Recordings of speech play a central role in the diverse subdisciplines of linguistics. The reliance on speech recordings is especially profound in sociolinguistics, where scholars have developed a range of techniques for eliciting and analyzing natural talk. Despite the focus on naturalistic speech data, sociolinguists have rarely focused explicitly on the management (e.g. organization, storage, accessibility, and preservation) of their data, and this lack of focus has had consequences for the advancement of the field. At the same time, the interviews that sociolinguists labor so hard to obtain are often barely mined for their full potential to further our understanding of language. That is, sociolinguists often focus on a handful of phonological and/or morphosyntactic variables to the exclusion of so many other features of speech. The present work both addresses the management of sociolinguistic data and, through an innovative approach to speech data management and analysis, extends the sociolinguistic lens to include the lesser-examined realm of variation in sequential temporal patterns of talk. The first part of this dissertation describes the Sociolinguistic Archive and Analysis Project (SLAAP), a web-based digitization and preservation initiative at North Carolina State University. SLAAP, which I principally have designed and developed, is more than an archive; it has actively sought to explicate approaches to spoken language data management and to enrich spoken language data through the development of analytic tools designed specifically for sociolinguistic analysis. This dissertation begins by situating SLAAP within the history of data management practices in the field of sociolinguistics. It then provides an overview of many of SLAAP's features, discussing in particular the transcript model that enables most of its analytic and presentational capabilities.