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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. [ABSTRACT FROM AUTHOR]

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries. [ABSTRACT FROM AUTHOR]

Computational annotation of textual information has taken on an important role in knowledge extraction from the biomedical literature, since most of the relevant information from scientific findings is still maintained in text format. In this endeavour, annotation tools can assist in the identification of biomedical concepts and their relationships, providing faster reading and curation processes, with reduced costs. However, the separate usage of distinct annotation systems results in highly heterogeneous data, as it is difficult to efficiently combine and exchange this valuable asset. Moreover, despite the existence of several annotation formats, there is no unified way to integrate miscellaneous annotation outcomes into a reusable, sharable and searchable structure. Taking up this challenge, we present a modular architecture for textual information integration using semantic web features and services. The solution described allows the migration of curation data into a common model, providing a suitable transition process in which multiple annotation data can be integrated and enriched, with the possibility of being shared, compared and reused across semantic knowledge bases. [ABSTRACT FROM AUTHOR]