The application of big data and the development of nursing science: A discussion paper

Data is regarded a powerful raw material that can affect multidisciplinary study undertakings in addition to federal government as well as service performance. The goal of this discussion paper is to share the data analytics viewpoints as well as viewpoints of the writers connecting to the new opportunities and also challenges brought forth by the big data movement. The writers bring together varied viewpoints, originating from different geographical places with various core research study knowledge and also different associations and job experiences. This paper supplies a tool to integrate maximized equipment as well as extensive software right into its database to sustain big data difficulties.

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The Ethics of Big Data and Nursing Science

Nursing Science Quarterly ◽

10.1177/0894318417724474 ◽

2017 ◽

Vol 30 (4) ◽

pp. 300-302 ◽

Cited By ~ 5

Author(s):

Constance L. Milton

Keyword(s):

Big Data ◽

Informed Consent ◽

Nursing Science ◽

Ethical Implications

Big data is a scientific, social, and technological trend referring to the process and size of datasets available for analysis. Ethical implications arise as healthcare disciplines, including nursing, struggle over questions of informed consent, privacy, ownership of data, and its possible use in epistemology. The author offers straight-thinking possibilities for the use of big data in nursing science.

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Cognition and expansion of nursing science: A response to the discussion paper entitled “At the intersection of science and theory: How the Nurse Role Integration Model reconciles the conflict”

International Journal of Nursing Sciences ◽

10.1016/j.ijnss.2020.11.002 ◽

2020 ◽

Author(s):

Lei Lei ◽

Jinyu Huang ◽

Yu Luo

Keyword(s):

Discussion Paper ◽

Integration Model ◽

Nursing Science ◽

Role Integration ◽

Nurse Role

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Perspectives on Policy and the Value of Nursing Science in a Big Data Era

Nursing Science Quarterly ◽

10.1177/0894318417741122 ◽

2017 ◽

Vol 31 (1) ◽

pp. 78-81 ◽

Cited By ~ 3

Author(s):

Sheila M. Gephart ◽

Mary Davis ◽

Kimberly Shea

Keyword(s):

Big Data ◽

Data Science ◽

Epistemic Values ◽

Data Movement ◽

Nursing Science ◽

Body Of Knowledge ◽

Data Volume ◽

Domain Expertise

As data volume explodes, nurse scientists grapple with ways to adapt to the big data movement without jeopardizing its epistemic values and theoretical focus that celebrate while acknowledging the authority and unity of its body of knowledge. In this article, the authors describe big data and emphasize ways that nursing science brings value to its study. Collective nursing voices that call for more nursing engagement in the big data era are answered with ways to adapt and integrate theoretical and domain expertise from nursing into data science.

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Mehr Sicherheit mit zentraler Bankenaufsicht

Die Wirtschaft im Wandel ◽

10.1007/978-3-658-31735-5_9 ◽

2021 ◽

pp. 53-57

Author(s):

David Gmür

Keyword(s):

Monetary Policy ◽

Big Data ◽

Risk Taking ◽

Banking Supervision ◽

Discussion Paper ◽

Cepr Discussion Paper

ZusammenfassungDie Wirtschaft braucht Kredit, und die Gesellschaft mehr Sicherheit. Die Banken müssen in der Kreditvergabe auf Ertrag und Risiko gleichzeitig achten. Damit die Regulierung effektiven Schutz bieten kann, muss die Bankenaufsicht die Einhaltung der Vorschriften überwachen und frühzeitig das Entstehen übermässiger Risiken aufdecken. In der Bankenunion kann eine zentrale Aufsicht eher für gleich lange Spiesse im europaweiten Wettbewerb der Banken sorgen, kann unabhängiger als nationale Aufsichtsbehörden agieren, und dank besserer Ressourcen auch komplexe Grossbanken wirksam beaufsichtigen. So wird die Kreditvergabe sicherer, indem die Banken angehalten sind, faule und riskante Kredite zügig abzubauen und mehr Kredit auf die produktiveren Unternehmen mit besseren Aussichten lenken.Christian Keuschnigg und Michael Kogler, Herausgeber.Altavilla, Carlo, Miguel Boucinha, José-Luis Peydró, und Frank Smets (2020), Banking Supervision, Monetary Policy and Risk-Taking: Big Data Evidence from 15 Credit Registers, CEPR Discussion Paper Nr. 14288.

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