Figure 1: Data is derived from 52 participants of the survey who answered what career stage they were currently in. Not all respondents from the survey were required to answer.
Over the past year, Arctic research has continued to evolve at a rapid pace, shaped by shifting environments, new technologies, and changing funding landscapes, along with growing expectations around data access, stewardship, and collaboration. As these pressures and opportunities converge, developing research infrastructure that can keep up with the evolving needs of the community it serves is imperative.
To better understand these emerging needs, the Arctic Data Center launched its 2026 Community Survey, inviting anyone who works with Arctic data to share their experiences, challenges, and priorities. The survey provides a snapshot of how workflows, data practices, and support needs are shifting in real time, including how individuals are navigating evolving funding realities and resource constraints with an increasingly complex data environment.
This year, 118 responses were collected, offering valuable insight into the current Arctic researcher community and where additional support, tools, and investment can make the greatest impact. In this article, we highlight key findings from the survey and reflect on how they will help shape the Arctic Data Center’s efforts moving forward.
Who We Heard From
Figure 2: Data is derived from about 35 participants of the survey who answered what discipline they are involved in. Not all respondents from the survey were required to answer.
Survey respondents represented a wide range of career stages, from students and early career researchers to senior career professionals with over 25 years of experience (Fig. 1). This diversity provided a broad view of how needs shift across the research lifecycle and career stages.
In terms of scientific discipline, respondents reflected the interdisciplinary nature of Arctic research (Fig. 2). Participants identified with fields spanning physical science, life science, computer science, arts and humanities, social science, and more. This range highlights the importance of supporting data practices and tools that are flexible and relevant across multiple domains, as well as the growing integration of diverse knowledge systems and approaches.
Survey questions centered around our three key areas of focus at the Arctic Data Center: data services, cyberinfrastructure, and community engagement and outreach.
Perspectives on Data Use and Sharing
Figure 3: Data is derived from 61 participants of the survey who answered if they do or do not work with large datasets in their research. Not all respondents from the survey were required to answer.
Data sharing requires additional time and care to ensure datasets are accessible and reusable, and our support for the full data lifecycle ensures that data remains FAIR (Findable, Accessible, Interoperable, and Reusable). Most survey participants reported insufficient time and resources to prepare and make their data accessible online. This is often a challenge recognized by other researchers in the broader scientific community. Yet, most participants also shared that they are generally satisfied with the Arctic Data Center’s archiving standards, and found our data curation team to be supportive and responsive to their individual needs.
Figure 4: Data is derived from 34 participants who answered they work with large datasets in their research. Not all respondents from the survey were required to answer.
Increasingly, we are seeing researchers work with—and submit—very large datasets. More than half of survey participants reported working with large datasets (roughly larger than 0.45 TiB or more than 250 files)(Fig. 3), highlighting a clear shift in research practices. Over the past few years, this trend has translated into a growing number of large dataset submissions, some reaching up to dozens of terabytes or more in size. This has resulted in a significant increase in data storage and staff time required to carefully review datasets before publishing. One notable dataset example is Newman et al., a 127 TiB model output published in March 2026. The dataset details hydroclimate simulations across Alaska and the Yukon River and has a related published paper describing its functionality and utility beyond the science community. The scale of this one dataset alone dramatically increased the size of our repository. Another example is a dataset by Dominik Gräff containing distributed acoustic and temperature sensing data (DAS/DTS) near the Greenland Ice Sheet that totaled about 13 TiB. Respondents who work with large datasets indicated that clear guidance on file formats and organization, data science training opportunities, and more data processing and quality control support would be most valuable for handling large datasets from the Arctic Data Center (Fig. 4). To better support large data submissions like these, we’ve released an updated large model output policy containing clear recommendations for file formats and data organization. Read more here.
One of the most developed data portals is the Permafrost Discovery Gateway (PDG), which includes features like geospatial data layer visualizations on interactive maps and virtual permafrost tours that help users understand how permafrost is affecting communities across the Arctic. In addition, the PDG features stories from the Local Environmental Observer (LEO) Network, which discusses different scientific data with the perspectives of community members. Other data portals such as the State of Alaska Salmon and People (SASAP) have a unique focus that is thematic and regional. This data portal includes our latest feature to embed a Shiny app, which allows for a different interactive experience with the data.
