The network science community has created a rich portfolio of network modelling and analysis techniques, which have become a cornerstone of data science. Most of these techniques build on simple graph abstractions, where nodes represent a system's elements and links represent dyadic interactions, relations, or dependencies between them. This simple formalism has proven useful to reason about the importance of nodes, the evolution and control of dynamical processes, as well as community or cluster structures in networked systems. However, they do not account for higher-order dependencies between nodes, which are present in many real complex systems.

HONS is the NetSci satellite for researchers that try to understand what we miss when we analyze graphs and network abstractions of complex systems. It focus is on cutting-edge higher-order network modelling techniques, which generalize network science techniques to models that account for higher-order dependencies in data on real systems. Continuing successful editions in Berkeley, Zaragoza, Seoul, and Indianapolis, and Paris, this year's edition will be held at NetSci 2019 in Burlington, Vermont, USA. The 2019 edition focuses on the challenge of learning and model selection, i.e. methods that allow us to select the "optimal" higher-order model to analyze a given system.

If you are interested to contribute a talk to the program, please get in touch with us. We look forward seeing you all again in beautiful Vermont in May!