scholarly journals iOntoBioethics: A Framework for the Agile Development of Bioethics Ontologies in Pandemics, Applied to COVID-19

2021 ◽  
Vol 8 ◽  
Author(s):  
Mohammed Odeh ◽  
Faten F. Kharbat ◽  
Rana Yousef ◽  
Yousra Odeh ◽  
Dina Tbaishat ◽  
...  
Keyword(s):  
Research Design ◽  
Design Science ◽  
Big Data Analytics ◽  
Science Research ◽  
Search Space ◽  
Research Literature ◽  
Agile Development ◽  
Learning Stage ◽  
Domain Experts ◽  
Open Platform

Background: Few ontological attempts have been reported for conceptualizing the bioethics domain. In addition to limited scope representativeness and lack of robust methodological approaches in driving research design and evaluation of bioethics ontologies, no bioethics ontologies exist for pandemics and COVID-19. This research attempted to investigate whether studying the bioethics research literature, from the inception of bioethics research publications, facilitates developing highly agile, and representative computational bioethics ontology as a foundation for the automatic governance of bioethics processes in general and the COVID-19 pandemic in particular.Research Design: The iOntoBioethics agile research framework adopted the Design Science Research Methodology. Using systematic literature mapping, the search space resulted in 26,170 Scopus indexed bioethics articles, published since 1971. iOntoBioethics underwent two distinctive stages: (1) Manually Constructing Bioethics (MCB) ontology from selected bioethics sources, and (2) Automatically generating bioethics ontological topic models with all 26,170 sources and using special-purpose developed Text Mining and Machine-Learning (TM&ML) engine. Bioethics domain experts validated these ontologies, and further extended to construct and validate the Bioethics COVID-19 Pandemic Ontology.Results: Cross-validation of the MCB and TM&ML bioethics ontologies confirmed that the latter provided higher-level abstraction for bioethics entities with well-structured bioethics ontology class hierarchy compared to the MCB ontology. However, both bioethics ontologies were found to complement each other forming a highly comprehensive Bioethics Ontology with around 700 concepts and associations COVID-19 inclusive.Conclusion:The iOntoBioethics framework yielded the first agile, semi-automatically generated, literature-based, and domain experts validated General Bioethics and Bioethics Pandemic Ontologies Operable in COVID-19 context with readiness for automatic governance of bioethics processes. These ontologies will be regularly and semi-automatically enriched as iOntoBioethics is proposed as an open platform for scientific and healthcare communities, in their infancy COVID-19 learning stage. iOntoBioethics not only it contributes to better understanding of bioethics processes, but also serves as a bridge linking these processes to healthcare systems. Such big data analytics platform has the potential to automatically inform bioethics governance adherence given the plethora of developing bioethics and COVID-19 pandemic knowledge. Finally, iOntoBioethics contributes toward setting the first building block for forming the field of “Bioethics Informatics”.

scholarly journals SHAPES Cyber Secure HealthCare Platform in Digital Environments

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Large Scale ◽  
Design Science ◽  
Research Question ◽  
Science Research ◽  
Ageing Population ◽  
Security Issues ◽  
Open Platform ◽  
Digital Environments ◽  
Future Society ◽  
Considerable Work

The SHAPES project is an ambitious endeavor that gathers stakeholders from across Europe to create, deploy and pilot at large-scale a EU-standardized open platform incorporating and integrating a broad range of solutions, including technological, organizational, clinical, educational and societal, to enable the ageing population of Europe to remain healthy, active and productive, as well as to maintain a high quality of life and sense of wellbeing for the longest time possible. The research question of this design science research (DSR) is how to build and deploy health and care (H&C) services into a future society in such a way that citizens are able to use them safely in their everyday lives? We found that considerable work is needed to develop the required architecture in smart societies: information architecture, integrations architecture, target architecture, security architecture, and security issues. Service chains must be checked against the architectures to ensure no risks are present

