  Systematic Literature Reviews aim at investigating current approaches to
conclude a research gap or determine a futuristic approach. They represent a
significant part of a research activity, from which new concepts stem. However,
with the massive availability of publications at a rapid growing rate,
especially digitally, it becomes challenging to efficiently screen and assess
relevant publications. Another challenge is the continuous assessment of
related work over a long period of time and the consequent need for a
continuous update, which can be a time-consuming task. Knowledge graphs model
entities in a connected manner and enable new insights using different
reasoning and analysis methods. The objective of this work is to present an
approach to partially automate the conduction of a Systematic Literature Review
as well as classify and visualize the results as a knowledge graph. The
designed software prototype was used for the conduction of a review on
context-awareness in automation systems with considerably accurate results
compared to a manual conduction.
