  Event prediction is the ability of anticipating future events, i.e., future
real-world occurrences, and aims to support the user in deciding on actions
that change future events towards a desired state. An event prediction method
learns the relation between features of past events and future events. It is
applied to newly observed events to predict corresponding future events that
are evaluated with respect to the user's desired future state. If the predicted
future events do not comply with this state, actions are taken towards
achieving desirable future states. Evidently, event prediction is valuable in
many application domains such as business and natural disasters. The diversity
of application domains results in a diverse range of methods that are scattered
across various research areas which, in turn, use different terminology for
event prediction methods. Consequently, sharing methods and knowledge for
developing future event prediction methods is restricted. To facilitate
knowledge sharing on account of a comprehensive classification, integration,
and assessment of event prediction methods, we combine taxonomies and take a
systems perspective to integrate event prediction methods into a single system,
elicit requirements and assess existing work with respect to the requirements.
Based on the assessment, we identify open challenges and discuss future
research directions.
