Abstract
neXtProt provides a comprehensive knowledgebase on human proteins complemented by an extensive cross incorporation of annotations from many databases. With the diversity of published data, provenance information becomes critical to providing reliable and trustworthy services to scientists, thus the tracking of provenance in open, decentralized systems is especially important. Since the nanopublication system addresses many of these challenges, we have developed the neXtProt Linked Data by serializing in RDF/XML annotations specific to neXtProt and started employing the nanopublication model to give appropriate attribution to all data. Specifically, a use case demonstrates the handling of post-translational modification (PTM) data modeled as nanopublications to illustrate how the different levels of provenance and data quality thresholds can be captured in this model.