Abstract
The understanding of certain data often requires the collection of similar data from different places to be analysed and interpreted. Interoperability standards and ontologies, are facilitating data interchange around the world. However, 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 are needed.We present the 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 dramaticaly improve from bilateral agreements to multilateral ones, up to reach almost all data available in the network.
Highlights
Clinicians and biomedical researchers often need to compare the information collected from the exams performed on their patients with information from similar patients in other places
A Unicast Petitioner Agent (UCP) arrives to the end of a path candidate to solve a multilateral agreement, when it receives the requested data from its Unicast Contributor Agent (UCC) without the need to launch any other Multicast Petitioner Agent (MCP)
The results shown in this article are based, firstly on the activation of the Multicast Contributor Agent (MCC) for the datasets with the same cases available, and secondly on the activation of a request for every possible dataset, by every node
Summary
Clinicians and biomedical researchers often need to compare the information collected from the exams performed on their patients with information from similar patients in other places. MOSAIC (see Figure 1) is a Multy-Agent System that facilitates the multilateral data exchange in a network by providing mechanisms for the intelligent search of paths to reach the datasets requested, involving a set of nodes in multilateral agreements. When an MCP does not find any MCC with the data set needed to fulfil a constraint, it stops the exploration and notifies to its creator UCP on the failure of the path in its attempt to find a multilateral agreement. At the end of the process of network exploration, the MCP that initiated the request receives, for every dataset of interest, the set of negotiation paths that correspond to a possible multilateral agreement. An initial selection is performed among the paths that arrive to the same dataset, but the MCP may decide to execute only a subset of all the remaining negotiation path candidates, based on other criteria (e.g. cost or reputation)
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