Context Matters

Simulation and case studies (including logistics, healthcare, and cross-border data spaces) confirm that no single model solves all challenges. Recursive models provide flexibility and revocation robustness, but require multiple lookups. Concatenation models improve efficiency, but at the cost of privacy and adaptability. Macaroons excel in privacy and speed, but complicate governance and auditing.

The choice of model depends on context: logistics chains may favour flexibility (Previous Party ID), regulated sectors may prioritise auditability (Previous Delegation ID), performance-driven IoT exchanges may prefer concatenation, and privacy-sensitive domains may lean towards macaroons.

For iSHARE, the key is not to prescribe a single approach, but to ensure interoperability across models. The framework’s attributes (delegation_path, previous_steps) and clarifications (e.g., rules must not contain targets in delegation evidence) provide the baseline for compatibility. This allows ARs and participants to adopt the model that best fits their context without fragmenting the ecosystem. The following Table gives a final overview of the benefits and limitations of each model:

Table 4.1: Consolidated strengths and weaknesses across delegation models.

A Continued Commitment to Optimisation

The models presented illustrate that there are several valid methods to manage delegation chains, each with their own strengths and trade-offs. Recursive approaches emphasise resilience and flexibility, concatenation offers speed and implementation ease, and macaroons provide strong privacy and cryptographic efficiency.

By documenting these patterns side by side, implementers can make informed choices suited to their requirements, while ensuring interoperability across data spaces. This approach reinforces that the data spaces remains secure.