Metamodeling the e-waste domain to support decision-making

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Andrea Herrera ◽  
Paola Lara ◽  
Mario Sánchez ◽  
Jorge Villalobos
Keyword(s):  
Decision Making ◽  
Structural Model ◽  
Design Science ◽  
Conceptual Modeling ◽  
Science Research ◽  
Behavioral Model ◽  
Content Type ◽  
Domain Experts ◽  
Simulation Techniques ◽  
Is Design

PurposeThis paper proposes a conceptualization of the e-waste domain, formalized through a metamodel, to express complex e-waste realities in a simple manner. This also enables the transition from a structural model to a behavioral model to implement analysis techniques.Design/methodology/approachThe methodology used is design science research (DSR), a problem-solving paradigm which seeks to construct a working artifact and prove its relevance. The artifact, a metamodel for the e-waste domain, was constructed through an iterative manner and later analyzed to conclude its theoretical relevance and contributions in this domain. As part of the approach, the authors used supplementary techniques such as systematic literature review (SLR), conceptual modeling (CM) and system dynamics (SD).FindingsThe application in the e-waste domain of CM techniques such as metamodeling, model-to-model transformation and simulation is valuable for supporting decision-making, especially when combined with SD. The approach presented in this paper, the conceptual tools and different simulation techniques could also be applied in other complex domains to obtain similar results.Practical implicationsThe modeling method to apply simulation techniques is targeted toward the e-waste domain experts to understand, design, implement, measure and improve strategies and public policies.Originality/valueThe use of CM techniques to model and analyze structural and behavioral e-waste scenarios.

scholarly journals Design Science Research: Evaluation in the Lens of Big Data Analytics

Systems ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 27 ◽  
Author(s):  
Ahmed Elragal ◽  
Moutaz Haddara
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Design Research ◽  
Research Evaluation ◽  
Design Science ◽  
Big Data Analytics ◽  
Science Research ◽  
Design Science Research ◽  
Evaluation Phase ◽  
New Type

Given the different types of artifacts and their various evaluation methods, one of the main challenges faced by researchers in design science research (DSR) is choosing suitable and efficient methods during the artifact evaluation phase. With the emergence of big data analytics, data scientists conducting DSR are also challenged with identifying suitable evaluation mechanisms for their data products. Hence, this conceptual research paper is set out to address the following questions. Does big data analytics impact how evaluation in DSR is conducted? If so, does it lead to a new type of evaluation or a new genre of DSR? We conclude by arguing that big data analytics should influence how evaluation is conducted, but it does not lead to the creation of a new genre of design research.

Designing an architecture description language for nontechnical actors and purposes (NOTE-ADL)

2020 ◽  
Vol 33 (3) ◽  
pp. 482-501
Author(s):  
Stefan Strohmeier ◽  
Felix Gross
Keyword(s):  
Design Science ◽  
Conceptual Modeling ◽  
Science Research ◽  
Research Literature ◽  
Software Architectures ◽  
Communication Tool ◽  
Description Language ◽  
Content Type ◽  
Architecture Description Language ◽  
Architecture Description

PurposeThe paper proposes the development of a graphical architecture description language (ADL) that allows a better understanding of software architectures for nontechnical actors and purposes and, beyond, can serve as a communication tool between domain experts and IT experts, for instance, in a software development process.Design/methodology/approachThe paper follows the methods and guidelines of design science research. By deriving characteristics and general requirements for ADLs from a research literature review and from industry standards, the paper provides a conceptual modeling approach for an ADL. The model design is based on typical requirements and suggestions derived from literature and related work. The application possibilities and advantages are then demonstrated with a usage scenario.FindingsThe paper elaborates a user-oriented ADL that makes software architecture comprehensible for stakeholders and end users. It provides a high level of abstraction and, thus, is not restricted to a particular domain. The paper also provides a corresponding modeling editor as well as an underlying catalogue with symbols and rules for the ADL.Research limitations/implicationsAs this is a conceptual study, the ADL has not been practically evaluated yet. Thus, the usefulness of this academic approach for the industry remains to be validated.Originality/valueThe elaborated ADL can serve as a language to visualize software architectures, particularly in the business domain, in a comprehensible manner. Still, it retains the structured character of ADLs to facilitate communication on an IT-near level. In including nontechnical actors, the approach broadens the overall application capabilities of ADLs.

