The instinct in modern research is to keep everything. Storage is cheap, deletion feels risky, and the principles of openness and reproducibility seem to counsel retaining as much as possible for as long as possible. But this instinct conceals a real and growing cost. Storing data, running computations and preserving digital material for the long term all consume energy, and energy carries a carbon footprint. The cloud is not a weightless abstraction; it is data centres drawing power and demanding cooling, somewhere, continuously. As research becomes ever more data-intensive, the environmental cost of its digital life — storage, computation, preservation — can no longer be treated as invisible. Digital sustainability is the discipline of taking that cost seriously, and it is the subject of this article, which draws on the sustainable-research domain of the CASRAI Dictionary.
The hidden cost of keeping everything
The first thing digital sustainability asks us to see is that “keep it just in case” is not a cost-free default. Every dataset retained indefinitely occupies storage that must be powered, cooled, maintained, migrated to new media over time, and backed up — and the aggregate of countless such decisions across the research system is substantial. There is a real tension here with the open-data ideal. The drive to make data findable and reusable is valuable, but it can shade into digital hoarding: keeping vast quantities of low-value data on the vague principle that more is always better, without asking whether a dataset is worth its ongoing cost. The FAIR principles call for data to be findable and reusable — not for everything to be kept forever regardless of value. Distinguishing data worth preserving from data that need not be is itself an act of stewardship, not a betrayal of openness.
Appraisal and data minimisation
The practices that respond to this are appraisal and data minimisation. Appraisal — long established in the archival and records-management traditions — is the disciplined process of deciding what to keep, for how long, and what may responsibly be discarded, based on enduring value rather than reflex. Data minimisation, familiar also from data protection, is the principle of collecting and retaining only what is genuinely needed. Applied to research, these practices mean making conscious decisions: which raw data must be preserved to support published results and which intermediate files can be regenerated if ever needed; which datasets have lasting reuse value and which were transient. This is not an argument for carelessly deleting valuable data — the cost of losing irreplaceable data far exceeds the cost of storing it. It is an argument for deciding, deliberately and well, rather than defaulting to indiscriminate retention. Good appraisal keeps what matters and lets go of what does not, serving both sustainability and the long-term usability of the record.
Green software and computation
Storage is only part of the picture; computation has its own footprint. The green software movement — advanced by organisations such as the Green Software Foundation — aims to reduce the environmental impact of software itself. A central concept is Software Carbon Intensity (SCI), a specification for measuring the carbon emissions associated with running software, so that the impact can be quantified, compared and reduced rather than guessed at. For research, the principles translate into practical questions: is a computation more efficient than it needs to be; is it run repeatedly when results could be cached; is the workload run where and when the energy is cleaner? Efficient, well-considered computation is not only cheaper and faster but less carbon-intensive, and measuring impact, as SCI encourages, is the precondition for managing it.
Preservation that lasts: OAIS
Sustainability is not only about using less; it is also about preserving well, so that what is kept genuinely endures and the energy spent keeping it is not wasted. The reference model for long-term digital preservation is OAIS — the Open Archival Information System reference model — which provides a framework for what a trustworthy digital archive must do to preserve information over the long term and keep it accessible and understandable to future users. OAIS matters to digital sustainability in two ways. First, preservation is itself an ongoing activity with an environmental cost, and doing it according to a sound model means that cost buys real durability rather than slow decay. Second, preserving fewer things well — properly described, in sustainable formats, in a trustworthy archive — is far better, environmentally and intellectually, than preserving many things badly, where data accumulates and yet quietly becomes unusable through neglect. Good preservation and disciplined appraisal are two sides of the same sustainable practice.
Sustainability and FAIR, properly understood
None of this is in conflict with FAIR or with open research, properly understood. FAIR is about good stewardship — making the data that is worth keeping findable, accessible, interoperable and reusable — not about hoarding. A sustainable approach is, in fact, a more honest expression of FAIR: it concentrates effort on the data that genuinely merits it, rather than spreading thin attention and real resources across everything indiscriminately. Sustainability and good data stewardship point in the same direction: keep what matters, describe it well, preserve it properly, and let go of what does not earn its keep.
A consistent vocabulary for digital sustainability
For sustainable practice to be applied consistently — across repositories, institutions and funders — the concepts involved, such as retention periods, appraisal decisions, preservation levels and format requirements, must be described in ways that mean the same thing everywhere. That consistency is what the CASRAI Dictionary works towards: a shared vocabulary so that decisions about what to keep, how to preserve it and for how long are understood the same way wherever they are recorded. And because appraising, curating and preserving data well is genuine, skilled work, it can be described in the same shared framework as any other contribution — the CRediT taxonomy and the wider apparatus of research administration. The most sustainable digital research is not the research that stores the least, but the research that decides most carefully what is worth keeping — and then keeps it well.