SDA: Towards a novel knowledge discovery model for information systems

Here, we present a novel model for knowledge discovery in biomedical sciences which has already been used for analyzing millions of journal articles from PMC and PubMed. We decompose each scientific document into semantic digital assets (SDA) that help to build an efficient workflow to retrieve single statements and hypothesis from huge and heterogeneous collections of large documents instead of complete articles. This new approach is so general applicable, that it will also be useful for information systems in other domains.