Egas is a web-based platform for biomedical text mining and collaborative curation. The web tool allows users to annotate texts with concept occurrences as well as with relations between concepts. Annotations can be performed manually or based on the results of automated concept identification and relation extraction tools. These automatic annotations may have been previously added to the documents, using one of the accepted input formats, or may be added during the annotation process, by calling a document annotation service. Users can inspect, correct or remove automatic text mining results, manually add new annotations, and export the results to standard formats.


Text-processing and fetching modules, such as the concept and relation annotation services, were implemented in Java, and the web interface was developed using HTML5, CSS3, and JavaScript, in order to allow fast processing of large documents and support mobile devices. The resulting information is stored in a relational database. Finally, all database operations are performed using secured RESTful web-services, allowing easy integration with mobile devices, such as smartphones and tablets.