F. Abou Eddahab-Burke
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Digital community platforms have transformed civic participation, enhancing social belonging and shared responsibility. Yet, they intensify the digital divide between people. This can be a risk to their fundamental human value of dignity. This paper explores designing for dignity within digital community platforms through a qualitative study conducted in South Holland, The Netherlands. Twenty citizens participated in semi-structured interviews to investigate their understanding, experiences, frustrations and expectations of dignity in digital interactions. The study confirmed dignity’s multifaceted nature (14 distinct definitions), varied expectations of respectful treatment, and common challenges in using government digital services. Only 30% of participants felt these platforms respected their dignity, the rest expressed negative experiences such as feeling helpless, stupid, frustrated, anxious, etc. Participants emphasized needs such as language support, clarity, and navigation assistance, as well as design requirements. The findings will be validated in participatory design sessions of co-creating a dignified digital community platform.
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Digital community platforms have transformed civic participation, enhancing social belonging and shared responsibility. Yet, they intensify the digital divide between people. This can be a risk to their fundamental human value of dignity. This paper explores designing for dignity within digital community platforms through a qualitative study conducted in South Holland, The Netherlands. Twenty citizens participated in semi-structured interviews to investigate their understanding, experiences, frustrations and expectations of dignity in digital interactions. The study confirmed dignity’s multifaceted nature (14 distinct definitions), varied expectations of respectful treatment, and common challenges in using government digital services. Only 30% of participants felt these platforms respected their dignity, the rest expressed negative experiences such as feeling helpless, stupid, frustrated, anxious, etc. Participants emphasized needs such as language support, clarity, and navigation assistance, as well as design requirements. The findings will be validated in participatory design sessions of co-creating a dignified digital community platform.
Dignified Engineering Education
An Introduction
Human dignity, though challenging to define precisely, holds immense significance in our lives. It is the foundation of human rights and considered by researchers to be the most essential and influential existing value referring to the state of being worthy of honor or respect, as well as the moral right of not to be humiliated. Feeling dignified contributes to human well-being. In the field of education, some scholars argue that human dignity should not only be a guiding principle but also the ultimate goal of education and life. An education that integrates dignity offers more than just knowledge acquisition. It provides a way for society to support individuals explore their self-identity, internalize fundamental values, develop personal responsibility, and gain a deeper understanding of their character and identity. However, recent efforts, particularly in traditionally male-dominated and non-disabled-centric engineering education, have focused primarily on promoting diversity, equity, and inclusion (DEI). This paper defines dignity within the context of engineering education and introduces a novel vision: 'Dignifying Engineering Education' (DEE), which extends beyond DEI principles. Emerging from combining insights from literature on engineering education and human dignity, DEE emphasizes providing students with choice, respect, usefulness, inclusion, safety, equity and diversity (CRUISED). The implementation of DEE in universities allows creating an educational environment that not only equips students with up-to-date technical skills and tools but also promotes their well-being and personal growth in a respectful, inclusive, safe, fair and diverse environment. To do so, joint efforts of researchers and faculty are needed to set an action plan that is customized to the special needs of their organization and students' population. The paper concludes with recommendations for engineering universities seeking to transition to DEE. Follow-up research will outline the 'DEE framework,' detailing actionable steps in six interconnected categories: facilities, course content, teaching/learning material, assessment, interactions and faculty.
