Life science’s main asset is its data. Data forms the basis of scientific decision making and its availability via electronic systems is a prerequisite for collaborative work and successful innovation. While more data is published as linked (open) data, huge amounts of data remain unused in internal data silos, such as various ELN’s, because of substantial integration efforts and data quality issues. Since the overwhelming amount of data is unstructured, information extraction and corresponding classification and semantic labeling of content is required. To generate value from your ELN data, a solid informatics strategy is needed to ensure data quality and streamline analytics. Semantic technologies are key enabler to overcome existing limitations.