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To the above end, advanced engineering informatics acknowledges that engineering work is a [[Information#As an influence which leads to a transformation|knowledge]]-intensive activity.<ref name="KunzEdit02">{{cite journal |title=Editorial |journal=Advanced Engineering Informatics |author=Kunz, J.C.; Smith, I.F.C.; Tomiyama, T. |volume=16 |issue=1 |pages=1–2 |year=2002 |doi=10.1016/S1474-0346(02)00004-6}}</ref> Any research into how computational methods can support engineering work needs to start with an explicit formalization of the knowledge engineers posses. Advanced engineering informatics is a specific discipline of knowledge engineering<ref name="SowaPrinc14">{{cite book |title=Principles of Semantic Networks: Explorations in the Representation of Knowledge |author=Sowa, J.F. |publisher=Elsevier |year=2014 |isbn=9781483221144}}</ref> with an overarching research question: “How can we formalize complex engineering knowledge to develop advanced computational methods that help engineers to solve practical problems within their constraints and budgets?” | To the above end, advanced engineering informatics acknowledges that engineering work is a [[Information#As an influence which leads to a transformation|knowledge]]-intensive activity.<ref name="KunzEdit02">{{cite journal |title=Editorial |journal=Advanced Engineering Informatics |author=Kunz, J.C.; Smith, I.F.C.; Tomiyama, T. |volume=16 |issue=1 |pages=1–2 |year=2002 |doi=10.1016/S1474-0346(02)00004-6}}</ref> Any research into how computational methods can support engineering work needs to start with an explicit formalization of the knowledge engineers posses. Advanced engineering informatics is a specific discipline of knowledge engineering<ref name="SowaPrinc14">{{cite book |title=Principles of Semantic Networks: Explorations in the Representation of Knowledge |author=Sowa, J.F. |publisher=Elsevier |year=2014 |isbn=9781483221144}}</ref> with an overarching research question: “How can we formalize complex engineering knowledge to develop advanced computational methods that help engineers to solve practical problems within their constraints and budgets?” | ||
With this research question—above and beyond improving our understanding in how to formalize complex engineering knowledge through explicit representations and symbolic or numerical process models—advanced engineering informatics is hence also concerned with understanding how such representations can support practical engineering work. To this end, topics for research are not only the development of advanced computational methods based on explicitly formulated knowledge, but also exploring the representation of information in graphical user interfaces, the provision of extensive knowledge bases through large scale databases, or how engineers and engineering groups can be supported in interpreting solutions and intermediate solution spaces.<ref name="KunzEdit02"> In all of these endeavors, an explicit focus on engineering knowledge is required to advance this understanding. | With this research question—above and beyond improving our understanding in how to formalize complex engineering knowledge through explicit representations and symbolic or numerical process models—advanced engineering informatics is hence also concerned with understanding how such representations can support practical engineering work. To this end, topics for research are not only the development of advanced computational methods based on explicitly formulated knowledge, but also exploring the representation of information in graphical user interfaces, the provision of extensive knowledge bases through large scale databases, or how engineers and engineering groups can be supported in interpreting solutions and intermediate solution spaces.<ref name="KunzEdit02" /> In all of these endeavors, an explicit focus on engineering knowledge is required to advance this understanding. | ||
Despite the scientific and practical importance, most studies published in the scientific engineering journals fail to explicitly address aspects of engineering knowledge formalization and representation. This also holds for publications focusing on the engineering of our built environment. More often than not, new methods, algorithms, or results of data analysis efforts are presented without the contextualization of the suggested methods within a specific engineering context. Often it is not clear how suggested novel methods make use of explicitly formalized engineering knowledge and how the methods support engineers in their knowledge-intensive tasks. By large, the scientific engineering community still needs to establish a continuous growing body of scientific knowledge about how advanced computational methods can support engineers. Consequently, little general understanding about how novel computation methods can be implemented across tasks and engineering disciplines exists. This lack, in turn, has slowed down the development of solutions that could truly enhance practical engineering work. | Despite the scientific and practical importance, most studies published in the scientific engineering