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Human dignity, though challenging to define precisely, holds immense significance in our lives. It is the foundation of human rights and considered by researchers to be the most essential and influential existing value referring to the state of being worthy of honor or respect, as well as the moral right of not to be humiliated. Feeling dignified contributes to human well-being. In the field of education, some scholars argue that human dignity should not only be a guiding principle but also the ultimate goal of education and life. An education that integrates dignity offers more than just knowledge acquisition. It provides a way for society to support individuals explore their self-identity, internalize fundamental values, develop personal responsibility, and gain a deeper understanding of their character and identity. However, recent efforts, particularly in traditionally male-dominated and non-disabled-centric engineering education, have focused primarily on promoting diversity, equity, and inclusion (DEI). This paper defines dignity within the context of engineering education and introduces a novel vision: 'Dignifying Engineering Education' (DEE), which extends beyond DEI principles. Emerging from combining insights from literature on engineering education and human dignity, DEE emphasizes providing students with choice, respect, usefulness, inclusion, safety, equity and diversity (CRUISED). The implementation of DEE in universities allows creating an educational environment that not only equips students with up-to-date technical skills and tools but also promotes their well-being and personal growth in a respectful, inclusive, safe, fair and diverse environment. To do so, joint efforts of researchers and faculty are needed to set an action plan that is customized to the special needs of their organization and students' population. The paper concludes with recommendations for engineering universities seeking to transition to DEE. Follow-up research will outline the 'DEE framework,' detailing actionable steps in six interconnected categories: facilities, course content, teaching/learning material, assessment, interactions and faculty.
The advent of complex socio-technical systems in modern society calls for teaching value-based participatory design in engineering curricula. Yet, no scientific literature supports teachers in this effort. This paper introduces a teaching approach called “value-based participatory design of complex socio-technical systems” and reports on its implementation. It emphasizes the importance of actively involving stakeholders and tapping into their values from the very start of the design process. Following this approach, students learn to (1) design with stakeholders, (2) identify key values and conflicts to create a value-based mission statement, (3) navigate uncertainties, (4) adopt an iterative design process, and (5) recognize that only stakeholders can define what works best. Results of an academic course based on this approach confirm its value and importance for engineering curricula.
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The advent of complex socio-technical systems in modern society calls for teaching value-based participatory design in engineering curricula. Yet, no scientific literature supports teachers in this effort. This paper introduces a teaching approach called “value-based participatory design of complex socio-technical systems” and reports on its implementation. It emphasizes the importance of actively involving stakeholders and tapping into their values from the very start of the design process. Following this approach, students learn to (1) design with stakeholders, (2) identify key values and conflicts to create a value-based mission statement, (3) navigate uncertainties, (4) adopt an iterative design process, and (5) recognize that only stakeholders can define what works best. Results of an academic course based on this approach confirm its value and importance for engineering curricula.
This paper addresses the challenge of handling large and diverse data streams from connected products during middle-of-life use. Current data analytics tools struggle with such data, necessitating the development of a crucial function in next-generation data analytics tools that semantically merges and analyzes these streams collectively. The proposed function, recommendation for semantic merging of middle-of-life, acquires, pre-processes, and merges data from various streams, providing designers with enhanced product information. Tested on simulated data streams of a washing machine enhancement case, the function offers more comprehensive product insights than individual sensor analysis. Implementation of such a function could improve fidelity in reflecting product conditions, reduce sensor analysis time and effort, and deliver an actionable plan for product improvement. Being design-focused, this article addresses the functional validity and the proof of concept of the recommendation function. Full computational analysis is out of this paper’s scope and will be addressed in future research.
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This paper addresses the challenge of handling large and diverse data streams from connected products during middle-of-life use. Current data analytics tools struggle with such data, necessitating the development of a crucial function in next-generation data analytics tools that semantically merges and analyzes these streams collectively. The proposed function, recommendation for semantic merging of middle-of-life, acquires, pre-processes, and merges data from various streams, providing designers with enhanced product information. Tested on simulated data streams of a washing machine enhancement case, the function offers more comprehensive product insights than individual sensor analysis. Implementation of such a function could improve fidelity in reflecting product conditions, reduce sensor analysis time and effort, and deliver an actionable plan for product improvement. Being design-focused, this article addresses the functional validity and the proof of concept of the recommendation function. Full computational analysis is out of this paper’s scope and will be addressed in future research.
