This software demonstration paper presents the Epidemic Marketplace, a platform for integrating and sharing epidemiological data. It uses its own semantic metadata model for characterizing the resources submitted, which integrates a network of epidemiology related ontologies. The Epidemic Marketplace platform is available at http://www.epimarketplace.net/.
The Epidemic Marketplace is a platform for integrating and
sharing epidemiological data, which aims at supporting
transparent, seamless access to distributed, heterogeneous and redundant
resources
The Epidemic Marketplace uses its own semantic metadata model
for characterizing the submitted resources
The usage of ontologies enables the restriction of the semantic characterization of every resource to standard and unambiguous terms, making the information retrieval and analysis of the stored resources more effective. Additionally, it also facilitates the semantic characterization process, for example by providing term suggestions according to the user profile and their previous resource submissions.
The platform provides a web user interface to upload, characterize, browse, search, download, request and comment the epidemic resources and their metadata. The resources are disseminated under access policies that can be personalized.
The interface was developed using Drupal, a highly customizable free software package for the organization, management and distribution of any content 1. The resources are stored in a repository based on Fedora Commons, a general-purpose, open-source digital object repository system 2.
Figure 1 shows an example of the resources returned by the platform when searching for flu in 2010 and by ordering them by date (oldest first). This is just an example of a generic search, but more specialized filters based on ontological terms may be performed.
The resources and their metadata are also directly accessible through the set of RESTful web services that are invoked by the user interface to store and manage the resources. These web services are currently being used by computational applications that require automatic retrieval, search, upload, update or removal of resources stored in the Marketplace platform. For example, these web services are currently being used to store simulation data from the GleamViz simulator 3, tweets retrieved by the MEDCollector 4, and monitorization data gathered by the Influenzanet system 5. The web services also enable computational applications to manage group-based access control policies. The detailed specification of these web services is presented on the platform’s web site. 6. 3
This software demonstration paper presents the Epidemic Marketplace, a platform that enables users to semantically characterize their resources in a standard way by exploiting the knowledge encoded in a comprehensive network of epidemiologically relevant ontologies. This model not only enhances the characterization process, but also provides the community with an important asset by its own, and improves the integration, retrieval and analysis of resources. 1 http://www.drupal.org/ 2 http://www.fedora-commons.org/ 3 http://www.gleamviz.org/simulator/ 4 http://vimeo.com/14734417 5 http://www.influenzanet.eu/ 6 http://www.epimarketplace.net/developers_corner/ web_services
The goal is to provide a unified and integrated platform for the management of epidemic resources, which will be semantically characterized by extensively exploiting the knowledge encoded in available ontologies. This platform will eventually serve as the basis for a distributed information reference for epidemic modelers, which will further aid the communication within the community of epidemiologists and the sharing of their knowledge.
The authors want to thank the European Commission for the financial support of the EPIWORK project under the Seventh Framework Programme (Grant #231807) and the Portuguese Fundação para a Ciência e Tecnologia through the financial support of the SOMER project (PTDC/EIA-EIA/119119/2010), the PhD grant SFRH/BD/69345/2010, through the PIDDAC Program funds (INESC-ID multi annual funding) and through the LASIGE multiannual support.