Development and governance of FAIR thresholds for a data federation
- Wong, Megan, Levett, Kerry, Lee, Ashlin, Box, Paul, Simons, Bruce, David, Rakesh, Macleod, Andrew, Taylor, Nicolas, Schneider, Derek, Thompson, Helen
- Authors: Wong, Megan , Levett, Kerry , Lee, Ashlin , Box, Paul , Simons, Bruce , David, Rakesh , Macleod, Andrew , Taylor, Nicolas , Schneider, Derek , Thompson, Helen
- Date: 2022
- Type: Text , Journal article
- Relation: Data Science Journal Vol. 21, no. (2022), p.
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- Description: The FAIR (findable, accessible, interoperable, and re-usable) principles and practice recommendations provide high level guidance and recommendations that are not research-domain specific in nature. There remains a gap in practice at the data provider and domain scientist level demonstrating how the FAIR principles can be applied beyond a set of generalist guidelines to meet the needs of a specific domain community. We present our insights developing FAIR thresholds in a domain specific context for self-governance by a community (agricultural research). ‘Minimum thresholds’ for FAIR data are required to align expectations for data delivered from providers’ distributed data stores through a community-governed federation (the Agricultural Research Federation, AgReFed). Data providers were supported to make data holdings more FAIR. There was a range of different FAIR starting points, organisational goals, and end user needs, solutions, and capabilities. This informed the distilling of a set of FAIR criteria ranging from ‘Minimum thresholds’ to ‘Stretch targets’. These were operationalised through consensus into a framework for governance and implementation by the agricultural research domain community. Improving the FAIR maturity of data took resourcing and incentive to do so, highlighting the challenge for data federations to generate value whilst reducing costs of participation. Our experience showed a role for supporting collective advocacy, relationship brokering, tailored support, and low-bar tooling access particularly across the areas of data structure, access and semantics that were challenging to domain researchers. Active democratic participation supported by a governance framework like AgReFed’s will ensure participants have a say in how federations can deliver individual and collective benefits for members. © 2022 The Author(s).
- Authors: Wong, Megan , Levett, Kerry , Lee, Ashlin , Box, Paul , Simons, Bruce , David, Rakesh , Macleod, Andrew , Taylor, Nicolas , Schneider, Derek , Thompson, Helen
- Date: 2022
- Type: Text , Journal article
- Relation: Data Science Journal Vol. 21, no. (2022), p.
- Full Text:
- Reviewed:
- Description: The FAIR (findable, accessible, interoperable, and re-usable) principles and practice recommendations provide high level guidance and recommendations that are not research-domain specific in nature. There remains a gap in practice at the data provider and domain scientist level demonstrating how the FAIR principles can be applied beyond a set of generalist guidelines to meet the needs of a specific domain community. We present our insights developing FAIR thresholds in a domain specific context for self-governance by a community (agricultural research). ‘Minimum thresholds’ for FAIR data are required to align expectations for data delivered from providers’ distributed data stores through a community-governed federation (the Agricultural Research Federation, AgReFed). Data providers were supported to make data holdings more FAIR. There was a range of different FAIR starting points, organisational goals, and end user needs, solutions, and capabilities. This informed the distilling of a set of FAIR criteria ranging from ‘Minimum thresholds’ to ‘Stretch targets’. These were operationalised through consensus into a framework for governance and implementation by the agricultural research domain community. Improving the FAIR maturity of data took resourcing and incentive to do so, highlighting the challenge for data federations to generate value whilst reducing costs of participation. Our experience showed a role for supporting collective advocacy, relationship brokering, tailored support, and low-bar tooling access particularly across the areas of data structure, access and semantics that were challenging to domain researchers. Active democratic participation supported by a governance framework like AgReFed’s will ensure participants have a say in how federations can deliver individual and collective benefits for members. © 2022 The Author(s).
Improving the FAIRness of Australia’s grains research sector data
- Willis, Ben, Parker, Julie, Robinson, Nathan, Wong, Megan
- Authors: Willis, Ben , Parker, Julie , Robinson, Nathan , Wong, Megan
- Date: 2019
- Type: Text , Conference paper
- Relation: Proceedings of the 19th Australian Society of Agronomy Conference,25-29 August 2019, Wagga Wagga, NSW, Australia
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- Description: Across Australia’s arable landscapes, thousands of crop trials have been conducted to improve the profitability and sustainability of Australian grain production. Although there have been significant steps to make knowledge gained from trials available to users, there is the potential to further support the development of next generation data models and knowledge products by integrating trials from disparatei sources by adhering to FAIR principles of data management. That is, making data: findable, accessible, interoperable and reusable. This research explores whether Online Farm Trials increase the FAIRness of agricultural grains trial datasets through a comparison of the trial data capture and handling practices of organisations whose datasets are not discoverable through Online Farm Trials (OFT) (N = 50) with the FAIRness of the datasets discoverable through OFT. The findings demonstrate that OFT is helping to make the results of Australia’s grains trials more FAIR to the users of trial data, and suggests a number of improvements to the FAIRness of trial datasets, foremost through the use of machine-readable metadata.