scholarly journals Lean Based Maturity Framework Integrating Value, BIM and Big Data Analytics: Evidence from AEC Industry

2021 ◽  
Vol 13 (18) ◽  
pp. 10029
Author(s):  
Gökhan Demirdöğen ◽  
Nihan Sena Diren ◽  
Hande Aladağ ◽  
Zeynep Işık
Keyword(s):  
Big Data ◽  
Construction Industry ◽  
Negative Impact ◽  
Design Science ◽  
Big Data Analytics ◽  
Value Added ◽  
Science Research ◽  
Research Problem ◽  
Design Cycle ◽  
Aec Industry

The construction industry is considered as one of the least productive, highest energy consuming, and least digitized industries. The Lean Management (LM) philosophy became a significant way for eliminating non-value-added activities and wastes during a building’s lifecycle. However, studies have shown that philosophies are not efficient by themselves to solve the issues of the construction industry. They need to be supported with the appropriate technologies and tools. Therefore, the integrated use of Building Information Modelling (BIM) with LM or Value Engineering (VE) were proposed in the literature. Nonetheless, it was also seen that BIM can provide more insights and improvements when BIM is integrated with data analysis tools to analyze BIM data. In the literature, the synergies between these concepts are generally addressed pairwise, and there is no comprehensive framework which identifies their relationships. Therefore, this study aims to develop a maturity framework that facilitates the adoption of LM, VE, BIM, and Big Data Analytic (BDA) concepts to address long-standing productivity and digitalization issues in the Architecture, Engineering, and Construction (AEC) industry. Design Science Research (DSR) methodology and its three-cycle view (relevance, rigor, and design cycle) were applied to build the proposed maturity framework. Two interviews were performed to identify and observe research problem in relevance cycle. In the rigor cycle, a comprehensive literature review was performed to create a base for the development of the maturity framework. In addition to the developed base of the framework, lean processes were added to this cycle. In the design cycle, the developed framework was evaluated and validated by five experts through face-to-face interviews. The importance of employer’s requirements to adopt the proposed methodologies, the negative impact of change orders, the importance of pre-construction phases to facilitate value creation and waste elimination, and the usage of common data environment with BIM were identified as the prominent application and adaptation issues.

Design Science Research Design

2021 ◽  
pp. 97-116
Author(s):  
Stefan Hunziker ◽  
Michael Blankenagel
Keyword(s):  
Research Design ◽  
Design Science ◽  
Science Research ◽  
Design Science Research

Models for Interpretive Information Systems Research, Part 2

2012 ◽  
pp. 238-255 ◽  
Author(s):  
M. R. (Ruth) De Villiers
Keyword(s):  
Information Systems ◽  
Research Design ◽  
Design Research ◽  
Design Science ◽  
Science Research ◽  
Design Science Research ◽  
Interpretive Research ◽  
Development Research ◽  
Design Based Research ◽  
Research Designs

This chapter introduces interpretive research as a background to research that is time-and context-dependent. The study presents practical, yet theoretical research approaches that are relevant to postgraduate studies and to ad-hoc research. The models proposed as interpretive research designs are development research, design-science research, and design-based research. Systems development, in and of itself, is not research, but when integrated with evaluation and applied both to solve real-world problems and to propose general design principles, it gives rise to development research. Design research – termed design-science research in the domain of information systems (where it has roots in software engineering) and design-based research in educational technology (where the approaches are more pragmatic) – has clearly defined features and methods in each domain respectively. The common attributes are the generation of creative and innovative artifacts to serve in complex situations, and the joint advancement of theory and practice. The three research designs are described, and each is illustrated by an example of a study where the model was applied

