The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services.
Each service may actually request or create a large amount of data sets. To compose these services will be more challenging.
Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of
reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism
is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Twostage
negotiation procedures are used in our data-intensive service provision model, which will provide effective and efficient
service selection for service composers. We also present a multi-phase, multi-party negotiation protocol, where the ant colony
system is applied to select services with the best or near-optimal utility outputs. In order to adapt the ant colony system to handle
the dynamic scenarios during negotiations, we also discuss several strategies for modifying the pheromone information in the
first place. The experimental results show that our negotiation-based approach can facilitate the data-intensive service provision
with better outcome.