The theme of Open Access Week 2026 “The Cost of Knowledge” speaks to an issue close to Dryad, and one that is at the forefront of current discourse: Appropriate funding for research infrastructure.
Over the past two decades the scholarly communications community has come to appreciate that a summary journal article isn’t sufficient to fully understand, much less reproduce, the results of a research investigation. With that in mind, we’ve begun to reconceptualize what it means to communicate research, and started to share more additional research outputs ranging from study registration and data management plans, to raw data and code, to peer review reports.
But both the financial support and the intangible – and tangible – rewards of research are still primarily and disproportionately tied to traditional journal publishing. That leaves the rest of the ecosystem, especially core infrastructure providers, in curious, sometimes precarious positions.
As an open data publisher, Dryad operates both in parallel with and embedded in the traditional journal publishing workflow. Our processes, needs and costs are often analogous, but differ in key ways that demand a unique support structure.
Dryad works differently
Dryad publishes data under creative commons licenses, making it available for anyone to discover, access, remix, and reuse, without restriction anywhere in the world. But preparing, publishing, and preserving that data has real costs attached. So does maintaining an organization with the staff and expertise to develop standards, design workflows, build custom systems, and adjust to new requirements.
Dryad isn’t simply a platform where researchers can store their data. We’re a data publishing service.
Our professional data publishing experts review each dataset and work one-on-one with authors to prepare it for publication. Their depth of knowledge and hands-on personal care ensures Dryad data meets all relevant journal and funder requirements. Published datasets are also protected in accordance with preservation standards, and augmented with persistent identifiers like DOI, ORCID, CRediT, and ROR. The result is unparalleled metadata that makes Dryad datasets the most discoverable and impactful around.
Our expenses fall into two broad categories: the direct costs associated with our author service — what it costs to submit, evaluate, publish, and preserve a dataset; and everything else — running our nonprofit organization, keeping our standards up-to-date, and staying abreast of the latest technologies, features, and functionality. We’re a small team dispersed around the world, with no central office, and minimal administrative support needs, which cuts down on costs. We pay our programmers and data publishing experts fairly for their contributions. And we’re growing.
A sustainable community funding model
Early in 2025, Dryad announced a new partner program and fee structure designed to distribute our operational and data-publishing costs across our user community and partner organizations in a fair, flexible, and sustainable way. The new model was the result of three years of intensive work, including formal and informal listening sessions, co-design with stakeholders, user research, and a product market fit assessment that identified the aspects of Dryad’s service that resonated with users and partner organizations, and those that didn’t.
The previous fee model had evolved over time. It was inconsistent, requiring significant administrative oversight, and making it difficult to predict future income. The new model is community-informed, transparent, financially sound, and explicitly links fees to the services users value. Eighteen months on, we’re beginning to see the difference: While the number of partner organizations decreased, revenue increased by 5%. We have the information we need to create valid financial predictions, plan our growth, and set benchmarks. We have the stability to continue to provide exceptional service over the long term.
What we’ve learned is: Our community is willing to contribute to cover reasonable costs, if they feel the value added is commensurate.
The shifting significance of data
Scholarly communications still treats data as ancillary to journal articles — even as we’re beginning to acknowledge that attitude is outdated.
Data publishing may have begun as a strategy for improving the quality of published research by providing context, enabling validation and replication, and improving reproducibility. But today, data can and should stand alone as an independent research output. Increasingly, it’s being processed in bulk as part of larger analyses, meta-analyses, or systematic reviews. In the future, as AI takes on a larger role in how research is conducted and consumed, the importance of data will only increase.
Research isn’t complete until it’s shared, and data isn’t usable until it’s checked, discoverable, and well described. Data publication deserves support that reflects its value to the research community, and enables the high-quality data curation that makes modern data discovery and reuse possible.