This second Part of the paper (i) develops a detailed procedural model for handling complicated research problematics, (ii) transfers the procedural framework into a scenario of processing steps, (iii) demonstrates the deployment of the procedural scenario in a sample case, and (iv) addresses some important issues of research model development for supradisciplinary research. First, the framework called Holistic Systematic Combinatorial Scoping (HSCS) is introduced that comprises 21 subsequent activity steps. To illustrate the practical application of the HSCS framework, a demonstrative case study of preventing frequently occurring accidents at an uncontrolled intersection is presented. This case-study explains how the HSCS framework can facilitate (i) semantic capturing and rendering of complicated research problematics, (ii) scoping the overall research problematics and constructing definitive research problematics, and (iii) deriving a manageable research model of definitive research problematics. Further research intends to test the methodology by transdisciplinary research collectives and other CPSs related problematics.
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This second Part of the paper (i) develops a detailed procedural model for handling complicated research problematics, (ii) transfers the procedural framework into a scenario of processing steps, (iii) demonstrates the deployment of the procedural scenario in a sample case, and (iv) addresses some important issues of research model development for supradisciplinary research. First, the framework called Holistic Systematic Combinatorial Scoping (HSCS) is introduced that comprises 21 subsequent activity steps. To illustrate the practical application of the HSCS framework, a demonstrative case study of preventing frequently occurring accidents at an uncontrolled intersection is presented. This case-study explains how the HSCS framework can facilitate (i) semantic capturing and rendering of complicated research problematics, (ii) scoping the overall research problematics and constructing definitive research problematics, and (iii) deriving a manageable research model of definitive research problematics. Further research intends to test the methodology by transdisciplinary research collectives and other CPSs related problematics.
There are many large-scale, transdisciplinary research problematics associated with next-generation cyber-physical systems, which are difficult to capture, analyze, and transfer into sharable research models. This two-part paper is intended to contribute to a better understanding and to provide a systematic approach to describing, scoping, and specifying manageable contents for transdisciplinary research models. Part 1 of the paper analyzes the essence and the interplays of the most important current trends, and creates a robust theoretical and methodological foundation for capturing and scoping research problematics associated with the evolving paradigm of cyber-physical systems. The elaboration and deployment of the proposed approach are discussed in detail in Part 2. Besides the overall procedural framework of the proposed holistic systematic combinational breakdown, all steps are explained and exemplified in an illustrative real-life example. The discussion in both Parts concludes with a number of propositions and further research opportunities concerning the theoretical and methodological foundations.
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There are many large-scale, transdisciplinary research problematics associated with next-generation cyber-physical systems, which are difficult to capture, analyze, and transfer into sharable research models. This two-part paper is intended to contribute to a better understanding and to provide a systematic approach to describing, scoping, and specifying manageable contents for transdisciplinary research models. Part 1 of the paper analyzes the essence and the interplays of the most important current trends, and creates a robust theoretical and methodological foundation for capturing and scoping research problematics associated with the evolving paradigm of cyber-physical systems. The elaboration and deployment of the proposed approach are discussed in detail in Part 2. Besides the overall procedural framework of the proposed holistic systematic combinational breakdown, all steps are explained and exemplified in an illustrative real-life example. The discussion in both Parts concludes with a number of propositions and further research opportunities concerning the theoretical and methodological foundations.
Reliable development of next-generation data analytics toolboxes (N-GDATs) requires robust underpinning theories, which cannot necessarily be inductively generated. Based on the axiomatic theories fusion (ATF) methodology we deductively developed a comprehensive theory supporting the development of a N-GDAT for white goods design based on middle-of-life data. Accordingly, theories about designer’s needs, advanced technologies, data analytics, creative problem-solving, decision-making, and interoperability were fused following the ATF steps: (i) selection of component theories, (ii) axiomatic discretization of foundational theories, (iii) establishing relationships among axioms and postulates, (iv) transcription of system of axiomatic propositions into a textual format, and (v) validation of explanatory theory. The obtained new theory provides a robust basis for the targeted knowledge platform. It provides (i) decision- making, (ii) algorithmic concepts, (iii) learning, (iv) data management, (v) interfacing, (vi) reasoning, (vii) data types and characteristics, (viii) design issues, (ix) analytics techniques and methods, and (x) outputs requirements to develop N- GDATs.