journals fail to explicitly address aspects of engineering knowledge formalization and representation. This also holds for publications focusing on the engineering of our built environment. More often than not, new methods, algorithms, or results of data analysis efforts are presented without the contextualization of the suggested methods within a specific engineering context. Often it is not clear how suggested novel methods make use of explicitly formalized engineering knowledge and how the methods support engineers in their knowledge-intensive tasks. By large, the scientific engineering community still needs to establish a continuous growing body of scientific knowledge about how advanced computational methods can support engineers. Consequently, little general understanding about how novel computation methods can be implemented across tasks and engineering disciplines exists. This lack, in turn, has slowed down the development of solutions that could truly enhance practical engineering work. | ||
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This paper is an effort to refocus the current scientific discourse on the importance of engineering knowledge. To this end, we attempt to first provide a clear definition and description of the underlying philosophical basis of knowledge formulation and knowledge engineering as the foundation for all scientific inquiry within the field of advanced engineering informatics. We illustrate these definition and descriptions using a number of recently published articles that focus on the domain of built environment engineering as example. | |||
Our second goal for the paper is to start a discussion about the required methodological approaches for advanced engineering informatics [[research]] practice. So far there is little to no discourse about research methods within the field, which has significantly hindered its establishment among the other scientific disciplines. To catalyze this discourse, in the second part of the paper we suggest different research approaches and some underlying theories. | |||
Of course, like every other scientific discipline, the definitions, concepts, methods, and approaches associated with advanced engineering informatics are an ever-moving target. Therefore, this paper can only represent our current reflections and thinking in the field and is intended to provide food for thought and a catalyst for more reflective and vibrant discussion. By no means are the presented concepts of knowledge formalization and research methods meant as fixed bearing points, but rather as points of departure for wider theoretical explorations. Therefore, the paper also provides an elaborated discussion section with suggestions for future important areas of inquiry. | |||
In the next section, we introduce the theoretical underpinnings of knowledge representation and knowledge formalization. That section also illustrates these underpinnings using four recently published research studies. Then different research methods that might be appropriate for advanced engineering informatics research are suggested. Finally, an extensive discussion with suggestions for important research directions are presented, along with conclusions. | |||
==Knowledge representation and formalization== | |||
==References== | ==References== | ||
Revision as of 22:53, 4 January 2021
| Full article title |
Advanced engineering informatics: Philosophical and methodological foundations with examples from civil and construction engineering |
|---|---|
| Journal | Developments in the Built Environment |
| Author(s) | Hartmann, Timo; Trappey, Amy |
| Author affiliation(s) | Technische Universität Berlin, National Tsing Hua University |
| Primary contact | timo dot hartmann at tu-berlin dot de |
| Year published | 2020 |
| Volume and issue | 4 |
| Article # | 100020 |
| DOI | 10.1016/j.dibe.2020.100020 |
| ISSN | 2666-1659 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.sciencedirect.com/science/article/pii/S2666165920300168 |
| Download | https://www.sciencedirect.com/science/article/pii/S2666165920300168/pdfft (PDF) |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
We argue that the representation and formalization of complex engineering knowledge is the main aim of inquiries in the scientific field of advanced engineering informatics. We introduce ontology and logic as underlying methods to formalize knowledge. We also suggest that it is important to account for the purpose of engineers and the context they work in while representing and formalizing knowledge. Based on the concepts of ontology, logic, purpose, and context, we discuss different possible research methods and approaches that scholars can use to formalize complex engineering knowledge and to validate whether a specific formalization can support engineers with their complex tasks. On the grounds of this discussion, we suggest that research efforts in advanced engineering should be conducted in a bottom-up manner, closely involving engineering practitioners. We also suggest that researchers make use of social science methods while both eliciting knowledge to formalize and validating that formalized knowledge.
