Knowledge Centric Systems Engineering for better projects

Ambiguity is a factor that can jeopardize the optimal development of a project, as decisions over the requirements statement are made subjectively. And luckily this aspect can be under control if we apply Systems Engineering centred on Knowledge and Quality to develop better assets of information during the project lifecycle. There are four main aspects that aids KCSE (Knowledge Centric Systems Engineering) implementation within an organization.

Discovering Information in Requirements Documents: The concepts taught during the PoC Case Study aims to help engineers to identify the main elements when users are creating or analysing a requirement document, so as to enhance the early discovery of issues.

Controlled information to unify requirements interpretation: Requirements documents contain both structured (requirement objects, tables, …) and unstructured information (comments, additional information, …), this complicates the understanding of the specification’s purpose. The Organization needs to find the methods and tools to organize information from technical specifications in a structured Knowledge Base. Thus, the ontology in combination with the tools aids the understanding of the meaning (semantics) of textual requirements and their related information (i.e. models), reducing the ambiguity and inconsistencies in the documents and promoting a common understanding of the different requirement statements.

Identifying weaknesses and challenges in requirements documents: When an organization receives or delivers a requirements specification, it is hoped that what is defined in the document is going to persist until the end of the project. Hence this document will impact greatly the evolution of the project, so it is important to identify the points to be focused on, in order to reduce risk. With the proper understanding of the main metrics to evaluate and identify incompleteness and inconsistency issues in the documents, as well as correctness errors in the requirements statement, an organization will understand the most crucial elements to identify in the requirements documents that might impact the development of the system.

Building up the Knowledge Base or Ontology: The requirement specifications commonly include several elements of information, as unstructured information (descriptions, standards and regulations, …), requirements (different typologies, levels of detail, …), terminology (definitions, acronyms, …), interfaces, traceability matrices, data flow diagrams, and many others. All these items of information can be modelled in a Knowledge Base (or Ontology) during the lifetime of the project.

Verification analysis: Smarter and Quicker: The different elements for the verification (and testing) tasks are critical for the integration of the system. These verification elements are designed in accordance with the information stated in the requirements documents, interfaces, data flow diagrams, and other information that must comply with the quality priorities defined by the organization.

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