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Title:Data sharing concepts : a viable system model diagnosis
Authors:ID Perko, Igor (Author)
Files:.pdf Perko-2023-Data_sharing_concepts__a_viable_sys.pdf (663,49 KB)
MD5: 856FEA75997B53D567D81A18B3A0348F
 
URL https://doi.org/10.1108/K-04-2022-0575
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:EPF - Faculty of Business and Economics
Abstract:Purpose Artificial intelligence (AI) reasoning is fuelled by high-quality, detailed behavioural data. These can usually be obtained by the biometrical sensors embedded in smart devices. The currently used data collecting approach, where data ownership and property rights are taken by the data scientists, designers of a device or a related application, delivers multiple ethical, sociological and governance concerns. In this paper, the author is opening a systemic examination of a data sharing concept in which data producers execute their data property rights. Design/methodology/approach Since data sharing concept delivers a substantially different alternative, it needs to be thoroughly examined from multiple perspectives, among them: the ethical, social and feasibility. At this stage, theoretical examination modes in the form of literature analysis and mental model development are being performed. Findings Data sharing concepts, framework, mechanisms and swift viability are examined. The author determined that data sharing could lead to virtuous data science by augmenting data producers' capacity to govern their data and regulators' capacity to interact in the process. Truly interdisciplinary research is proposed to follow up on this research. Research limitations/implications Since the research proposal is theoretical, the proposal may not provide direct applicative value but is largely focussed on fuelling the research directions. Practical implications For the researchers, data sharing concepts will provide an alternative approach and help resolve multiple ethical considerations related to the internet of things (IoT) data collecting approach. For the practitioners in data science, it will provide numerous new challenges, such as distributed data storing, distributed data analysis and intelligent data sharing protocols. Social implications Data sharing may post significant implications in research and development. Since ethical, legislative moral and trust-related issues are managed in the negotiation process, data can be shared freely, which in a practical sense expands the data pool for virtuous research in social sciences. Originality/value The paper opens new research directions of data sharing concepts and space for a new field of research.
Keywords:hybrid reality, data sharing, systems thinking, cybernetics, artificial intelligence
Publication status:Published
Publication version:Version of Record
Submitted for review:18.04.2022
Article acceptance date:22.08.2022
Publication date:29.08.2023
Publisher:MCB university press
Year of publishing:2023
Number of pages:Str. 2976-2991
Numbering:Letn. 52, Št. 9
PID:20.500.12556/DKUM-87061 New window
UDC:004.8
ISSN on article:0368-492X
COBISS.SI-ID:129746947 New window
DOI:10.1108/K-04-2022-0575 New window
Publication date in DKUM:14.02.2024
Views:595
Downloads:28
Metadata:XML DC-XML DC-RDF
Categories:Misc.
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Record is a part of a journal

Title:Kybernetes
Shortened title:Kybernetes
Publisher:MCB university press
ISSN:0368-492X
COBISS.SI-ID:28709889 New window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:29.08.2022

Secondary language

Language:Slovenian
Keywords:hibridna resničnost, izmenjava podatkov, sistemsko razmišljanje, kibernetika, umetna inteligenca


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