Federal Big Data Analytics in the Health Domain

Kuiler, Erik W.; McNeely, Connie L.

doi:10.1016/b978-0-12-812443-7.00010-7

Federal Data Science 2018

DOI: 10.1016/b978-0-12-812443-7.00010-7

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Federal Big Data Analytics in the Health Domain

Erik W. Kuiler

Connie L. McNeely

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2020

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Cited by 4 publications

(2 citation statements)

References 9 publications

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“…Boulding (1970), provides a useful introduction to this topic. See Kuiler and McNeely (2018), on the use of signals, data and information in the health domain.…”

mentioning

confidence: 99%

Bridging digital and knowledge divides: Concepts, frameworks and ethical concerns

Kuiler

2024

Policy & Internet

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Since time immemorial, the hegemonic imposition of cultural and political power asymmetries has resulted in the de jure and de facto exclusion of certain groups from the common weal. Withe the introduction of digital information and communication technologies (ICT), the rifts between the ‘haves’ and the ‘have‐nots’ have expanded at nearly exponential rates. To provide an instrument for analysing the complexities of bridging the digital and knowledge divides, a conceptual framework is presented that provides different perspectives on agency in the commonwealth and the infosphere, which, in turn, leads to a discussion of the operationalization of ethics and justice in human rights that directly affect the entelechy of wellbeing. This discussion provides a basis for exploring certain aspects of social‐cultural barriers to wellbeing, the commodification of human rights, digital imperialism and cultural hegemonies in the world polity, including the infosphere, that have a direct bearing on the wellbeing of all in the common weal. A summary and a call‐to‐action complete the study.

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“…Boulding (1970), provides a useful introduction to this topic. See Kuiler and McNeely (2018), on the use of signals, data and information in the health domain.…”

mentioning

confidence: 99%

Bridging digital and knowledge divides: Concepts, frameworks and ethical concerns

Kuiler

2024

Policy & Internet

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“…The achievement of interoperability, a key aspect of FAIR, relies on the use of common vocabularies, ontologies, and formats specified using metadata standards. These standardized structures allow for seamless integration of data from diverse sources, promoting cross-domain collaborations and knowledge integration [ 4 ]. Moreover, the machine-readability of formalized metadata enables automated processing and integration, further streamlining data analysis and interpretation.…”

mentioning

confidence: 99%

Keep It Simple: Using README Files to Advance Standardization in Chronobiology

Zieliński,

Hodge,

Millar

2023

Clocks & Sleep

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Standardization plays a crucial role in ensuring the reliability, reproducibility, and interoperability of research data in the biomedical sciences. Metadata standards are one foundation for the FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data management. They facilitate data discovery, understanding, and reuse. However, the adoption of metadata standards in biological research lags in practice. Barriers such as complexity, lack of incentives, technical challenges, resource constraints, and resistance to change hinder widespread adoption. In the field of chronobiology, standardization is essential but faces particular challenges due to the longitudinal nature of experimental data, diverse model organisms, and varied measurement techniques. To address these challenges, we propose an approach that emphasizes simplicity and practicality: the development of README templates tailored for particular data types and species. Through this opinion article, our intention is to initiate a dialogue and commence a community-driven standardization process by engaging potential contributors and collaborators.

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Social Determinants and COVID‐19 Disparities: Differential Pandemic Effects and Dynamics

McNeely¹,

Schintler²,

Stabile³

2020

World Med & Health Policy

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The COVID-19 pandemic has had disproportionately negative impacts on socially disadvantaged and underserved populations around the world. Inequality and the related social determinants that impact certain groups are directly related to the adverse health outcomes of vulnerable populations during the pandemic. People in disadvantaged communities are generally more prone to occupational exposure to the virus and tend to have limited access to health care and higher rates of comorbidities. Outcomes related to widespread school closures are also of particular concern for underserved communities. Additionally, these populations are more susceptible to the negative economic outcomes of the pandemic. There is an urgent need for research and policy solutions regarding the impact of the COVID-19, with particular attention to the needs of disadvantaged and vulnerable populations, a foundation for which is offered in this discussion.

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Federal Big Data Analytics in the Health Domain

Cited by 4 publications

References 9 publications

Bridging digital and knowledge divides: Concepts, frameworks and ethical concerns

Bridging digital and knowledge divides: Concepts, frameworks and ethical concerns

Keep It Simple: Using README Files to Advance Standardization in Chronobiology

Social Determinants and COVID‐19 Disparities: Differential Pandemic Effects and Dynamics

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