  Everlasting contact between language communities leads to constant changes in
languages over time, and gives rise to language varieties and dialects.
However, the communities speaking non-standard language are often overlooked by
non-inclusive NLP technologies. Recently, there has been a surge of interest in
studying diatopic and diachronic changes in dialect NLP, but there is currently
no research exploring the intersection of both. Our work aims to fill this gap
by systematically reviewing diachronic and diatopic papers from a unified
perspective. In this work, we critically assess nine tasks and datasets across
five dialects from three language families (Slavic, Romance, and Germanic) in
both spoken and written modalities. The tasks covered are diverse, including
corpus construction, dialect distance estimation, and dialect geolocation
prediction, among others. Moreover, we outline five open challenges regarding
changes in dialect use over time, the reliability of dialect datasets, the
importance of speaker characteristics, limited coverage of dialects, and
ethical considerations in data collection. We hope that our work sheds light on
future research towards inclusive computational methods and datasets for
language varieties and dialects.
