D8.2 Final Synthesis and Roadmap for further evolution of the pan-AOSS
Bibliographic record
Abstract
The Arctic is undergoing unprecedented environmental transformation, with temperatures rising nearly four times faster than the global average. These dramatic changes, such as melting ice, extensive wildfires, and shifting ecosystems, demand a coordinated, adaptive, and inclusive approach to environmental monitoring. This requires a shift away from fragmented and siloed efforts and towards a more cohesive network. One that is inclusive of scientific knowledge, Indigenous Knowledge, and local knowledge, while delivering actionable knowledge for decision-makers, businesses, researchers, and local people alike. Arctic PASSION, an EU and Canadian funded initiative, has spent the past four and a half years working together in international collaboration to build this vision by strengthening the components and connection of the many observing systems that make up the Arctic Observing System of Systems (AOSS). By doing so Arctic PASSION has enhanced our capacity to monitor, interpret, and respond to Arctic change in ways that are both scientifically robust and socially relevant. At its core, the AOSS addresses a fundamental challenge: no single organisation or technology can comprehensively monitor the vast, complex Arctic environment. Instead, the system connects diverse observing efforts, from satellite networks to community-based monitoring, into an interconnected framework that produces reliable, accessible information for climate adaptation, sustainable resource management, and emergency response. Arctic PASSION has significantly advanced this system by fostering inclusive governance structures that empower Indigenous Peoples and Arctic residents as equal partners in observation design and implementation.The project's co-creation of the Event Database of Community-Based Monitoring stands as a groundbreaking achievement, preserving and presenting previously unreleased Indigenous Knowledge while providing unprecedented insights into Arctic environmental change. Similarly, the establishment of Shared Arctic Variables Expert Panels has created structured platforms where Indigenous knowledge holders collaborate with scientists to define observing priorities that reflect both cultural values and scientific rigor. The project has also significantly advanced how Arctic data is collected, processed, and utilized for society. Through innovative services such as the Arctic Landscape EXplorer (ALEX) for permafrost monitoring, the Integrated Fire Risk Management (INFRA) service for wildfire information and many more, Arctic PASSION has demonstrated how observations can be transformed into practical tools for community resilience and policy development. These services, partly co-designed with Indigenous communities and local authorities, exemplify the project's commitment to making data not just available, but truly actionable. The enhancement of data interoperability, semantic mapping and catering the SAON Data Portal has further ensured that Arctic information can flow seamlessly between scientific repositories and decision-making processes, adhering to both FAIR, CARE and TRUST principles to maintain ethical standards and cultural relevance.In the field of Arctic observation and monitoring governance Arctic PASSION has played a pivotal role in strengthening international coordination. The project's successful advocacy for 'GEO Convener' status for Arctic GEOSS has elevated the region's profile in global observing systems, while its support for the Arctic Ocean Regional Alliance (ArORA) and the expansion of the Distributed Biological Observatory (DBO) concept has established a stable framework for marine observations, and the support of INTERACT has strengthened the terrestrial network. Intense interaction with local and regional policy and decision-making players offered important insights into their needs and their offerings. These governance advancements have been complemented by efforts to maintain dialogue during geopolitical disruptions, ensuring that Arctic observing remains a collaborative endeavour even in challenging circumstances. Looking ahead, the future of the AOSS must build on such foundations while addressing persistent challenges. Sustainable, long-term funding remains critical to maintain observing networks that can detect and respond to Arctic changes over decades rather than project cycles. The inclusion of Indigenous Peoples and other Arctic residents must continue to evolve from consultation to genuine co-leadership, with simplified and accordingly realigned funding processes. Holistic approaches including different Knowledge Systems are needed and require open minds and capacity building on all sides. Science - policy/decision-making communication channels need strengthening to ensure that research informs action and that societal needs guide observing priorities. Advances in technologies like AI, autonomous systems and community-based monitoring will reshape the AOSS. These and other developments must be carefully balanced with ethical considerations and Indigenous data sovereignty principles.The Arctic PASSION experience has shown that building a truly effective observing system requires more than technical solutions, it demands trust, meaningful engagement, and a commitment to equity at every level. Our project's most relevant legacy lies not just in the tools and services it has developed, but in the collaborative relationships it has fostered between scientists, Indigenous communities, and local decision- and policymakers. As climate change continues to reshape the Arctic at an accelerating pace, this integrated, inclusive approach to observing will be essential for developing the resilience and adaptive capacity needed to navigate the challenges ahead. The time has come to transition from demonstration projects to sustained implementation, ensuring that the AOSS becomes a funded, permanent, yet evolving system that serves both the Arctic and the global community for the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.108 | 0.022 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".