Tool-Support for Design Science Research: Design Principles and Instantiation

2017 ◽  
Author(s):  
Jan vom Brocke ◽  
Peter Fettke ◽  
Michael Gau ◽  
Constantin Houy ◽  
Stefan Morana
Keyword(s):  
Research Design ◽  
Design Science ◽  
Science Research ◽  
Design Science Research ◽  
Design Principles ◽  
Tool Support

A design science-based case study of retail chain delivery operations and its implications

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shong-lee Ivan Su ◽  
Xuemei Fan ◽  
Yongyi Shou
Keyword(s):  
Problem Solving ◽  
Design Science ◽  
Route Planning ◽  
Science Research ◽  
Research Process ◽  
Research Literature ◽  
Planning System ◽  
Research Experience ◽  
Content Type ◽  
Supply Chain Logistics

PurposeThe study aims to explore and develop a smart route planning system for the cross-docking delivery operations of a large supermarket chain using an action research (AR) approach and assessing through a design science research (DSR) lens.Design/methodology/approachThis study took a problem-solving AR (PAR) approach toward the delivery operational issue of the case firm. The research process has accorded with the solution incubation and the refinement phases defined by a DSR framework. An intervention-based research framework for DSR is developed to assess the validity of this study as a DSR research and derive mid-range theories.FindingsDramatic operational and financial improvements were achieved for the case firm. Significant and unintended environmental and social benefits were also found. A design proposition (DP) and several mid-range theories are proposed as an extension of AR research to DSR research.Research limitations/implicationsA problem-solving DSR research can be better assessed by the intervention-based DSR framework developed in this study. DSR studies should be encouraged for both practical and theoretical advancement purposes.Practical implicationsA challenging business problem-solving study can be tackled effectively through an industry/academic collaboration taking a PAR approach to deliver substantial values and organization transformational results.Social implicationsDrivers and store associates are safer with smart delivery operations in the case firm.Originality/valueThere are still limited PAR design science case studies in the supply chain/logistics research literature. The research experience and findings gained from this study provide more insights toward how this type of research can be conducted and assessed.

An Intelligent Mechanism to Automatically Discover Emerging Technology Trends: Exploring Regulatory Technology

2022 ◽  
Vol 13 (2) ◽  
pp. 1-29
Author(s):  
Shi Ming Huang ◽  
David C. Yen ◽  
Ting Jyun Yan ◽  
Yi Ting Yang
Keyword(s):  
Trend Analysis ◽  
Design Science ◽  
Science Research ◽  
Additional Time ◽  
Domain Experts ◽  
Cross Domain ◽  
Service Information ◽  
Study Results ◽  
Effective Decision Making ◽  
Google Search

Technology trend analysis uses data relevant to historical performance and extrapolates it to estimate and assess the future potential of technology. Such analysis is used to analyze emerging technologies or predict the growing markets that influence the resulting social or economic development to assist in effective decision-making. Traditional trend analysis methods are time-consuming and require considerable labor. Moreover, the implemented processes may largely rely on the specific knowledge of the domain experts. With the advancement in the areas of science and technology, emerging cross-domain trends have received growing attention for its considerable influence on society and the economy. Consequently, emerging cross-domain predictions that combine or complement various technologies or integrate with diverse disciplines may be more critical than other tools and applications in the same domain. This study uses a design science research methodology, a text mining technique, and social network analysis (SNA) to analyze the development trends concerning the presentation of the product or service information on a company's website. This study applies regulatory technology (RegTech) as a case to analyze and justify the emerging cross-disciplinary trend. Furthermore, an experimental study is conducted using the Google search engine to verify and validate the proposed research mechanism at the end of this study. The study results reveal that, compared with Google Trends and Google Correlate, the research mechanism proposed in this study is more illustrative, feasible, and promising because it reduces noise and avoids the additional time and effort required to perform a further in-depth exploration to obtain the information.

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