Nicolas Genon

Analysing the cognitive effectiveness of the BPMN 2.0 visual notation

BPMN 2.0 is an OMG standard and one of the leading process modelling notations. Although the current language specification recognises the importance of defining a visual notation carefully, it does so by relying on common sense, intuition and emulation of common practices, rather than by adopting a rigorous scientific approach. This results in a number of suboptimal language design decisions that may impede effective model-mediated communication between stakeholders. We demonstrate and illustrate this by looking at BPMN 2.0 through the lens of the Physics of Notations, a collection of evidence-based principles that together form a theory of notation design. This work can be considered a first step towards making BPMN 2.0s visual notation more cognitively effective.

Adapting Secure Tropos for Security Risk Management in the Early Phases of Information Systems Development

Security is a major target for todays information systems (IS) designers. Security modelling languages exist to reason on security in the early phases of IS development, when the most crucial design decisions are made. Reasoning on security involves analysing risk, and effectively communicating risk-related information. However, we think that current languages can be improved in this respect. In this paper, we discuss this issue for Secure Tropos, the language supporting the eponymous agent-based IS development. We analyse it and suggest improvements in the light of an existing reference model for IS security risk management. This allows for checking Secure Tropos concepts and terminology against those of current risk management standards, thereby improving the conceptual appropriateness of the language. The paper follows a running example, called eSAP, located in the healthcare domain.

Visual notation design 2.0: Towards user comprehensible requirements engineering notations

The success of requirements engineering depends critically on effective communication between business analysts and end users, yet empirical studies show that business stakeholders understand RE notations very poorly. This paper proposes a novel approach to designing RE visual notations that actively involves naïve users in the process. We use i*, one of the most influential RE notations, to demonstrate the approach, but the same approach could be applied to any RE notation. We present the results of 5 related empirical studies that show that novices outperform experts in designing symbols that are comprehensible to novices: the differences are both statistically significant and practically meaningful. Symbols designed by novices increased semantic transparency (their ability to be spontaneously interpreted by other novices) by almost 300% compared to the existing i* notation. The results challenge the conventional wisdom about visual notation design: that it should be conducted by a small group of experts; our research suggests that it should instead be conducted by large numbers of novices. The approach is consistent with Web 2.0, in that it harnesses the collective intelligence of end users and actively involves them in the notation design process as “prosumers” rather than passive consumers. We believe this approach has the potential to radically change the way visual notations are designed in the future.

Analysing the cognitive effectiveness of the UCM visual notation

The Use Case Map (UCM) notation is a scenario modelling language part of ITU-Ts User Requirements Notation and intended for the elicitation, analysis, specification, and validation of requirements. Like many visual modelling languages, the concrete graphical syntax of the UCM notation has not been designed taking cognitive effectiveness formally into consideration. This paper conducts a systematic analysis of the UCM notation through an evaluation against a set of evidencebased principles for visual notation design. Several common weaknesses are identified and some improvements suggested. A broader goal of the paper is to raise the awareness of the modelling, language design, and standardization communities about the need for such evaluations and the maturity of the techniques to perform them.

Towards a more semantically transparent i* visual syntax

[Context and motivation]i* is one of the most popular modelling languages in Requirements Engineering. i* models are meant to support communication between technical and non-technical stakeholders about the goals of the future system. Recent research has established that the effectiveness of model-mediated communication heavily depends on the visual syntax of the modelling language. A number of flaws in the visual syntax of i* have been uncovered and possible improvements have been suggested. [Question/problem] Producing effective visual notations is a complex task that requires taking into account various interacting quality criteria. In this paper, we focus on one of those criteria: Semantic Transparency, that is, the ability of notation symbols to suggest their meaning. [Principal ideas/results] Complementarily to previous research, we take an empirical approach. We give a preview of a series of experiments designed to identify a new symbol set for i* and to evaluate its semantic transparency. [Contribution] The reported work is an important milestone on the path towards cognitively effective requirements modelling notations. Although it does not solve all the problems in the i* notation, it illustrates the usefulness of an empirical approach to visual syntax definition. This approach can later be transposed to other quality criteria and other notations.

Feature-Based Elicitation of Cognitively Efficient Visualizations for SPL Configurations

Configuring a SPL is a cognitively difficult activity that requires a deep understanding of the features and their constraints to be performed effectively. To this end, SPL configurators have been equipped with various visualizations to assist users in their tasks. However, there are many ways to visualize data: the process of associating an efficient visualization to a given (configuration) task is neither well-understood nor systematically applied, resulting in confusing visualizations yielding configuration errors. In this chapter, we offer such a process, based on theories of the visualization community for data representation. The first step consists in choosing the data to be visualized. This selection induces restrictions on the types of visualization that are then computed based on the data characteristics and best practices from semiology and visual languages. Designers can then select an efficient visualization for the intended task. Our process is supported by feature models and FAMILIAR to merge and constrain the set of applicable visualizations.

Unlocking Visual Understanding: Towards Effective Keys for Diagrams

Diagrams are (meant to be) effective communication supports to convey information to stakeholders. Being communication supports, they have to be quickly and accurately understood. To enable immediateness, many disciplines such as cartography rely on keys, which categorise diagram symbols and bind them to their meaning. Software engineering extensively relies on visual languages such as UML to communicate amongst the many stakeholders involved in information systems’ life-cycle. Yet, keys are barely used in these diagrams, hindering (immediate) understanding and limiting it to language experts. We provide a disciplined approach to design effective keys, by adapting graphic semiology theory and cartographers’ know-how to software diagrams. We illustrate our method on a UML class diagram. Designing effective keys raises questions about the concerns and tasks to be addressed by the diagram, and even, reveals issues about the language itself.

Positioning Map: a Visual Technique to Improve the Layout of Diagram Contextual Information

The presentation of information is a difficult activity. It requires to deal with model complexity, characterised among other things by the number of visual elements per diagram. In this position paper, we propose a positioning map constructed by combining the navigation and locator maps – two techniques resulting from the theoretical principles of effective communication. We believe that the positioning map is a better means than navigation and locator maps together to decompose models and to integrate their information cognitively. However, we still need to validate our proposal through empirical studies.