SEQUAL framework

The SEQUAL framework is systems modelling reference model for evaluating the quality of models. The SEQUAL framework, which stands for "semiotic quality framework" is developed by John Krogstie and others since the 1990s. The SEQUAL framework is a so-called "top-down quality framework", which is based on semiotic theory, such as the works of Charles W. Morris. Building on these theory it "defines several quality aspects based on relationships between a model, a body of knowledge, a domain, a modeling language, and the activities of learning, taking action, and modeling". Its usefulness, according to Mendling et al. (2006), was confirmed in a 2002 experiment by Moody et al.

The SEQUAL framework is systems modelling reference model for evaluating the quality of models. The SEQUAL framework, which stands for "semiotic quality framework" is developed by John Krogstie and others since the 1990s. The SEQUAL framework is a so-called "top-down quality framework", which is based on semiotic theory, such as the works of Charles W. Morris. Building on these theory it "defines several quality aspects based on relationships between a model, a body of knowledge, a domain, a modeling language, and the activities of learning, taking action, and modeling". Its usefulness, according to Mendling et al. (2006), was confirmed in a 2002 experiment by Moody et al. ===Empirical quality=== To evaluate empirical quality, the model should be well externalized. Main aspects are: Ergonomics, readability, layout, and information theory. Basically empirical quality is about the question "Is the model easily readable?". Empirical quality deals with the variety of elements distinguished, error frequencies when being written or read, coding (shapes of boxes) and ergonomics for Computer-Human Interaction for documentation and modeling-tools. Ergonomics is the study of workplace design and the physical and psychological impact it has on workers. This quality is related to readability and layout. There are different factors that have an important impact on visual emphasis like size, solidity, foreground/background differences, colour (red attracts the eye more than other colours), change (blinking or moving symbols attract attention), position and so on. For graph aesthetics there may be different consideration(Battista, 1994, Tamassia, 1988) like angles between edges not be too small, minimize the number of bends along edges, minimize the number of crossings between edges, place nodes with high degree in the centre of the drawing, have symmetry of sons in hierarchies, have uniform density of nodes in the drawing, have verticality of hierarchical structures and so on. ===Syntactical quality=== Syntactic quality is the correspondence between the model M and the language extension L of the language in which the model is written. Three aspects here are: Error detection: During a modeling session, some syntactical errors--- syntactic incompleteness --- should be allowed on a temporary basis. For instance, although the DFD language requires that all processes are linked to a flow, it is difficult to draw a process and a flow simultaneously. Syntactical completeness has to be checked upon user's request. So, in contrast to implicit checks where the tool is forcing the user to follow the language syntax, explicit check can only detect and report on existing errors. The user has to make the corrections. Error correction: to replace a detected error with a correct statement ===Semantic quality=== What is expressed in the model? The semantic goals of this framework are: Validity; if all the statements in the model are correct and related to the problem. M\D = Ø Completeness; if the model contains all relevant and correct statements to solve this problem. D\M = Ø ===Perceived semantic quality=== Perceived semantic quality is the relation between an actor's interpretation of a model and his/her knowledge of the domain. Perceived validity I\K = Ø Perceived completeness K\I = Ø ===Pragmatic quality=== Pragmatic quality is the correspondence between the model and people's interpretation of it. Comprehension is the only pragmatic goal in the framework. It is very important that people that read the model, understand it. No solution is good if no-one understands it. Pragmatic quality relates to the effect the model have on the participants and the world. Four aspects is treated specifically, that: the human interpretation of the model is correct relative to what is meant. the tool interpretation is correct relative to what is meant to be expressed in the model. the participants learn based on the model. the domain is changed (preferably in a positive direction relative to the goal of modeling). Knowledge in domain is "complete": D\K = Ø. Knowledge in domain is "valid": K\D = Ø. Activities for improvement: Stakeholder identification Knowledge source identification Research and investigation Participant selection Participant training Problem definition ===Language quality=== To receive good language quality it is important that: The language is appropriate to the domain. The language is appropriate to the participants' knowledge of modeling languages The language appropriate to express the knowledge of the participants If the language quality is good, it will improve the participants' interpretation and other technical actors' interpretation. For additional detail, see the quality of modelling languages ===Organizational quality=== The organizational quality of the model relates to: That all statements in the model contribute to fulfilling the goals of modeling, or Organizational goal validity. That all the goals of modeling are addressed through the model, or Organizational goal completeness.

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