A new flow for Canadian young hydrologists: Key scientific challenges addressed by research cultural shifts

Aubry‐Wake, Caroline; Somers, Lauren; Alcock, Hayley; Anderson, A. M.; Azarkhish, Amin; Bansah, Samuel; Bell, Nicole M.; Biagi, Kelly; Castañeda-González, Mariana; Champagne, Olivier; Chesnokova, Anna; Coone, Devin; Gauthier, Thierry; Ghimire, Uttam; Glas, Nathan; Hrach, Dylan; Lai, Oi Yin; Lamontagne‐Hallé, Pierrick; Leroux, Nicolas; Lyon, Laura; Mandal, Sohom; Nasri, Bouchra; Popović, Nataša; Rankin, Tracy; Rasouli, Kabir; Robinson, Alexis; Sanyal, Palash; Shatilla, Nadine J.; Huizen, Brandon Van; Wilkinson, Sophie; Williamson, Jessica; Zaremehrjardy, Majid

doi:10.1002/hyp.13724

Cited by 3 publications

(9 citation statements)

References 33 publications

(30 reference statements)

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“…Standards should be agreed upon and adopted by all stakeholders, and changes should only be made with consensus from the group (Nielsen, 2015), otherwise it will be difficult to compare data across different research groups or partner organizations (Aubry‐Wake et al, 2020). If it is not possible to conform to a standard at the data collection or provision stage, a ‘crosswalk’ can be generated later to map existing structures and metadata attributes to the desired structure and facilitate data comparison.…”

Section: Best Practicesmentioning

confidence: 99%

“…The cost of field research, the vast size of Canada, the transitory nature of data collection opportunities, and a scarcity of long‐term data records make water science data especially valuable. Access to well‐managed data is crucial for researchers to develop insight into Canada's most pressing issues and to inform effective solutions; but data can be hard to find (Aubry‐Wake et al, 2020). The COVID‐19 pandemic has also highlighted the importance of having data to inform timely response decisions in crisis management and amplified the hindrance caused by disparate data collection, access and compatibility issues (Hurley, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…GWF and other groups are advocating for equitable access to RDM resources to support the needs of all researchers in Canada (DuBois et al, 2020; Dukacz et al, 2020). However, there are many ways individual researchers can start now to address the RDM challenges, accessibility and usability issues identified by Aubry‐Wake et al (2020). In this paper, these challenges are addressed through 10 RDM best practices that, together, form a general framework to help both early career and established researchers implement effective data management practices, promote change and strengthen data stewardship in the water science community (Table 2).…”

Section: Introductionmentioning

confidence: 99%

“…Even with these significant strides, Canadian water science data are often managed in ways that make data retrieval and analysis time consuming and expensive, and research collaboration challenging (Aubry‐Wake et al, 2020; GWF, 2019). This is a significant loss for science; historical field observations cannot be recaptured, and these data are key to understanding past and future trends (Gudmundsson et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Overall, data that have been poorly managed or are not well described, and data that are inaccessible, can be considered a waste of research resources (Buxton et al, 2021). Early career researchers (ECRs) in Canada highlighted two main data challenges related to water science: data accessibility (i.e., hidden and scattered data) and data usability (i.e., insufficient metadata) (Aubry‐Wake et al, 2020). These issues are recognized by researchers at all career stages.…”

Section: Introductionmentioning

confidence: 99%

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Ten best practices to strengthen stewardship and sharing of water science data in Canada

