The understanding of certain data often requires the collection of similar data from different places to be analysed and interpreted. Multi-agent systems (MAS), interoperability standards (DICOM, HL7 or EN13606) and clinical Ontologies, are facilitating data interchange among different clinical centres around the world. However, as more and more data becomes available, and more heterogeneous this data gets, the task of accessing and exploiting the large number of distributed repositories to extract useful knowledge becomes increasingly complex. Beyond the existing networks and advances for data transfer, data sharing protocols to support multilateral agreements are useful to exploit the knowledge of distributed Data Warehouses. The access to a certain data set in a federated Data Warehouse may be constrained by the requirement to deliver another specific data set. When bilateral agreements between two nodes of a network are not enough to solve the constraints for accessing to a certain data set, multilateral agreements for data exchange can be a solution.
The research carried out in this PhD Thesis comprises the design and implementation of a Multi-Agent System for multilateral exchange agreements of clinical data, and evaluate how those multilateral agreements increase the percentage of data collected by a single node from the total amount of data available in the network. Different strategies to reduce the number of messages needed to achieve an agreement are also considered.
The results show that with this collaborative sharing scenario the percentage of data collected dramatically improve from bilateral agreements to multilateral ones, up to reach almost all data available in the network.