Data Management Sub-team

Applying modern cyberinfrastructure to improve capabilities for integrating and blending data.

Scope of activities

Arctic data, including physical and biological samples and Indigenous Knowledge data, are irreplaceable. Often stemming from difficult and remote conditions, Arctic data are valuable in a time of rapid environmental change driven primarily by climate change. Data management is critical to basic research, monitoring, and applied research in the Arctic. It follows a cycle of data discovery, collection, and sharing; ideally, each step in the data lifecycle contributes to maximizing return on investment in data management. There is great care, review, and often standardization or harmonization in preparing, producing, and publishing data products which allow for their reuse. Nevertheless, customization of global or national tools is often necessary for Arctic applications. As data volumes increase, computational infrastructure and software management are both inextricably part of data management.

A National Academies study outlines best practices related to open, searchable, and rapidly accessible data; there is a need for centralized discovery and access to Arctic data across institutions and agencies. IARPC encourages the adoption of open data collections, development of intelligent data management tools and practices, and use of existing data and metadata platforms to achieve interdisciplinary and interagency coordination. In order to reflect the complexity of Arctic data and knowledge systems, data management for Arctic research must be responsive to a range of partners. Arctic research, participatory research, and data management now operate in an environment of FAIR (findable, accessible, interoperable, and reusable) data management principles and CARE (collective benefit, authority to control, responsibility, ethics) Principles of Indigenous Data Governance. While working toward open and accessible data, it is important to recognize these nuanced approaches that protect private and sensitive data, and to respect Indigenous data sovereignty and governance.

Continued international joint cooperation, innovation, and learning in all aspects of data management are integral to facilitating Arctic research. Working with international partners to implement harmonized standards and practices will make Arctic data more readily available and will improve U.S. Arctic research. Innovations in data collection, curation, discoverability, and use, such as new advances in artificial intelligence (AI), machine learning, and cloud computing, will be essential to fully use Arctic data.

IARPC will share best practices, innovative ideas, lessons learned, and networking opportunities as it works towards discoverability, understanding, and interoperability of Arctic data and tools. IARPC will help strengthen data management literacy and expertise by proactively connecting federal agencies, local partners, early career scientists, established researchers, Indigenous Knowledge holders, and others. IARPC is in a position to develop a culture around thoughtful data management (i.e., FAIR and CARE) and encourage the development of skills and knowledge related to advancing data management in the Arctic. IARPC is able to facilitate access to Arctic data by being a forward-looking space that can stimulate dialogue between diverse sectors to embrace actionable science.

As agencies work towards sharing data across the government and with the public, IARPC will be a strong partner and bridge towards achieving their Arctic research goals. Data management is rooted in federal policy and mandated for federal research agencies. Data sovereignty and CARE principles need to be considered in the context of federal data policies. Clear guidance, aligned with FAIR and CARE, on how to manage data compliant with these broad federal mandates can benefit those who enable Arctic insights and can support data users, providers, and managers in achieving their aims. federal agencies should aim to make data more discoverable, connected, and useful, emphasizing meaningful new Arctic insights. Therefore, this plan pursues responsive, responsible, and well-resourced application of best practices in Arctic data management.

Team leaders

Allen Pope
NSF (Website)

Michael Brady
National Geospatial-Intelligence Agency (Website)

Performance elements from the Arctic research plan


Under the Arctic Research Plan 2017-2021, the Data team:

  • Shared information about federal agency data science projects that supported data management capabilities for Arctic researchers.
  • Advanced tools developed to help Alaska Arctic communities understand and adapt to climate chang.
  • Shared information about mapping the marine environment, ground ice content, and other parts of the cryosphere.
  • Shared information about data that support Arctic operators, such as data on icebreaker efficacy and research on artificial intelligence and machine learning approaches to satellite based measurement of sea ice and coastal change.

For a full summary of the Data team's accomplishments under the 2017-2021 Arctic Research Plan, see the 2021 Performance Element Summary Statements.