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Reliable development of next-generation data analytics toolboxes (N-GDATs) requires robust underpinning theories, which cannot necessarily be inductively generated. Based on the axiomatic theories fusion (ATF) methodology we deductively developed a comprehensive theory supporting the development of a N-GDAT for white goods design based on middle-of-life data. Accordingly, theories about designer’s needs, advanced technologies, data analytics, creative problem-solving, decision-making, and interoperability were fused following the ATF steps: (i) selection of component theories, (ii) axiomatic discretization of foundational theories, (iii) establishing relationships among axioms and postulates, (iv) transcription of system of axiomatic propositions into a textual format, and (v) validation of explanatory theory. The obtained new theory provides a robust basis for the targeted knowledge platform. It provides (i) decision- making, (ii) algorithmic concepts, (iii) learning, (iv) data management, (v) interfacing, (vi) reasoning, (vii) data types and characteristics, (viii) design issues, (ix) analytics techniques and methods, and (x) outputs requirements to develop N- GDATs.
Conference paper
(2021)
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F. Abou Eddahab-Burke, Marjolein Derks, Peter Groot Koerkamp
Agricultural production worldwide is facing many challenges to be able to achieve the UN Sustainability Development Goals and international agreements with respect to environment, labour, and society. Our investigation revealed that further optimization of current farming practices with precision agriculture (PA) and precision livestock farming (PLF) technologies is insufficient to meet these challenges. Therefore, a paradigm shift is required for building the next- generation agricultural production systems that are (i) sustainable, (ii) circular, and (iii) regenerative. The Synergia research program, where this study takes place, addresses this transition through our new concept of ‘Technology 4- Ecology-based Agriculture’ (T4E-Agriculture) in the Netherlands. This concept implies that future agricultural systems have to (i) rely on natural processes as driver for agricultural ecosystems and primary productivity; (ii) be able to sense traits by focusing on following biological production processes instead of momentary states, and on biological and ecological traits in the systems instead of production traits and problem indicators only; (iii) build models based on the understanding of the underlying biological & ecological processes; and (iv) include control and management functions that focus on prevention of problems, and make smart use of biological diversity and ecological complexity. With this novel approach we are not opposing high tech to nature-based production, in the opposite, we are exploring how current and future farming technologies can enable and support truly ecology-based farming systems. This approach will be developed and validated within the Synergia research program in building next-generation (i) horticulture, (ii) dairy and (iii) arable farming systems.
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Agricultural production worldwide is facing many challenges to be able to achieve the UN Sustainability Development Goals and international agreements with respect to environment, labour, and society. Our investigation revealed that further optimization of current farming practices with precision agriculture (PA) and precision livestock farming (PLF) technologies is insufficient to meet these challenges. Therefore, a paradigm shift is required for building the next- generation agricultural production systems that are (i) sustainable, (ii) circular, and (iii) regenerative. The Synergia research program, where this study takes place, addresses this transition through our new concept of ‘Technology 4- Ecology-based Agriculture’ (T4E-Agriculture) in the Netherlands. This concept implies that future agricultural systems have to (i) rely on natural processes as driver for agricultural ecosystems and primary productivity; (ii) be able to sense traits by focusing on following biological production processes instead of momentary states, and on biological and ecological traits in the systems instead of production traits and problem indicators only; (iii) build models based on the understanding of the underlying biological & ecological processes; and (iv) include control and management functions that focus on prevention of problems, and make smart use of biological diversity and ecological complexity. With this novel approach we are not opposing high tech to nature-based production, in the opposite, we are exploring how current and future farming technologies can enable and support truly ecology-based farming systems. This approach will be developed and validated within the Synergia research program in building next-generation (i) horticulture, (ii) dairy and (iii) arable farming systems.
