New Publication: New CSIRO research identifies skills and methods scientists need when using data to support environmental decisions with Indigenous and local communities

Digital solutions to track changes in environmental conditions often fail to capture the unique components of local land and seascapes, and undermine expressions of distinct Indigenous and local knowledge and systems.

That is a key finding of a new paper from CSIRO that examines the proliferation of digital technologies and analytical tools now available to quantify and assess the environment, and to support environmental decision making.

The team concludes that there is a pressing need for conservation scientists to develop new methods and skills that embrace data justice, and not only safeguard but empower Indigenous and local community knowledge and environmental stewardship. 

Published in the leading journal Biological Conservation, the paper was led by Dr Cathy Robinson as part of the Valuing Sustainability Future Science Platform (VS FSP).

“Data justice refers to the need for fairness in the way that people and places are represented through data and fairness in the choices that are made as the result of that data,” explains Dr Robinson.

“Mitigating the risks of data injustice will require our research teams to adopt new approaches, including working collaboratively with place-based communities to co-design digital infrastructure, modelling techniques, agreements and data practices.”

The increasing use of environmental data and what that means for data justice

Environmental data is the term used for recorded information that helps us learn more about ecosystems and biodiversity.

From the Amazon to the Arctic – using a combination of field work, remote sensing and citizen science – researchers are now collecting more environmental data than at any previous point in history.

“Some of the cutting-edge research led by CSIRO includes projects that weave big data analytics and local community collaborations to solve complex environmental problems,” notes Dr Andrew Hoskins, a Senior Research Scientist who is a co-author on the paper. “That work ranges from understanding koala population status and trends to managing feral herds in remote regions of Australia.”

The planning, collection, management, processing, analysis and translation of environmental data has become an integral part of research programs tackling national and international sustainability issues.

However, there is growing recognition that that our research teams need new approaches and areas of research expertise that enable us to work with diverse knowledge systems and values and to recognise how to negotiate the power of data as basis for environmental decision-making.

Despite the development of ethical protocols and guidelines to try and address potential risks caused by data-driven solutions to Indigenous and local communities, the research published in Biological Conservation notes that there are few guidelines to ensure data justice informs data practices along the data supply chain.

At the data collection stage, for instance, the increased use of remotely-driven data and drone imagery can challenge Indigenous sovereignty rights in controlling territorial information by making sacred sites visible; can ignore local community refusals to be researched through data collection activities; and can impact on people’s privacy.

At the data management and processing stage, there is still dependence on expensive digital infrastructures and software that requires a high level of expertise to operate – which restricts the ability of local communities to access data that may impact them.

While there is broad consensus that the principles of data justice must become fully embedded in research methods, and that better collaboration is needed between researchers and the place-based communities that are often the focus of their research, more guidance is needed to inform how scientists can apply data justice in practice.  

The recent paper from CSIRO explores some of these complex issues, and works to identify ways to close the implementation gap between data justice standards and commitments and the reality of how these are negotiated and implemented on the ground.

How did the team approach this research?

This critical reviewof place-based data justice practices for collaborative conservation research has two key components.

First, a team of modellers, quantitative ecologists and social scientists reviewed published literature that examines how scientists are negotiating data collection, analysis and translation practices with place-based communities. Second, the team reflected on their own research skills and backgrounds to reflect on how insights from the review could inform data justice innovations and best practice.

Like much of the work done by the Valuing Sustainability FSP, the group working on this paper took a multidisciplinary approach and met regularly to enable postdoctoral researchers to learn from debates and engage in the writing process. This reflexive research method encouraged the team to identify and recognise their own potential biases. Senior researchers on the team shared their own experience working on collaborative research projects and the challenges and opportunities of integrating data modelling and analytics into local governance systems and priorities.

“We took that reflexive approach because really it is core to this kind of work,” explains Dr Robinson. “We’re building the capacity of this team – this next generation of scientists – to show how to work with different disciplines and with local and Indigenous communities. When everyone involved in the process has to explicitly consider what position they are coming from, that can create tensions but it also creates some innovative insights.”

Dr Hoskins, whose research focus is quantitative biology, agrees that bringing onboard researchers from different disciplines was a valuable exercise that helped build new skills that need to be applied across the entire data supply chain.  

“Key to this effort is the development of collaborative methods and approaches that are technically robust and also socially accepted, trusted and understood by the broader community,” he explains.

What are the key findings and what happens next?

One important way in which this paper contributes to the broader discussion on data justice is by using the information gathered through the literature review to conduct an analysis of the entire data supply chain as it applies to place-based research.

Rather than looking at one part of the system, such as data collection or data processing in isolation, the research team undertook an analysis of every step: planning, collection, management, processing and analysis, and translation.

According to Dr Robinson, this innovative approach enabled the team to identify where there are particular weaknesses in the system, and where researchers – including CSIRO researchers – need to intensify their efforts.

“It was quite interesting for us that the analysis revealed there has already been quite a bit of work done around data collection, and how to do that well,” she says.

Dr Hoskins agrees and notes “The review highlighted that a lot of collaborative methods have been developed to inform data collection and data translation, and researchers have explored how to incorporate data justice principles at these stages. But there’s a bit of a black spot in the middle of the process – where the modelling and processing takes place – where there is still significant work to do to guide responsible and inclusive modelling and analytical approaches.”     

For Dr Robinson, the importance of this research paper is twofold. Conducting a robust, rigorous analysis of the literature on place-based data justice practices is a valuable exercise that will help inform the ongoing debates around national and international conservation and sustainability policies and frameworks. 

But equally important is how to build the capacity of our next generation of researchers.

“The gap between data justice standards and the way those standards are actually negotiated in each-place based context is a gap that scientists have a responsibility to address,” she says. “That’s particularly true for researchers who are non-Indigenous, whose research is on Indigenous land or with Indigenous communities, and who often lead the technical data design and analytical components of environmental research. This is not a theoretical endeavour. It’s something we’re all grappling with, and it’s crucial that we collaborate to get it right.”

Author – Ruth Dawkins