Building on Aotearoa New Zealand’s Integrated Data Infrastructure

Jones, Craig; McDowell, Anna K.; Galvin, Vince; Adams, David S.

doi:10.1162/99608f92.d203ae45

Cited by 5 publications

(6 citation statements)

References 3 publications

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“…The full workflow and details are available in other articles in this special issue (Emecz et al, 2024;Zdawcyk et al, 2024).…”

Section: The Link Between the Data Usage Platform And Incentivesmentioning

confidence: 99%

An Invisible Hand for Creating Public Value From Data

Lane,

Spector,

Stebbins

2024

Harvard Data Science Review

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In this article we describe how data usage statistics could be designed to reward the contributions of both researchers and government agencies, functionally creating a carrot that rewards engagement. We provide a concrete use case-the Democratizing Data pilot project-and discuss how the results could be used to develop a community-driven incentive structure, or an 'invisible hand,' to generate better evidence for policymakers and lower costs for the taxpayer. We also note the potential to extend the approach and platform to other data-driven initiatives, notably investments in artificial intelligence.

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“…The full workflow and details are available in other articles in this special issue (Emecz et al, 2024;Zdawcyk et al, 2024).…”

Section: The Link Between the Data Usage Platform And Incentivesmentioning

confidence: 99%

An Invisible Hand for Creating Public Value From Data

Lane,

Spector,

Stebbins

2024

Harvard Data Science Review

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“…The advantage of such a classification approach is that most common terms that AI researchers use can change rapidly-for example, from neural networks, to deep learnings, to beta transformers, to large language models -while the people doing the work are much more persistent (Owen-Smith, 2024). Indeed, the term 'data set' itself may become archaic because as it is becoming more common, researchers may find more utility in combining or linking data sets produced from different sources, rather than relying on one individual data set to answer a particular research question Chang et al, 2022;Jones et al, 2022). Data producers and data users can, of course, be the same person in such a context, and the distinction is only a function of the way in which they engage with a particular data set during its life cycle.…”

Section: A Machine Learning Approach To Generating Data Labelsmentioning

confidence: 99%

Searching for How Data Have Been Used: Intuitive Labels for Data Search and Discovery

Zdawczyk,

Lane,

Rivers

et al. 2024

Harvard Data Science Review

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Data access, use, and reuse are crucial for empirical science and evidence-based policymaking, and rely on metadata to facilitate data discovery and utilization by users and producers alike. Metadata quality is pivotal for the federal government to understand data available for evidence building, enabling agencies to identify data production gaps and redundancies, and enhancing evidence quality through reproducible research. The alignment of federal data agency incentives with the private sector, alongside technological advancements, now supports feedback-driven data classification, leveraging machine learning for improved data discoverability and categorization. This article outlines the multiple classification needs of one statistical agency, the National Center for Science and Engineering Statistics, and proposes a machine learning approach for classifying data sets based on usage in research, aligning with legislative and policy frameworks to enhance data governance, interoperability, and utility for evidence-based decision-making.

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“…On the technological side, machine learning and natural language processing can be used to make those tools easier to use by agencies and the results of data collection easier to link and analyze by researchers. Craig Jones's (2020) article "Building on Aotearoa New Zealand's Integrated Data Infrastructure" provides a case study of the power of incentivizing rather than mandating the collection and linking of government data.…”

mentioning

confidence: 99%

Unlocking Government Data to Support and Evaluate Scientific Research: An Overview of Selected Papers from the Value of Science Conference

Kautz¹

2022

Harvard Data Science Review

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Building on Aotearoa New Zealand’s Integrated Data Infrastructure

Cited by 5 publications

References 3 publications

An Invisible Hand for Creating Public Value From Data

An Invisible Hand for Creating Public Value From Data

Searching for How Data Have Been Used: Intuitive Labels for Data Search and Discovery

Unlocking Government Data to Support and Evaluate Scientific Research: An Overview of Selected Papers from the Value of Science Conference

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