Keywords: advanced engineering informatics, knowledge formalization, knowledge engineering, computing in engineering, research method, engineering
Introduction: Attempting to define advanced engineering informatics
Engineers invent, design, analyze, build, test and maintain complex physical systems, structures, and materials to solve some of societies most urgent problems, but also to improve the quality of life of individuals. Engineering is artifact-centered and concerned with realizing physical products of all shapes, sizes, and functions. Engineers routinely use computers and engineering work is almost entirely digitized. Few tasks are conducted without some sort of digital support. Surprisingly still, some engineering disciplines, and in particular, civil engineers are termed (and term themselves) as digital laggards. Resistance to apply new digital technologies is high, and more often than not the real benefits of applying new digital technologies to support engineering design tasks is not perceived, visible, or existing.
The existing resistance towards adopting advanced computational tools has traditionally been attributed to individual and social characteristics of engineers themselves. For example, traditionally, studies focusing on the work of civil and construction engineers attributed resistance to the organizational characteristics of the industry, such as the seminal study of Mitropoulos and Tatum[1] about general industry characteristics, or the more recent study of Linderoth[2] looking at the specific collaboration network structure of the industry. Others like Davis and Songer[3] have attributed the resistance of engineers to adopt new technologies to individual characteristics of engineers, such as age, gender, general computer understanding, or experience.
Independent of resistance and its cause and despite the ever growing amount of digital applications that are used by engineers, it rather seems as if engineers are increasingly struggling with providing and improving our society’s complex engineering systems.[4] This, in particular, holds in relation to the engineering systems within our built environment. Little research has provided insights into how the characteristics of computational tools influenced adoptions. Those studies that did showed that there seems to be a large difference between the general expectations of the engineers with the support that the tools could truly provide.[5][6] This paradox of supporting today’s engineering work with adequate computational tools has triggered the engineering community to develop a new scientific field of study and inquiry: advanced engineering informatics.
Advanced engineering informatics is motivated by the quest to empower engineers to cope with the ever increasing complexity of the systems they have to provide. The discipline strives to provide means that allow engineers to leverage their understanding of the behavior of complex systems through advanced simulation and data analysis methods. It also strives at improving the collaboration and communication of engineers within the ever more complex collaborative interdisciplinary arrangements they face.
Unlike other related disciplines, advanced engineering informatics focuses not on the automation of mundane tasks, but on developing, researching, and exploring methods to enhance the existing work environment of engineers. Advanced engineering informatics scholars believe that well-designed computational methods have the potential to empower engineers in ways that have previously not been possible. They believe that computers cannot only incrementally speed up engineering design work, but significantly disrupt engineering tasks throughout the entire product development life-cycle, from the early stages of conceptual design, to detailed engineering design, to production, to the maintenance of engineered systems.
To the above end, advanced engineering informatics acknowledges that engineering work is a knowledge-intensive activity.[7] Any research into how computational methods can support engineering work needs to start with an explicit formalization of the knowledge engineers posses. Advanced engineering informatics is a specific discipline of knowledge engineering[8] with an overarching research question: “How can we formalize complex engineering knowledge to develop advanced computational methods that help engineers to solve practical problems within their constraints and budgets?”
With this research question—above and beyond improving our understanding in how to formalize complex engineering knowledge through explicit representations and symbolic or numerical process models—advanced engineering informatics is hence also concerned with understanding how such representations can support practical engineering work. To this end, topics for research are not only the development of advanced computational methods based on explicitly formulated knowledge, but also exploring the representation of information in graphical user interfaces, the provision of extensive knowledge bases through large scale databases, or how engineers and engineering groups can be supported in interpreting solutions and intermediate solution spaces.[7] In all of these endeavors, an explicit focus on engineering knowledge is required to advance this understanding.
