Beyond Silos: Data Management as a Lever for Scientific Collaboration on Canada’s Oceans

In Canada, discussions about scientific collaboration often focus on international consortia, partnerships between private and academic actors, or innovation more broadly. Yet one of the main obstacles to collaboration remains less visible: the fragmentation of data management practices across disciplines, regions, and linguistic communities.

Ocean science illustrates this reality well. Contemporary maritime issues such as coastal erosion, climate change, the governance of marine territories, coastal planning, biodiversity, maritime transport, or resource exploitation require collaboration across a wide range of scientific disciplines (oceanography, geography, urban planning, engineering, sociology, history, archaeology, public policy, and data science). These issues extend far beyond traditional disciplinary boundaries.

However, making data truly accessible and usable across these different fields remains a major challenge.

Researchers working on ocean-related questions produce diverse and increasingly complex research outputs: tabular data, satellite images, geospatial data, environmental models, interviews, ethnographic notes, digital archives, social media corpora, or mixed data. While each of these materials carries considerable scientific value on its own, they often remain scattered across research teams, universities, or organizations. When connected, cross-referenced, and made interoperable, however, their potential becomes even greater and more decisive. Together, they can become a genuine lever for transforming ecosystems and societies.

To illustrate this potential, consider the data contained in the logbooks of 18th-century maritime expeditions. These documents are often studied by historians and archaeologists interested in life aboard ships, navigation practices, or the trade of the era. Yet these same archives also hold a wealth of environmental information — temperatures, weather conditions, wind patterns, or ice conditions — that can be used by environmental science research teams. Once structured and made accessible, this data provides valuable reference points for better understanding the climate before the industrial era. This example shows that the value of a piece of data often extends beyond the discipline that produced or first used it, and that its full potential emerges when it can be reinterpreted and mobilized by other research communities.

With national open science initiatives (data spaces, the Digital Research Alliance of Canada) and recent investments in collaborative ocean research (Transforming Climate Action, the Apogée Fund), Canada today has a significant opportunity to build bridges between scientific communities by participating in international discussions on how research data is organized, documented, and shared across sectors and regions. This involves collaboration not only between francophone and anglophone institutions, but also between disciplines that sometimes understand the very term “data” quite differently.

For several decades, the marine natural sciences have developed infrastructures, standards, and procedures that are widely recognized internationally for sharing their datasets. The social sciences and humanities have much to learn from these models of standardization and reuse potential. Conversely, the natural sciences today find themselves facing challenges for which the social sciences and humanities hold recognized expertise: data governance, handling of sensitive data, relationships with communities, consent, local and Indigenous knowledge, and the contextualization of the data produced.

Data — including data about oceans and the communities who live alongside them — is never neutral. It is embedded in specific social, political, economic, and territorial contexts. This reality becomes particularly important in a context where discussions about artificial intelligence, open science, and mass data sharing sometimes tend to present data as a purely technical and universal object.

Breaking down disciplinary silos requires recognizing that every scientific community holds part of the solution needed for responsible, effective, and inclusive research data management. Each discipline contributes, in its own way, to strengthening the quality, governance, interoperability, and responsible use of data, while respecting the social, cultural, and territorial contexts in which it is produced.

Scientific collaboration must be built on a logic of reciprocity, dialogue, and complementarity.

Building a more connected Canadian scientific ecosystem means investing not only in technological infrastructure, but also in training, bilingual resources, common standards, and communities of practice that connect researchers across disciplinary and provincial boundaries.

Canada’s scientific future will depend not only on our capacity to produce more research, but also on our capacity to better circulate knowledge across disciplines, regions, and linguistic communities. In a country as inherently maritime as Canada, research data is not merely a technical resource: it is a foundational element of our shared way of life.

If Canada wants to build a more connected, inclusive scientific ecosystem capable of meeting the ocean challenges of the 21st century, then collaborative approaches to data management and sharing must be fully part of the conversation.

References:

Akers, Katherine G., et Jennifer Doty. 2013. « Disciplinary Differences in Faculty Research Data Management Practices and Perspectives ». International Journal of Digital Curation 8 (2): 5‑26. https://doi.org/10.2218/ijdc.v8i2.263.

Bingham, Andrea J. 2023. « From Data Management to Actionable Findings: A Five-Phase Process of Qualitative Data Analysis ». International Journal of Qualitative Methods 22 (octobre): 16094069231183620. https://doi.org/10.1177/16094069231183620.

Higgins, Stefan, Lisa Goddard, et Shahira Khair. 2024. « Research Data Management in the Humanities: Challenges and Opportunities in the Canadian Context ». Digital Studies / Le Champ Numérique 14 (1). https://doi.org/10.16995/dscn.9956.

Ortenzi, Kate M., Veronica L. Flowers, Carla Pamak, Michelle Saunders, Jörn O. Schmidt, et Megan Bailey. 2025. « Good Data Relations Key to Indigenous Research Sovereignty: A Case Study from Nunatsiavut ». Ambio 54 (2): 256‑69. https://doi.org/10.1007/s13280-024-02077-6.

Weidmann, Nils B. 2023. Data Management for Social Scientists: From Files to Databases. 1re éd. Cambridge University Press. https://doi.org/10.1017/9781108990424.