Evolutionary Archives: The Unlikely Comparison of GenBank and Know Your Meme

Abstract

Digital trace data in archives offer novel sources for examining "evolutionary" social and cultural phenomena. Yet, few studies have formally examined the features of archives that can be of use for scholars taking evolutionary perspectives in archival science. To address this gap, we compare the design features, metadata, and affordances of two repositories – GenBank and Know Your Meme – leveraging longstanding evolutionary analogies between genes and memes to identify trace data useful for evolutionary analyses. Our empirical analysis reveals the opportunities and limitations in using networked and longitudinal data contained in repositories. Repositories, here, are analyzed as trace data. We argue that archival system designers and CAS research should be aware of how archives represent data and how the archival features influence or limit CAS research. We conclude with a discussion of the challenges associated with archival (meta)data structures offering "big data" (and "big metadata"). In examining these repositories, we speculate about computational concerns in archiving evolutionary data. Doing so moves towards a principled approach for informing how evolutionary archives could be designed.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 1 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.