Data analytics needs dedicated tools, which are getting complex. In this paper we summarize the results of our literature research done with special attention to existing and potential future tools. The attention is paid mainly to processing big data, rather than to effective semantic processing of middle-of-life data (MoLD). The issue of handling of big MoLD of specific characteristics efficiently has not yet been addressed by the commercialized tools and methods. Another major limitation of the current tools is that they are typically not capable to adapt themselves to designers‟ needs and to support knowledge/experience reusability in multiple design tasks. MoLD require quasi-real life handling due to their nature and direct feedback relationships to the operation process and the environment of products. Nowadays products are equipped with smart capabilities. This offers new opportunities for exploiting MoLD. The knowledge aggregated in this study will be used in the development of a toolbox, which (i) integrates various tools under a unified interface, (ii) implements various smart and semantics orientated functions, and (iii) facilitates data transformations in contexts by the practicing designers themselves.
...
Data analytics needs dedicated tools, which are getting complex. In this paper we summarize the results of our literature research done with special attention to existing and potential future tools. The attention is paid mainly to processing big data, rather than to effective semantic processing of middle-of-life data (MoLD). The issue of handling of big MoLD of specific characteristics efficiently has not yet been addressed by the commercialized tools and methods. Another major limitation of the current tools is that they are typically not capable to adapt themselves to designers‟ needs and to support knowledge/experience reusability in multiple design tasks. MoLD require quasi-real life handling due to their nature and direct feedback relationships to the operation process and the environment of products. Nowadays products are equipped with smart capabilities. This offers new opportunities for exploiting MoLD. The knowledge aggregated in this study will be used in the development of a toolbox, which (i) integrates various tools under a unified interface, (ii) implements various smart and semantics orientated functions, and (iii) facilitates data transformations in contexts by the practicing designers themselves.
Though many enhancements are still possible and needed, data analytics software packages invaded all segments of industrial businesses. Since product designers are not specialized data analysts, an op- portunity of enhancement is to provide advice by smart data analytics toolboxes (SDATBs). For in- stance, SDATBs can provide guidance at selecting commercially available data analytics tools (DATs) for a specific design-related task. The reported work focused on the implementation of a recommendation functionality for selecting DATs for different appli- cations. The paper presents the proposed solution, which (i) interprets the designer’s input, (ii) pro- poses a description of the problem identified by the designer, (iii) reasons with the warehoused DATs and (iv) recommends DATs matching the designer’s task at hand. Besides presenting the needed func- tionality, the rules used for selecting DATs are dis- cussed and the computational algorithms are speci- fied. A computational feasibility testing of the tool recommendation functionality has been done considering the application case of enhancing a wash- ing machine by white goods designers. The testing process showed that the realized functionality works correctly from a computational point of view and that it achieves sufficiently good tool matching. It compensates for the knowledge lack of product de- signers concerning selection of data analytics tools and reduces time and effort for tools selection. The outcomes of this study will be used in a follow up research to develop a SDATB providing even more comprehensive support for product designers.
...
Though many enhancements are still possible and needed, data analytics software packages invaded all segments of industrial businesses. Since product designers are not specialized data analysts, an op- portunity of enhancement is to provide advice by smart data analytics toolboxes (SDATBs). For in- stance, SDATBs can provide guidance at selecting commercially available data analytics tools (DATs) for a specific design-related task. The reported work focused on the implementation of a recommendation functionality for selecting DATs for different appli- cations. The paper presents the proposed solution, which (i) interprets the designer’s input, (ii) pro- poses a description of the problem identified by the designer, (iii) reasons with the warehoused DATs and (iv) recommends DATs matching the designer’s task at hand. Besides presenting the needed func- tionality, the rules used for selecting DATs are dis- cussed and the computational algorithms are speci- fied. A computational feasibility testing of the tool recommendation functionality has been done considering the application case of enhancing a wash- ing machine by white goods designers. The testing process showed that the realized functionality works correctly from a computational point of view and that it achieves sufficiently good tool matching. It compensates for the knowledge lack of product de- signers concerning selection of data analytics tools and reduces time and effort for tools selection. The outcomes of this study will be used in a follow up research to develop a SDATB providing even more comprehensive support for product designers.
