From FAIR to FAIRS: Data security by design for the global burden of animal diseases

Stacey, Deborah; Wulff, Kenneth; Chikhalla, Nidhip; Bernardo, Theresa M.

doi:10.1002/agj2.21017

Cited by 5 publications

(7 citation statements)

References 10 publications

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“…Improving the availability of comprehensive and reliable data is an essential step for addressing the challenges that the global food sector is facing, such as how to manage trade-offs between increasing demand and environmental impact, and how to invest in prevention or better management of animal diseases. Therefore, investment and global collaboration in data collection and ‘FAIRS’ness of data (Findability, Accessibility, Interoperability, Reusability, and Secure) is critical to provide improved data driven decision making within the farm animal production sector ( Stacey et al, 2022 ; Wilkinson et al, 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Approximating the global economic (market) value of farmed animals

Schrobback,

Dennis,

et al. 2023

Global Food Security

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Section: Discussionmentioning

confidence: 99%

Approximating the global economic (market) value of farmed animals

Schrobback,

Dennis,

et al. 2023

Global Food Security

Self Cite

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“…The GBADs Informatics team aims to create a community around shared, curated and re-usable data on a single platform. The development of all data products (Table I), including metadata and provenance, is guided by four founding principles: findability, accessibility, interoperability and reusability, commonly known as FAIR principles [16,17].…”

Section: Global Burden Of Animal Diseases Data Strategymentioning

confidence: 99%

Informatics progress of the Global Burden of Animal Diseases programme towards data for One Health

BERNARDO,

RUSHTON,

HUNTINGTON

et al. 2023

Rev. Sci. Tech. OIE

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The Global Burden of Animal Diseases (GBADs) programme will provide data-driven evidence that policy-makers can use to evaluate options, inform decisions, and measure the success of animal health and welfare interventions. The GBADs' Informatics team is developing a transparent process for identifying, analysing, visualising and sharing data to calculate livestock disease burdens and drive models and dashboards. These data can be combined with data on other global burdens (human health, crop loss, foodborne diseases) to provide a comprehensive range of information on One Health, required to address such issues as antimicrobial resistance and climate change.The programme began by gathering open data from international organisations (which are undergoing their own digital transformations). Efforts to achieve an accurate estimate of livestock numbers revealed problems in finding, accessing and reconciling data from different sources over time. Ontologies and graph databases are being developed to bridge data silos and improve the findability and interoperability of data. Dashboards, data stories, a documentation website and a Data Governance Handbook explain GBADs data, now available through an application programming interface.Sharing data quality assessments builds trust in such data, encouraging their application to livestock and One Health issues. Animal welfare data present a particular challenge, as much of this information is held privately and discussions continue regarding which data are the most relevant. Accurate livestock numbers are an essential input for calculating biomass, which subsequently feeds into calculations of antimicrobial use and climate change. The GBADs data are also essential to at least eight of the United Nations Sustainable Development Goals.

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“…In a similar manner, Stacey et al. (2022) emphasize the importance of data security and extend the Findable‐Accessible‐Interoperable‐Reusable (FAIR) framework to include the “Secure by Design” approach and suggest that FAIR be extended to FAIRS data‐sharing framework to explicitly account for security needs.…”

Section: Guide and Synthesis To The Special Issuementioning

confidence: 99%

“…Stacey et al. (2022) and Ault et al. (2022) both highlight frameworks that address a broad range of data related issues.…”

Section: Guide and Synthesis To The Special Issuementioning

confidence: 99%

Big data promises and obstacles: Agricultural data ownership and privacy

2022

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The year 2022 marks the ten-year anniversary of the White House's Big Data Research and Development Initiative. While this initiative, and the others it spawned, helped to advance the many facets of data intensive research and discovery, obstacles and challenges still exist. If left unaddressed these obstacles will persist and at a minimum limit the potential of what can be achieved by harnessing the many new ways to collect, analyze, and share data and the insights that can be drawn from them. The opportunities and challenges related to Big Data in agriculture touch on all aspects of the general research data lifecycle; from instruments used to gather data, to advanced digital platforms used to store, analyze, and share data, and the innovative insights from using advanced computational methods. The eight papers included in this special issue were chosen in part because they highlight both the challenges and the opportunities that come from all stages of the data lifecycle common across agricultural research and development. These papers grew out of several workshops made possible by the support of the Midwest Regional Big Data Hub, which is sponsored by the National Science Foundation.

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From FAIR to FAIRS: Data security by design for the global burden of animal diseases

Cited by 5 publications

References 10 publications

Approximating the global economic (market) value of farmed animals

Approximating the global economic (market) value of farmed animals

Informatics progress of the Global Burden of Animal Diseases programme towards data for One Health

Big data promises and obstacles: Agricultural data ownership and privacy

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