Systems of Systems Engineering Body of Knowledge (SoSEBoK)

The post reviews the article on Systems of Systems (SoS) that was published in Systems Engineering Body of Knowledge (SEBoK) v. 1.9.1, released on 16th October 2018 available here. The article covers major topics related to SoS, be it the defining of SoS, its characterizations, types, application domains or standards. However, few areas have been identified within the article, improvement of which will help in improved knowledge sharing among the academic community. Furthermore, the suggestions are proposed with a mindset to facilitate knowledge sharing of not only explicit but also tacit knowledge among multiple stakeholders, where the latter is usually regarded as a key to success of any organizations (Fengjie, Fei, & Xin, 2004) and results in higher innovation quality and operational performance (Wang & Wang, 2012). Many studies have been done over the time period to investigate ways of converting explicit knowledge into tacit knowledge like for example by (Nonaka, 1994), where he developed a framework that took analytical approach on the constituent dimensions of knowledge creation. Similarly Bayes algorithm has been implemented by (Sliwa & Patalas-Maliszewska, 2015) in a R&D domain of a manufacturing company to convert tacit into explicit knowledge. Since Body of Knowledge (BoK) is a “set of knowledge within a profession or subject area which is generally agreed as both essential and personally known” (Oliver, 2012) the contents of BoK must encompass information that can facilitate in transformation of tacit knowledge to the reader.
By my reckoning two areas need revision in the article which include highlighting of the similarities between the Systems Engineering (SE) and Systems of Systems Engineering (SoSE) and the description regarding the methodology for collection of the state of the art for the article. The emphasis on highlighting the difference between SE and SoSE is understandable and the detailed description into differences such as management and oversight; operational focus and others is well appreciated. The mentioned differences are fundamental and must not be overlooked but at the same time the article falls short of emphasizing on some of the similarities in SE and SoSE. Mentioning of some of the similarities will not only play the role of a bridging factor between the two but also magnify even more the differences between the two. Similarly, the article also lacks description into the methodology for collection of the state of the art which results in certain confusions. For example, the article initially states that “SoSE is not a new discipline” and later on in the section SoS principles presents SoS as “relatively new area”. This exacerbates the confusion of the reader and fails to provide a clear picture. I reckon that a detailed description into the methodology followed for collection of the state of the art will not only clarify the developed confusion but also minimize any future contingencies. Furthermore, it will also provide insight into the research approach and structure that will magnify the chances of tacit knowledge sharing, which is consistent with previous studies where structure was used to facilitate tacit knowledge exchange (Reber, 1989, 1993; Seger, 1994).

Fengjie, A., Fei, Q., & Xin, C. (2004). Knowledge sharing and Web-based knowledge-sharing platform. IEEE International Conference on E-Commerce Technology for Dynamic E-Business, 278–281.
Nonaka, I. (1994). A Dynamic Theory of Organizational Knowledge Creation. Organization Science.
Oliver, G. (2012). Foundations of the assumed business operations and strategy body of knowledge (BOSBOK) : an outline of shareable knowledge. Retrieved from,+p.+3.&ots=zRrYIpwDHj&sig=xXh7qdwklH5XLujFFXMMfmrwM
Reber, A. (1989). Implicit learning and Tacit Knowledge. Journal of Experimental Psychology: General, 118(3), 219–235.
Reber, A. (1993). Implicit learning and Tacit knowledge: An essay on the cognitive unconscious. Oxford university press, New York, NY.
Seger, C. A. (1994). Implicit learning. Psychological Bulletin, 115(2), 163–196.
Sliwa, M. ´, & Patalas-Maliszewska, J. (2015). Model of converting tacit knowledge into explicit knowledge on the example of R & D department of the manufacturing company , including evaluation of knowledge workers ’ usefulness. Journal of Theoretical and Applied Computer Science, 9(3), 25–34.
Wang, Z., & Wang, N. (2012). Knowledge sharing, innovation and firm performance. Expert Systems with Applications, 39(10), 8899–8908.

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