  To understand societal phenomena through simulation, we need computational
variants of socio-cognitive theories. Social Practice Theory has provided a
unique understanding of social phenomena regarding the routinized, social and
interconnected aspects of behaviour. This paper provides the Social Practice
Agent (SoPrA) model that enables the use of Social Practice Theory (SPT) for
agent-based simulations. We extract requirements from SPT, construct a
computational model in the Unified Modelling Language, verify its
implementation in Netlogo and Prot\'eg\'e and show how SoPrA maps on a use case
of commuting. The next step is to model the dynamic aspect of SPT and validate
SoPrA's ability to provide understanding in different scenario's. This paper
provides the groundwork with a computational model that is a correct depiction
of SPT, computational feasible and can be directly mapped to the habitual,
social and interconnected aspects of a target scenario.
