Immediate access to published research studies and the sharing of the raw data which underly them have long been a topic of considerable interest in the brain sciences. The recent announcement Footnote 1 from the White House Office of Science and Technology Policy (OSTP) on August 25 th , 2022 concerning the public availability of research literature and access to data has many in the field watching with interest on how the brain research and scholarly publishing communities will respond to government mandates on open access and the availability of primary data.

Beginning with the OSTP declaration in February 2013, federal public access policy has been governed by the Memorandum on Increasing Access to the Results of Federally Funded Research.Footnote 2 This memo directed all US federal departments and agencies responsible for more than $100 million in annual research and development expenditures to devise plans for supporting the increased public availability to federally funded research products. Moreover, the memo highlighted more direct access to scholarly publications and to the digital data obtained from such research projects.

On the eve of the ten-year anniversary of their original policy, the OSTP now seeks to advance its recommendationsFootnote 3 further to remove prior restrictions and promote further access for US tax payers and, as a byproduct, scientists worldwide. Policy revisions include removal of the 12-month embargo from public access, making that access free of charge to the public, and requiring scientific data forming the basis of peer-reviewed scholarly publications resulting from federally-funded research dollars be made freely available and publicly accessible by default at the time of publication. Presently, the OSTP is in discussions with US research funding agencies—including those funding major brain science efforts, e.g., the NIH, NSF, DoD, etc.—to begin implementing the process for supporting these new policies.

The new mandates come on the heels of a particularly stimulating time for the neurosciences – especially following a highly fruitful series of investments in brain research (Bookheimer et al., 2019; Feldstein Ewing et al., 2018; Koroshetz et al., 2018), the development of new community resources (Litvina et al., 2019), and emerging interest in the brain as a valuable source of digital information (Van Horn, 2021). Following earlier, pioneering efforts (Van Horn & Gazzaniga, 2013), deposition of data into large-scale neuroimaging, genomic, and phenotypic data archives, developed and run by the NIH (Hall et al., 2012), are a condition of grant funding.

Having grappled with the sociology of data sharing for over twenty years (Koslow, 2000) since the Decade of the Brain in the 1990’s (Rosenberg & Rowland, 1990), it has been gratifying to see US funding agencies implementing new access policies for peer-reviewed research and for the sharing of data. One early motivation behind efforts in the sharing of primary data was to ensure study reproducibility, confirmation of results, and to have data available to the widest possible audiences for secondary analyses (Van Horn & Gazzaniga, 2002). The so-called “reproducibility crisis” in neuroscience has been highlighted in recent years (Adali & Calhoun, 2022; Gilmore et al., 2017), been addressed as the subject of journal special issues (Poldrack et al., 2020), and the driver behind various best-practices recommendation efforts for neuroimaging (Nichols et al., 2017), MEEG (Pernet et al., 2020), epigenetic studies (Lancaster et al., 2018), for various clinical approaches (Backhausen et al., 2022; Mosher & Funke, 2020), and non-human research (Bjerke et al., 2018). Likewise, concerns over neuroimaging statistical inference (Eklund et al., 2016), the reliability of findings (Elliott et al., 2021), and issues concerning sample sizes (Marek et al., 2022) have been worrying. Calls to further compel researchers to share data in order to mitigate concerns have increased and become more demanding (Miyakawa, 2020).

Yet the history of neuroscience data sharing has had its share of headaches (Aldhous, 2000), concerns over data ownership (Editorial, 2000), not to mention the perceived challenges associated with mandatory sharing requirements (Bookheimer, 2000). While technologies have greatly improved concerning migrating datasets from site to site via secured internet connections and their public distribution, many challenges still remain across the biomedical research spectrum (Brayne et al., 2022).

