This presentation will show how different software development processes like requirements engineering, bug-tracking and customer support can be enhanced by using semantic web technologies. With the help of an extraction pipeline all information e.g. requirements information and tickets from standard tools like Confluence and JIRA are collected and then transformed to RDF, based on a standard ontology that is extended based on the specific use cases. In addition, the information from these different systems is linked by a taxonomy. The resulting enriched knowledge graph can be analyzed via graph similarity algorithms to find common patterns, so that e.g. similarities between feature requests and bug reports can automatically be detected. This allows to develop semantic plugins for the tools used or independent semantic applications providing novel ways to access and use that interlinked data set. The presentation will show the pipeline, the ontology needed to describe the problem space and the resulting data sets and patterns within two real world industrial use cases, where this technology is already applied. Basis for this is work in the H2020 project ALIGNED.