دورية أكاديمية

A perspective on data sharing in digital food safety systems.

التفاصيل البيبلوغرافية
العنوان: A perspective on data sharing in digital food safety systems.
المؤلفون: Qian C; Department of Food Science, Cornell University, Ithaca, NY, USA., Liu Y; School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA., Barnett-Neefs C; Department of Population Medicine and Diagnostic Sciences, Cornell University, Ithaca, NY, USA., Salgia S; School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA., Serbetci O; School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA., Adalja A; SC Johnson College of Business, Cornell University, Ithaca, NY, USA., Acharya J; School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA., Zhao Q; School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA., Ivanek R; Department of Population Medicine and Diagnostic Sciences, Cornell University, Ithaca, NY, USA., Wiedmann M; Department of Food Science, Cornell University, Ithaca, NY, USA.
المصدر: Critical reviews in food science and nutrition [Crit Rev Food Sci Nutr] 2023 Nov; Vol. 63 (33), pp. 12513-12529. Date of Electronic Publication: 2022 Jul 26.
نوع المنشور: Review; Journal Article
اللغة: English
بيانات الدورية: Publisher: Taylor & Francis Group Country of Publication: United States NLM ID: 8914818 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-7852 (Electronic) Linking ISSN: 10408398 NLM ISO Abbreviation: Crit Rev Food Sci Nutr Subsets: MEDLINE
أسماء مطبوعة: Publication: Philadelphia, PA : Taylor & Francis Group
Original Publication: Boca Raton, Fla. : CRC Press, c1980-
مواضيع طبية MeSH: Hazard Analysis and Critical Control Points* , Confidentiality*, Humans ; Privacy ; Food Safety ; Information Dissemination
مستخلص: In this age of data, digital tools are widely promoted as having tremendous potential for enhancing food safety. However, the potential of these digital tools depends on the availability and quality of data, and a number of obstacles need to be overcome to achieve the goal of digitally enabled "smarter food safety" approaches. One key obstacle is that participants in the food system and in food safety often lack the willingness to share data, due to fears of data abuse, bad publicity, liability, and the need to keep certain data (e.g., human illness data) confidential. As these multifaceted concerns lead to tension between data utility and privacy, the solutions to these challenges need to be multifaceted. This review outlines the data needs in digital food safety systems, exemplified in different data categories and model types, and key concerns associated with sharing of food safety data, including confidentiality and privacy of shared data. To address the data privacy issue a combination of innovative strategies to protect privacy as well as legal protection against data abuse need to be pursued. Existing solutions for maximizing data utility, while not compromising data privacy, are discussed, most notably differential privacy and federated learning.
فهرسة مساهمة: Keywords: Food safety; data privacy; data utility; decision support tools; predictive models
تواريخ الأحداث: Date Created: 20220726 Date Completed: 20231222 Latest Revision: 20231222
رمز التحديث: 20231222
DOI: 10.1080/10408398.2022.2103086
PMID: 35880485
قاعدة البيانات: MEDLINE
الوصف
تدمد:1549-7852
DOI:10.1080/10408398.2022.2103086