Despite the scientific and practical importance, most studies published in the scientific engineering journals fail to explicitly address aspects of engineering knowledge formalization and representation. This also holds for publications focusing on the engineering of our built environment. More often than not, new methods, algorithms, or results of data analysis efforts are presented without the contextualization of the suggested methods within a specific engineering context. Often it is not clear how suggested novel methods make use of explicitly formalized engineering knowledge and how the methods support engineers in their knowledge-intensive tasks. By large, the scientific engineering community still needs to establish a continuous growing body of scientific knowledge about how advanced computational methods can support engineers. Consequently, little general understanding about how novel computation methods can be implemented across tasks and engineering disciplines exists. This lack, in turn, has slowed down the development of solutions that could truly enhance practical engineering work.
This paper is an effort to refocus the current scientific discourse on the importance of engineering knowledge. To this end, we attempt to first provide a clear definition and description of the underlying philosophical basis of knowledge formulation and knowledge engineering as the foundation for all scientific inquiry within the field of advanced engineering informatics. We illustrate these definition and descriptions using a number of recently published articles that focus on the domain of built environment engineering as example.
Our second goal for the paper is to start a discussion about the required methodological approaches for advanced engineering informatics research practice. So far there is little to no discourse about research methods within the field, which has significantly hindered its establishment among the other scientific disciplines. To catalyze this discourse, in the second part of the paper we suggest different research approaches and some underlying theories.
Of course, like every other scientific discipline, the definitions, concepts, methods, and approaches associated with advanced engineering informatics are an ever-moving target. Therefore, this paper can only represent our current reflections and thinking in the field and is intended to provide food for thought and a catalyst for more reflective and vibrant discussion. By no means are the presented concepts of knowledge formalization and research methods meant as fixed bearing points, but rather as points of departure for wider theoretical explorations. Therefore, the paper also provides an elaborated discussion section with suggestions for future important areas of inquiry.
In the next section, we introduce the theoretical underpinnings of knowledge representation and knowledge formalization. That section also illustrates these underpinnings using four recently published research studies. Then different research methods that might be appropriate for advanced engineering informatics research are suggested. Finally, an extensive discussion with suggestions for important research directions are presented, along with conclusions.
Knowledge representation and formalization
References
- ↑ Mitropoulos, P.; Tatum, C.B. (2000). "Forces Driving Adoption of New Information Technologies". Journal of Construction Engineering and Management 126 (5): 340–8. doi:10.1061/(ASCE)0733-9364(2000)126:5(340).
- ↑ Linderoth, H.C.J. (2010). "Understanding adoption and use of BIM as the creation of actor networks". Automation in Construction 19 (1): 66–72. doi:10.1016/j.autcon.2009.09.003.
- ↑ Davis, K.A.; Songer, A.D. (2009). "Resistance to IT Change in the AEC Industry: Are the Stereotypes True?". Journal of Construction Engineering and Management 135 (12): 1324-1333. doi:10.1061/(ASCE)CO.1943-7862.0000108.
- ↑ de Weck, O.L.; Roos, D.; Magee, C.L. (2011). Engineering Systems: Meeting Human Needs in a Complex Technological World. MIT Press. ISBN 9780262016704.
- ↑ Hartmann, T.; van Meerveld, H.; Vossebeld, N. et al. (2012). "Aligning building information model tools and construction management methods". Automation in Construction 22 (1): 605–13. doi:10.1016/j.autcon.2011.12.011.
- ↑ Hartmann, T. (2011). "Goal and Process Alignment during the Implementation of Decision Support Systems by Project Teams". Journal of Construction Engineering and Management 137 (12): 1134–41. doi:10.1061/(ASCE)CO.1943-7862.0000389.
- ↑ 7.0 7.1 Kunz, J.C.; Smith, I.F.C.; Tomiyama, T. (2002). "Editorial". Advanced Engineering Informatics 16 (1): 1–2. doi:10.1016/S1474-0346(02)00004-6.
- ↑ Sowa, J.F. (2014). Principles of Semantic Networks: Explorations in the Representation of Knowledge. Elsevier. ISBN 9781483221144.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
