Abstract. This paper analyzes the requirements and presents a novel approach to the development of a system for epidemiological data collection and integration based on the principles of interoperability and modularity. Accurate and timely epidemic models require the integration of large, fresh datasets. Thus, from an e-science perspective, collected data should be shared seamlessly across multiple applications. This is addressed by our approach, MEDCollector, trough workflow design enables the extraction of data from multiple Web sources. The mapping of extracted entities to ontologies will guarantee the consistency within gathered datasets, and therefore enhance epidemic modeling tools.
Abstract. The Epidemic Marketplace is part of a computational framework for organizing data for epidemic modeling and forecasting. It is a distributed data management platform where epidemiological data can be stored, managed and made available to the scientific community. It includes tools for the automatic interaction with other applications through web services, for the collection of epidemiological data from internet social networks and for discussion of related topics. This paper defines its requirements, architecture and implementation plan based on open-source software. This platform will assist epidemiologists and public health scientists in finding, sharing and exchanging data.
The authors introduce a group-based discretionary access control with decentralized permission and group management for scientific repositories. Currently, access control approaches for repositories have inflexible centralized administrations, which do not scale well to large numbers of users. Moreover, discretionary access control is a legal standard for health-related resources. The proposed access control model, which is formalized using Barker's Unifying Meta-model, differentiates permissions for data and meta-data, enabling the sharing of meta-data while protecting sensitive data. The authors describe how the model was implemented, and what challenges were tackled, in the Epidemic Marketplace, an open software information platform for epidemic studies, designed to foster cooperative behavior and data sharing.
Abstract. This paper analyzes the requirements and presents a novel approach to the development of a system for epidemiological data collection and integration based on the principles of interoperability and modularity. Accurate and timely epidemic models require the integration of large, fresh datasets. Thus, from an e-science perspective, collected data should be shared seamlessly across multiple applications. This is addressed by our approach, MEDCollector, trough workflow design enables the extraction of data from multiple Web sources. The mapping of extracted entities to ontologies will guarantee the consistency within gathered datasets, and therefore enhance epidemic modeling tools.
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