DAI-DSS Research Specification – D3.1
Herwig Zeiner, Lucas Paletta, Michael Schneeberger, Gustavo Vieira, Sylwia Olbrych, Alexander Nasuta, Johanna Werz, Noushin Gheibi, Stefan Böschen, Magdalena Dienstl, Marlene Mayer, Christian Muck
This report focuses on the deliverable “D3.1 – DAI-DSS Research Specification”, part of the Horizon Europe project FAIRWork. The deliverable aims to describe the specific research factors in selected use cases of industrial partners FLEX and CRF. It presents a research strategies and factors catalogue that serves as a framework for conducting research within the Democratized AI-based Decision Support System (DAI-DSS). DAI-DSS research specifications are closely related to deliverables “D2.1 Specification of FAIRWork Use Case and DAI-DSS Prototype Report” and “D4.1 DAI-DSS Architecture and Initial Documentation and Test Report”.
The first part of the report provides an overview of the relevant literature related to the research intended within the frame of this project. It covers the most significant research domains, such as the democratization of decision-making and digital shadows and twins for human experts. Additionally, it explores technical approaches like Artificial Intelligence (AI) and Multi-Agent System (MAS) crucial for improving Decision Support Systems (DSS). This section also presents the state-of-the-art crucial aspects of today's technology, particularly reliability and trustworthiness in AI. The output of this literature review leads to research questions in multiple domains addressed within the FAIRWork project.
The second part of the report focuses on the research methodologies and strategies employed to investigate the technical aspects of decision-making processes, human aspects, and digital human factors measurements. It presents research approaches for successfully implementing AI and MAS-based technologies into DSS. Methods such as data-driven modelling, prototyping, and testing are proposed within the AI and MAS domains. Additionally, the report outlines the use of sensors to capture critical information about humans' mental, affective, and motivational states, including implementation details of the Intelligent Sensor Box (ISB). Furthermore, a novel framework using Personas as Human Digital Twins for Decision Making in the context of Industry 5.0 is described.
The final part of the report presents the key research factors identified in the industrial use cases and potential AI services to address them. These research factors are categorized into two main perspectives: the human perspective and the technical perspective. The human perspective factors are derived from the research plan and are observed in given use cases. On the technical side, the requirements for modelling and testing new concepts using AI and MAS technologies primarily focus on data availability (process-relevant and expert knowledge) and the DSS architecture necessary to enable information flow and decision models related to the use cases.
The report also provides a strategy for communication and dissemination in the context of the research methodology of the FAIRWork project. The objective is to continuously disseminate project achievements, raise awareness about the project, and gather feedback to improve the created research artefacts.
The first part of the report provides an overview of the relevant literature related to the research intended within the frame of this project. It covers the most significant research domains, such as the democratization of decision-making and digital shadows and twins for human experts. Additionally, it explores technical approaches like Artificial Intelligence (AI) and Multi-Agent System (MAS) crucial for improving Decision Support Systems (DSS). This section also presents the state-of-the-art crucial aspects of today's technology, particularly reliability and trustworthiness in AI. The output of this literature review leads to research questions in multiple domains addressed within the FAIRWork project.
The second part of the report focuses on the research methodologies and strategies employed to investigate the technical aspects of decision-making processes, human aspects, and digital human factors measurements. It presents research approaches for successfully implementing AI and MAS-based technologies into DSS. Methods such as data-driven modelling, prototyping, and testing are proposed within the AI and MAS domains. Additionally, the report outlines the use of sensors to capture critical information about humans' mental, affective, and motivational states, including implementation details of the Intelligent Sensor Box (ISB). Furthermore, a novel framework using Personas as Human Digital Twins for Decision Making in the context of Industry 5.0 is described.
The final part of the report presents the key research factors identified in the industrial use cases and potential AI services to address them. These research factors are categorized into two main perspectives: the human perspective and the technical perspective. The human perspective factors are derived from the research plan and are observed in given use cases. On the technical side, the requirements for modelling and testing new concepts using AI and MAS technologies primarily focus on data availability (process-relevant and expert knowledge) and the DSS architecture necessary to enable information flow and decision models related to the use cases.
The report also provides a strategy for communication and dissemination in the context of the research methodology of the FAIRWork project. The objective is to continuously disseminate project achievements, raise awareness about the project, and gather feedback to improve the created research artefacts.
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@techreport{fairwork_d3.1,
title = {DAI-DSS Research Specification - D3.1},
author = {Herwig Zeiner, Lucas Paletta, Michael Schneeberger, Gustavo Vieira, Sylwia Olbrych, Alexander Nasuta, Johanna Werz, Noushin Gheibi, Stefan Böschen, Magdalena Dienstl, Marlene Mayer, Christian Muck},
editor = {Sylwia Olbrych},
url = {https://fairwork-project.eu/deliverables/D3.1_DAI-DSS%20Research%20Specification-preliminary.pdf},
year = {2023},
date = {2023-06-20},
abstract = {This report focuses on the deliverable “D3.1 – DAI-DSS Research Specification”, part of the Horizon Europe project FAIRWork. The deliverable aims to describe the specific research factors in selected use cases of industrial partners FLEX and CRF. It presents a research strategies and factors catalogue that serves as a framework for conducting research within the Democratized AI-based Decision Support System (DAI-DSS). DAI-DSS research specifications are closely related to deliverables “D2.1 Specification of FAIRWork Use Case and DAI-DSS Prototype Report” and “D4.1 DAI-DSS Architecture and Initial Documentation and Test Report”.
The first part of the report provides an overview of the relevant literature related to the research intended within the frame of this project. It covers the most significant research domains, such as the democratization of decision-making and digital shadows and twins for human experts. Additionally, it explores technical approaches like Artificial Intelligence (AI) and Multi-Agent System (MAS) crucial for improving Decision Support Systems (DSS). This section also presents the state-of-the-art crucial aspects of today's technology, particularly reliability and trustworthiness in AI. The output of this literature review leads to research questions in multiple domains addressed within the FAIRWork project.
The second part of the report focuses on the research methodologies and strategies employed to investigate the technical aspects of decision-making processes, human aspects, and digital human factors measurements. It presents research approaches for successfully implementing AI and MAS-based technologies into DSS. Methods such as data-driven modelling, prototyping, and testing are proposed within the AI and MAS domains. Additionally, the report outlines the use of sensors to capture critical information about humans' mental, affective, and motivational states, including implementation details of the Intelligent Sensor Box (ISB). Furthermore, a novel framework using Personas as Human Digital Twins for Decision Making in the context of Industry 5.0 is described.
The final part of the report presents the key research factors identified in the industrial use cases and potential AI services to address them. These research factors are categorized into two main perspectives: the human perspective and the technical perspective. The human perspective factors are derived from the research plan and are observed in given use cases. On the technical side, the requirements for modelling and testing new concepts using AI and MAS technologies primarily focus on data availability (process-relevant and expert knowledge) and the DSS architecture necessary to enable information flow and decision models related to the use cases.
The report also provides a strategy for communication and dissemination in the context of the research methodology of the FAIRWork project. The objective is to continuously disseminate project achievements, raise awareness about the project, and gather feedback to improve the created research artefacts.},
howpublished = {https://fairwork-project.eu/deliverables/D3.1_DAI-DSS%20Research%20Specification-preliminary.pdf},
keywords = {deliverable},
pubstate = {published},
tppubtype = {techreport}
}