Matters (and metaphors) of life and death: How DNA storage doubles back on its promise to the world
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
For this special section on “geographies of the digital,” we explore how DNA‐based data storage is touted as an alternative to traditional storage modalities and pitched by the data storage industry as a more efficient, stable, and long‐term archival solution than that offered by current technologies. In analyzing how DNA is soaked in the language of sustainability, life, and longevity by those trumpeting the new technology, we situate emergent discourses proposing DNA as a remedy to energy‐, water‐, and land‐intensive data centres and cloud storage. While DNA is not an “online” data storage technology, we show that the prospects of biological computation have altered the imagined futurity of cloud infrastructure. We then explain how DNA data storage works, and we complete the paper with three case studies—Microvenus, The National Film and Sound Archive of Australia, and The Arch Mission Foundation's Lunar Library—offering a critique of “the archive” as it is framed through these nascent scientific and technological discourses. In sum, we argue that DNA‐based data storage is imbricated by an apocalyptic thinking, and that the temporality and timing of this technology speaks to growing, unevenly distributed, planetary anxieties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it