Continuous enhancements of connected products make them able to generate and communicate a huge amounts of middle-of-life data streams to their producers. This affordance also creates a challenge for current data analytics tools unable to keep up with the heterogeneous nature and characteristics of these type of data. Accordingly, a function able to combine data from multiple data streams and analyze them as one source of information is definitely needed in a next-generation data analytics toolbox to support product enhancements by designers. As a result of a recent Ph.D. project, this paper presents the conceptualization and the implementation of a novel function of merging middle-of-life data streams. The implemented computational mechanism (i) acquires middle-of-life data streams, (ii) pre-processes them individually, (iii) merges information from the concerned streams, (iv) derives recommendation based on the merged information, and (v) send a recommendation as a message to the designer. The performance of the computational implementation was tested in an application case of data steaming and management to white goods designers for enhancing a connected washing machine. From a computational point of view, the testing proved that the set of proprietary algorithms designed for the realization of computational merging, together with the existing ones taken from the literature, were able to efficiently perform the subtasks. The advantages of merges were: (i) it provides more information than the one obtained by processing sensors' data individually, (ii) it reflects the condition of the product with a higher fidelity, (iii) it communicates information about the product while it is in use by the customer, (iv) it reduces the sensors analyses time and effort, and (v) it provides recommendation as an action plan concerning the product at hand. The outcomes of this study will be used in a follow up research to develop a comprehensive smart data analytics toolbox to support product designers in product innovation.
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Continuous enhancements of connected products make them able to generate and communicate a huge amounts of middle-of-life data streams to their producers. This affordance also creates a challenge for current data analytics tools unable to keep up with the heterogeneous nature and characteristics of these type of data. Accordingly, a function able to combine data from multiple data streams and analyze them as one source of information is definitely needed in a next-generation data analytics toolbox to support product enhancements by designers. As a result of a recent Ph.D. project, this paper presents the conceptualization and the implementation of a novel function of merging middle-of-life data streams. The implemented computational mechanism (i) acquires middle-of-life data streams, (ii) pre-processes them individually, (iii) merges information from the concerned streams, (iv) derives recommendation based on the merged information, and (v) send a recommendation as a message to the designer. The performance of the computational implementation was tested in an application case of data steaming and management to white goods designers for enhancing a connected washing machine. From a computational point of view, the testing proved that the set of proprietary algorithms designed for the realization of computational merging, together with the existing ones taken from the literature, were able to efficiently perform the subtasks. The advantages of merges were: (i) it provides more information than the one obtained by processing sensors' data individually, (ii) it reflects the condition of the product with a higher fidelity, (iii) it communicates information about the product while it is in use by the customer, (iv) it reduces the sensors analyses time and effort, and (v) it provides recommendation as an action plan concerning the product at hand. The outcomes of this study will be used in a follow up research to develop a comprehensive smart data analytics toolbox to support product designers in product innovation.
Companies are getting increasingly interested in learning how different customers use their products. Collecting data about the use of products provides useful insights and facilitates design enhancements. Effective data analytics needs dedicated tools. In this paper, we summarize the results of our literature research done with special attention to existing tools. We observed that everything is changing rapidly and getting more complex in terms of data and processing methods and tools. While remarkable attention has been paid to processing big data, much less is being devoted to effective semantic progressing of middle-of-life (MoL) data. One of our findings is that commercialized data analytics tools have not addressed extraction, aggregation, and handling genuine MoL data adequately. Another one is that the currently available tools are in the lack of the capability to adapt themselves to designers needs and to produce results that could be reused in multiple design tasks. Nowadays products are equipped with smart capabilities and this offers new opportunities for exploiting middle-of-life data. The knowledge aggregated in this study will be used in the development of a sophisticated toolbox. This will: (i) integrate various tools under a unified interface, (ii) implement various semantics orientated and smart reasoning-based functions, and (iii) facilitate data transformations by practicing designers in contexts.