- Authors: Willis, Ben , Parker, Julie , Robinson, Nathan , Wong, Megan
- Date: 2019
- Type: Text , Conference paper
- Relation: Proceedings of the 19th Australian Society of Agronomy Conference,25-29 August 2019, Wagga Wagga, NSW, Australia
- Full Text:
- Reviewed:
- Description: Across Australia’s arable landscapes, thousands of crop trials have been conducted to improve the profitability and sustainability of Australian grain production. Although there have been significant steps to make knowledge gained from trials available to users, there is the potential to further support the development of next generation data models and knowledge products by integrating trials from disparatei sources by adhering to FAIR principles of data management. That is, making data: findable, accessible, interoperable and reusable. This research explores whether Online Farm Trials increase the FAIRness of agricultural grains trial datasets through a comparison of the trial data capture and handling practices of organisations whose datasets are not discoverable through Online Farm Trials (OFT) (N = 50) with the FAIRness of the datasets discoverable through OFT. The findings demonstrate that OFT is helping to make the results of Australia’s grains trials more FAIR to the users of trial data, and suggests a number of improvements to the FAIRness of trial datasets, foremost through the use of machine-readable metadata.
Drivers of seedling establishment success in dryland restoration efforts
- Shackelford, Nancy, Paterno, Gustavo, Winkler, Daniel, Erickson, Todd, Wong, Megan
- Authors: Shackelford, Nancy , Paterno, Gustavo , Winkler, Daniel , Erickson, Todd , Wong, Megan
- Date: 2021
- Type: Text , Journal article
- Relation: Nature Ecology and Evolution Vol. 5, no. 9 (2021), p. 1283-1290
- Full Text: false
- Reviewed:
- Description: Restoration of degraded drylands is urgently needed to mitigate climate change, reverse desertification and secure livelihoods for the two billion people who live in these areas. Bold global targets have been set for dryland restoration to restore millions of hectares of degraded land. These targets have been questioned as overly ambitious, but without a global evaluation of successes and failures it is impossible to gauge feasibility. Here we examine restoration seeding outcomes across 174 sites on six continents, encompassing 594,065 observations of 671 plant species. Our findings suggest reasons for optimism. Seeding had a positive impact on species presence: in almost a third of all treatments, 100% of species seeded were growing at first monitoring. However, dryland restoration is risky: 17% of projects failed, with no establishment of any seeded species, and consistent declines were found in seeded species as projects matured. Across projects, higher seeding rates and larger seed sizes resulted in a greater probability of recruitment, with further influences on species success including site aridity, taxonomic identity and species life form. Our findings suggest that investigations examining these predictive factors will yield more effective and informed restoration decision-making. © 2021, The Author(s), under exclusive licence to Springer Nature Limited. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Megan Wong” is provided in this record** Author Correction: Drivers of seedling establishment success in dryland restoration efforts (Nature Ecology & Evolution, (2021), 5, 9, (1283-1290), 10.1038/s41559-021-01510-3). https://doi.org/10.1038/s41559-021-01544-7
- Description: Restoration of degraded drylands is urgently needed to mitigate climate change, reverse desertification and secure livelihoods for the two billion people who live in these areas. Bold global targets have been set for dryland restoration to restore millions of hectares of degraded land. These targets have been questioned as overly ambitious, but without a global evaluation of successes and failures it is impossible to gauge feasibility. Here we examine restoration seeding outcomes across 174 sites on six continents, encompassing 594,065 observations of 671 plant species. Our findings suggest reasons for optimism. Seeding had a positive impact on species presence: in almost a third of all treatments, 100% of species seeded were growing at first monitoring. However, dryland restoration is risky: 17% of projects failed, with no establishment of any seeded species, and consistent declines were found in seeded species as projects matured. Across projects, higher seeding rates and larger seed sizes resulted in a greater probability of recruitment, with further influences on species success including site aridity, taxonomic identity and species life form. Our findings suggest that investigations examining these predictive factors will yield more effective and informed restoration decision-making. © 2021, The Author(s), under exclusive licence to Springer Nature Limited. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Megan Wong” is provided in this record**
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