Custom Geospatial Maps
This video demonstrates a custom portal map page on the Permafrost Discovery Gateway, showing how datasets, like retrogressive thaw slump measurements, can be explored interactively. Users can zoom, pan, and filter visible data layers.
Have an idea for an interactive data layer in your portal? Reach out to our data curation team to get started: support@arcticdata.io
Based on the other feedback from survey participants, we’re prioritizing several improvements to make the data submission process smoother and more efficient. Some of these improvements include recommendations for archiving code and software products, making required file formats easier to find, and streamlining metadata entry with autofill and duplication options. Additionally, we’ll add enhancements to existing data portal tools and systems. We look forward to continuing to advance what’s available to the Arctic science community.
Cyberinfrastructure Advancements
Survey respondents also provided feedback specifically related to our cyberinfrastructure tools and services, including data submission workflows, data quality assessments, and ways to better track dataset use and updates. Over the past year, we have released 20 improvements to our Metacat and MetacatUI software, which has enhanced the user experience in both data discovery and online data submission. Some of the more user-targeted tools released include a customizable feed on the data portals, map features filtering polygons by attribute, improved data assessment checks, prevention of duplicate data packages, and support for copying attributes via reference linking during data submission.
Our development team also has an active pipeline of future improvements targeting our backend and frontend services. One currently available tool is our metadata quality assessment feature, which allows users to determine whether their datasets meet established standards and identify where metadata could be strengthened. Another upcoming feature is a notification service system, which will alert Arctic Data Center users about updates on a specific dataset. Through this new tool, users will receive a notification via email whenever a dataset has been updated, such as adding, replacing, or removing files, and when a dataset has been cited. The ability to collect deeper citation metrics in the notification service system directly reflects feedback from researchers, both from our survey and external communications. While this feature is still under development, we aim to have a test version available on the Arctic Data Center before Fall 2026.
Highlighting Training and Support Needs
Survey respondents also highlighted several opportunities to improve user support, training resources, and overall navigation of our online resources. Feedback included requests for clearer information on accepted data file types, better guidance for preparing and de-identifying data, and improvements in how users discover datasets, news, and other resources online. Respondents also expressed interest in additional training topics related to large geospatial datasets, AI applications in Arctic science, metadata creation workflows, and data licensing practices.
Our annual data science training courses continue to support researchers and students in developing skills in data management, reproducibility, data publication, analysis tools, and much more, with the goal of helping participants apply these approaches within their own research environments. Many topics identified in the survey are already covered in our current course offerings, including working with data in R, cloud computing, scalable processing, data sovereignty, workflow management, data publication, and more. However, with a rapid and ever-changing data landscape, survey participants expressed interest in learning about more tools in AI, data visualization, and handling of large datasets, and we are actively looking to incorporate these topics more into our future course offerings.
Survey respondents also highlighted the importance of improving the accessibility and visibility of online resources. In response, we are exploring ways to make information about accepted file types and data preparation guidance more prominent across our website, while also considering additional online resources focused on topics such as data de-identification and licensing. Respondents also noted mixed experiences discovering datasets and opportunities at the Arctic Data Center. As part of our ongoing outreach efforts, we are evaluating ways to improve overall website usability and accessibility.
While we continue to address the Arctic research community’s needs, navigating budgetary concerns has meant that we can no longer offer some of our annual training courses. However, as we move into our next phase, we are expanding our outreach efforts to include a variety of webinars and office hours designed to help users with their data processing needs. Preliminary topic ideas include help with data submissions, creating data portals, structuring metadata, and more.
Importance in Community Feedback
We thank all survey participants who took the time to provide their feedback and suggestions on new tools and services to support all Arctic Data Center users and the broader Arctic research community. Our team will continue to carefully review feedback from the community to find more ways to improve our cyberinfrastructure and remain committed to our mission of effective data preservation. As we close out this NSF Award (#2042102) and move into our next phase, we’re excited to continue supporting the Arctic research community and open science initiatives by providing tools, resources, and data science training courses for users to preserve and access their data through our platform. Our next phase prioritizes increasing the accessibility and usefulness of Arctic data for researchers, communities, and beyond.
If you have any questions or feedback to share with the Arctic Data Center, please email info@arcticdata.io. For any other data support services, contact support@arcticdata.io.