Persaud

Dukacz²,

Saha

et al. 2021

Hydrological Processes

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Water science data are a valuable asset that both underpins the original research project and bolsters new research questions, particularly in view of the increasingly complex water issues facing Canada and the world. Whilst there is general support for making data more broadly accessible, and a number of water science journals and funding agencies have adopted policies that require researchers to share data in accordance with the findable, accessible, interoperable, reusable (FAIR) principles, there are still questions about effective management of data to protect their usefulness over time. Incorporating data management practices and standards at the outset of a water science research project will enable researchers to efficiently locate, analyse and use data throughout the project lifecycle, and will ensure the data maintain their value after the project has ended. Here, some common misconceptions about data management are highlighted, along with insights and practical advice to assist established and early career water science researchers as they integrate data management best practices and tools into their research. Freely available tools and training opportunities made available in Canada through Global Water Futures, The Gordon Foundation DataStream, the Digital Research Alliance of Canada Portage Network, Compute Canada, and university libraries, among others are compiled. These include webinars, training videos, and individual support for the water science community that together enable researchers to protect their data assets and meet the expectations of journals and funders. The perspectives shared here have been developed as part of the Global Water Futures programme's efforts to improve data management and promote the use of common data practices and standards in the context of water science in Canada. Ten best practices are proposed that may be broadly applicable to other disciplines in the natural sciences and can be adopted and adapted globally.

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Section: Best Practicesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Ten best practices to strengthen stewardship and sharing of water science data in Canada

Persaud

Dukacz²,

Saha

et al. 2021

Hydrological Processes

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Canada Source Watershed Polygons (Can-SWaP): A dataset for the protection of Canada’s municipal water supply

Robinne,

Lamache,

Thompson

et al. 2023

Sci Data

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Over 80% of municipal (i.e., excluding industrial and agricultural) water use in Canada comes from streams, lakes, and reservoirs. These freshwater bodies and their catchments require adequate protection to secure drinking water supply for Canadians. Canada, like most countries, lacks a consolidated national dataset of municipal catchments, arguably due to gaps in data availability. Against this backdrop, we present the Canada Source Watershed Polygons dataset, or Can-SWaP. Can-SWaP was created using point locations of more than 3,300 municipal water licences defining rights to surface water withdrawal. Where possible, the resulting 1,574 catchments were assessed for accuracy in spatial coverage against provincial and local datasets. Each watershed in Can-SWaP has an estimated water volume used for municipal water purposes derived from licencing data, and several variables from RiverATLAS for investigating the integrity of surface drinking water sources in Canada. Furthermore, basing our method on the HydroSHEDS suite of global products offers a robust framework for the production of other national datasets following an established international standard.

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Guiding principles for transdisciplinary and transformative fire research

Copes-Gerbitz,

Sutherland,

Dickson-Hoyle

et al. 2024

fire ecol

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Background Managing landscape fire is a complex challenge because it is simultaneously necessary for, and increasingly poses a risk to, societies and ecosystems worldwide. This challenge underscores the need for transformative change in the way societies live with and manage fire. While researchers have the potential to act as agents of transformative change, in practice, the ability to affect change is often constrained by siloed and biased expertise, rigid decision-making institutions, and increasingly vulnerable social-ecological systems where urgent rather than long-term solutions are prioritized. Addressing these challenges requires more holistic and equitable approaches to fire research that promote new models of transdisciplinary thinking, collaboration, and practice. Results To advance transformative solutions to this complex fire challenge, we propose four principles for conducting transdisciplinary fire research: (1) embrace complexity, (2) promote diverse ways of knowing fire, (3) foster transformative learning, and (4) practice problem-centered research. These principles emerged from our experience as a group of early-career researchers who are embedded within and motivated by today’s complex fire challenge within British Columbia (BC), Canada. In this forum piece, we first describe the four principles and then apply the principles to two case studies: (1) BC, a settler-colonial context experiencing increased size, severity, and impacts of wildfires, and (2) our ECR discussion group, a space of collective learning and transformation. In doing so, we present a unique contribution that builds on existing efforts to develop more holistic fire research frameworks and demonstrates how application of these principles can promote transdisciplinary research and transformation towards coexistence with fire, from local to global scales. Conclusions In this forum piece, we identify and apply four guiding principles for transdisciplinary fire research. Collectively, these principles can foster more inclusive applied fire research that matches the scope and scale of today’s fire challenge and promotes transformative change towards coexisting with fire.

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A new flow for Canadian young hydrologists: Key scientific challenges addressed by research cultural shifts

Cited by 3 publications

References 33 publications

Ten best practices to strengthen stewardship and sharing of water science data in Canada

Ten best practices to strengthen stewardship and sharing of water science data in Canada

Canada Source Watershed Polygons (Can-SWaP): A dataset for the protection of Canada’s municipal water supply

Guiding principles for transdisciplinary and transformative fire research

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