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There are many health information systems that visualize the symptoms of influenza-like illness on a digital map, which is suitable for end-users, but it does not afford further processing and analysis. Existing systems have emphasized the collection, analysis, and visualization of surveillance data, but they have neglected a modular and interoperable design that integrates high-resolution geo-location with real-time data. As a remedy, we have built an open-source project and we have been operating an open service that detects flu-related symptoms and shares the data in real-time with anyone who wants to built upon this system. An analysis of a small number of precisely geo-located status updates (e.g. Twitter) correlates closely with the Google Flu Trends and the Centers for Disease Control and Prevention flu-positive reports. We suggest that public health information systems should embrace an open-source approach and offer linked data, in order to facilitate the development of an ecosystem of applications and services, and in order to be transparent to the general public interest. <\/jats:p>","DOI":"10.1177\/1460458215599822","type":"journal-article","created":{"date-parts":[[2015,9,9]],"date-time":"2015-09-09T01:03:25Z","timestamp":1441760605000},"page":"962-974","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":24,"title":["Flutrack.org: Open-source and linked data for epidemiology"],"prefix":"10.1177","volume":"22","author":[{"given":"Konstantinos","family":"Chorianopoulos","sequence":"first","affiliation":[{"name":"Ionian University, Greece"}]},{"given":"Karolos","family":"Talvis","sequence":"additional","affiliation":[{"name":"Ionian University, 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