  Multiwinner voting captures a wide variety of settings, from parliamentary
elections in democratic systems to product placement in online shopping
platforms. There is a large body of work dealing with axiomatic
characterizations, computational complexity, and algorithmic analysis of
multiwinner voting rules. Although many challenges remain, significant progress
has been made in showing existence of fair and representative outcomes as well
as efficient algorithmic solutions for many commonly studied settings. However,
much of this work focuses on single-shot elections, even though in numerous
real-world settings elections are held periodically and repeatedly. Hence, it
is imperative to extend the study of multiwinner voting to temporal settings.
Recently, there have been several efforts to address this challenge. However,
these works are difficult to compare, as they model multi-period voting in very
different ways. We propose a unified framework for studying temporal fairness
in this domain, drawing connections with various existing bodies of work, and
consolidating them within a general framework. We also identify gaps in
existing literature, outline multiple opportunities for future work, and put
forward a vision for the future of multiwinner voting in temporal settings.
