODRL) standards. The framework comprises a negotiation engine that implements iterative, time-dependent concession strategies, utility-based evaluation, and opponent modeling, together with a translator module that provides bidirectional mapping between ODRL policy constructs and the negotiation logic. The framework design is grounded in a practitioner needs assessment that identifies current negotiation gaps, confirms demand for automated support, and informs the selection of negotiation issues and the human-in-the-loop approval mechanism. The framework is integrated with the Eclipse Dataspace Components (EDC) and validated in an urban data-sharing scenario. A systematic evaluation compares the framework against baseline strategies, analyzes the effect of concession pace on the efficiency-welfare tradeoff, and characterizes framework robustness across varying degrees of preference overlap between parties.