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Knowledge sharing in the health scenario.

Lluch-Ariet M, Brugués de la Torre A, Vallverdú F, Pegueroles-Vallés J - J Transl Med (2014)

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

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.

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Cases collected through bilateral agreements. Average of the percentage of cases collected by the nodes after bilateral exchanges. Nodes have been grouped according to the relative size of their local Data Marts in four categories. As larger Data Marts, as more data collected.
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Figure 7: Cases collected through bilateral agreements. Average of the percentage of cases collected by the nodes after bilateral exchanges. Nodes have been grouped according to the relative size of their local Data Marts in four categories. As larger Data Marts, as more data collected.

Mentions: Finally, we checked our hypothesis that the nodes with less data which had less chances to achieve bilateral agreements would be those that specially benefit from MOSAIC. The figures corresponding to this hypothesis are shown in Figure 7 and are generated after running the MOSAIC protocol in the evaluation scenario of the worldwide network. The total set of nodes has been grouped in 4 categories according to the size of the datasets (e.g. "less than 25%" indicates the category of the set of nodes with a number of cases in their datasets, minor than the 25% of the average size of all datasets in the network).


Knowledge sharing in the health scenario.

Lluch-Ariet M, Brugués de la Torre A, Vallverdú F, Pegueroles-Vallés J - J Transl Med (2014)

Cases collected through bilateral agreements. Average of the percentage of cases collected by the nodes after bilateral exchanges. Nodes have been grouped according to the relative size of their local Data Marts in four categories. As larger Data Marts, as more data collected.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4255915&req=5

Figure 7: Cases collected through bilateral agreements. Average of the percentage of cases collected by the nodes after bilateral exchanges. Nodes have been grouped according to the relative size of their local Data Marts in four categories. As larger Data Marts, as more data collected.
Mentions: Finally, we checked our hypothesis that the nodes with less data which had less chances to achieve bilateral agreements would be those that specially benefit from MOSAIC. The figures corresponding to this hypothesis are shown in Figure 7 and are generated after running the MOSAIC protocol in the evaluation scenario of the worldwide network. The total set of nodes has been grouped in 4 categories according to the size of the datasets (e.g. "less than 25%" indicates the category of the set of nodes with a number of cases in their datasets, minor than the 25% of the average size of all datasets in the network).

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

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.

Show MeSH