Hello! First time poster here. I work at a company that uses Neo4j in production. I took many graph theory courses in school, but they were focused on mathematical properties of graphs in the abstract, rather than property graphs for applied use.

I am starting a project investigating how we can use the GDS algorithms on our data. I figure I need to learn about how to design experiments in general, and how to choose projections of our data intelligently so that I can run experiments to select the right algorithm for the job. I've ordered the Barabási network science book, and I am looking for additional resources to skill up in this topic. Thanks!