...
Companies are getting increasingly interested in learning how different customers use their products. Collecting data about the use of products provides useful insights and facilitates design enhancements. Effective data analytics needs dedicated tools. In this paper, we summarize the results of our literature research done with special attention to existing tools. We observed that everything is changing rapidly and getting more complex in terms of data and processing methods and tools. While remarkable attention has been paid to processing big data, much less is being devoted to effective semantic progressing of middle-of-life (MoL) data. One of our findings is that commercialized data analytics tools have not addressed extraction, aggregation, and handling genuine MoL data adequately. Another one is that the currently available tools are in the lack of the capability to adapt themselves to designers needs and to produce results that could be reused in multiple design tasks. Nowadays products are equipped with smart capabilities and this offers new opportunities for exploiting middle-of-life data. The knowledge aggregated in this study will be used in the development of a sophisticated toolbox. This will: (i) integrate various tools under a unified interface, (ii) implement various semantics orientated and smart reasoning-based functions, and (iii) facilitate data transformations by practicing designers in contexts.
Conference paper
(2015)
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F. Abou Eddahab-Burke, Guy Prodhomme, Cedric Masclet, Jean-François Boujut, Kris Lund
Conference paper
(2015)
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F. Abou Eddahab-Burke, Guy Prudhomme, Cedric Masclet, Kris Lund, Jean-François Boujut
Nowadays the innovation process has become a collective activity where designers have no longer to work only in their own field of expertise but they have also to work with others in project meetings in order to make decisions collectively. The main purpose of this study is to understand how participants argue and converge toward one solution in an upstream phase of an innovation project. Our work is based on a case study. We captured video and audio data and we gathered working documents from an innovation project meeting in a French company. Our first macro analysis showed that during this meeting there were no explicit decisions concerning both technical and business model solutions. We also noticed that the technical discussions converged towards a solution. This
convergence was based on a multitude of mobilized criteria that we structured in different categories. In future research we plan to carry out micro analyses of particular moments highlighted in our current work in order to understand this convergence process.
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Nowadays the innovation process has become a collective activity where designers have no longer to work only in their own field of expertise but they have also to work with others in project meetings in order to make decisions collectively. The main purpose of this study is to understand how participants argue and converge toward one solution in an upstream phase of an innovation project. Our work is based on a case study. We captured video and audio data and we gathered working documents from an innovation project meeting in a French company. Our first macro analysis showed that during this meeting there were no explicit decisions concerning both technical and business model solutions. We also noticed that the technical discussions converged towards a solution. This
convergence was based on a multitude of mobilized criteria that we structured in different categories. In future research we plan to carry out micro analyses of particular moments highlighted in our current work in order to understand this convergence process.
Report
(2014)
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Fatima-Zahra Abou Eddahab-Burke, Badr El Harradi
Cet ouvrage est le fruit d'un long travail portant sur l'étude des usures des cerces d'arrêt bandages d'un exemple de four rotatif. Il essaye de toucher tout aspect de calcul, de conception et de dimensions à travers les différentes solutions proposées. Cette étude est faite sur un exemple de four rotatif qui est l'un des plus populaires actuellement dans l'industrie. Ce livre donne tous les détails allant de la définition du problème jusqu'à la proposition de solutions, et montre comment les solutions ont été construites au cours de l'étude.
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Cet ouvrage est le fruit d'un long travail portant sur l'étude des usures des cerces d'arrêt bandages d'un exemple de four rotatif. Il essaye de toucher tout aspect de calcul, de conception et de dimensions à travers les différentes solutions proposées. Cette étude est faite sur un exemple de four rotatif qui est l'un des plus populaires actuellement dans l'industrie. Ce livre donne tous les détails allant de la définition du problème jusqu'à la proposition de solutions, et montre comment les solutions ont été construites au cours de l'étude.