But success stories in the use of communal and public neuroscience data illustrate the importance of sharing. The ENIGMA consortium (Thompson et al., 2020) pools summary neuroimaging and genetics data in an at-scale meta-analytic framework to explore heritable elements of brain connectivity in a variety healthy and disease conditions (Dennis et al., 2018; Kelly et al., 2018; Kong et al., 2018). Data from the Alzheimer’s Disease Neuroimaging Initiative (Weiner et al., 2017) has been utilized in countless examinations of brain morphological differences between Alzheimer’s patients, subjects with mild cognitive impairment, and otherwise healthy older adults. The Allen Brain Institute (Koch & Jones, 2016) openly shares mouse brain atlases, tract tracing data, gene expression, and other information through its attractive website. The UK Biobank – a rich, remarkable, and growing archive of neuroimaging, genomic, biomarker, lifestyle, and health information – has set the bar high for large sample neuroimaging size studies. These and other compendia (Van Horn, 2021) have expanded the utility of their data’s original collection, contributed greatly to current knowledge about brain function, structure, and connectivity, and provided grist for the mill in novel new computational methods (Sanchez-Arias et al., 2021).

So, too, with neuroscience publishing (Bloom, 2000). Open access publishing in neuroscience has long been a desire in the community (Ascoli, 2005) though some publishers showed initial resistance to its adoption (Merkel-Sobotta, 2005). Major publishers offer the option for open access along with traditional print articles, with the absence of paywalls, but charge handsomely for this as a service. Some universities have established new policies fighting back against publishing charges by having their own open access services.Footnote 4 With the advent of popular pre-print servers such as arXiv, bioarXiv, PsyArXiv, and F1000Research, a segment of the community advocate for an overhaul of the dependence on journal publishers, the peer-review system, and what it means to publish one’s research. Several international efforts have worked to define what publication means and have provided guidelines on what publishers can do to better support open access (Boulton et al., 2021) and to support new models of peer review (Prager et al., 2019). With the ‘publish or perish’ model still strongly factoring into university promotion and tenure decision-making, full-scale change may be some time off. Nevertheless, a pathway of manuscript pre-print submission seeding subsequent formal peer-review followed by open online and print publication is taking hold. Accompanied by open data (Poline, 2019), processing provenance (Mackenzie-Graham et al., 2008), and code, may very well alter the landscape of typical career paths in academic research (Katz et al., 1926).

The OSTP policy spells out what should be done but is rather light on the details of how it should be done. The policy may expedite open availability but at what cost and to whom? Access to the published literature may be free but will it be actually free? It is not hard to imagine publishers already scheming to find new ways to charge further publication costs to investigators – and, hence, tax payers – to make research articles openly accessible sans reader subscriptions. Increased costs associated with openness would likely demotivate smaller research groups as well as teams from developing nations from publishing altogether. Science publishing – open or not – may become a game only the richest research centers can play.

Finally, the sharing of data only really works if there is a venue for the data to be shared. This necessitates thoughtful development of robust data repositories, supporting a vast array of neuroscience datatypes, accommodating many spatial and temporal scales, along with appropriate descriptive meta-data (Bourne et al., 2022). Such effort is not trivial and takes time to for the community to develop a sense of trust in these resources (Van Horn & Toga, 2009). Given the NIH’s uneven, boom or bust commitments toward neuroinformatics (Gazzaniga et al., 2006), data science (Bui et al., 2017), and neuroscience databasing (Keator et al., 2016; De Schutter et al., 2006), a dedicated, consistent, and long-term vision for where and how data will be archived will likely be needed.

New government policies in support of easing access to published research, data, software, and other research products, making them findable, accessible, interoperable, and re-useable (FAIR), are widely welcomed as a necessary (Martone, 2022) but not sufficient step toward greater scientific rigor, robustness, and integrity. Time will tell on how the neurosciences and other biomedical disciplines will react to the new OSTP mandates. Hopefully, in a positive light. But one can bet that making neuroscientific research articles and primary data freely available – valuable as they are—will undoubtedly come at a cost.