COEUS 2.0: automated platform to integrate and publish biomedical data as nanopublications

Abstract

Publishing, analysing or properly accessing the abundant information resulting largely from experimental studies in the biomedical domain are current challenges for the research community. Problems with the extraction of relevant information, redundant data, and lack of associations or provenance are good examples of the main concerns. The innovative nanopublication publishing strategy tries to overcome these issues by representing the essential pieces of publishable information on the Semantic Web. However, existing methods to create these Resource Description Framework-based data snippets are based on complex scripting procedures, hindering their use by the community. Therefore, novel and automated strategies are needed to explore the evident value of nanopublications and to enable data attribution mechanisms, an important feature for data owners. To solve these challenges, the authors introduce the second generation of the COEUS open-source application framework (http://bioinformatics.ua.pt/coeus/), an automated platform to integrate heterogeneous scientific outcomes into nanopublications. This results in seamless integration, making data accessible and citable at the same time. No additional scripting methods are needed. A validation of a nanopublishing pipeline is described to demonstrate the system functionalities, integrating and publishing common biomedical achievements into the Semantic Web ecosystem.