On the Completeness of Spider Diagrams Augmented with Constants

Diagrammatic reasoning can be described formally by a number of diagrammatic logics; spider diagrams are one of these, and are used for expressing logical statements about set membership and containment. Here, existing work on spider diagrams is extended to include constant spiders that represent specific individuals. We give a formal syntax and semantics for the extended diagram language before introducing a collection of reasoning rules encapsulating logical equivalence and logical consequence. We prove that the resulting logic is sound, complete and decidable

A Normal Form for Spider Diagrams of Order

We develop a reasoning system for an Euler diagram based visual logic, called spider diagrams of order. We de- fine a normal form for spider diagrams of order and provide an algorithm, based on the reasoning system, for producing diagrams in our normal form. Normal forms for visual log- ics have been shown to assist in proving completeness of associated reasoning systems. We wish to use the reasoning system to allow future direct comparison of spider diagrams of order and linear temporal logic

Evaluation of the usability of constraint diagrams as a visual modelling language: theoretical and empirical investigations

This research evaluates the constraint diagrams (CD) notation, which is a formal representation for program specification that has some promise to be used by people who are not expert in software design. Multiple methods were adopted in order to provide triangulated evidence of the potential benefits of constraint diagrams compared with other notational systems. Three main approaches were adopted for this research. The first approach was a semantic and task analysis of the CD notation. This was conducted by the application of the Cognitive Dimensions framework, which was used to examine the relative strengths and weaknesses of constraint diagrams and conventional notations in terms of the perceptive facilitation or impediments of these different representations. From this systematic analysis, we found that CD cognitively reduced the cost of exploratory design, modification, incrementation, searching, and transcription activities with regard to the cognitive dimensions: consistency, visibility, abstraction, closeness of mapping, secondary notation, premature commitment, role-expressiveness, progressive evaluation, diffuseness, provisionality, hidden dependency, viscosity, hard mental operations, and error-proneness. The second approach was an empirical evaluation of the comprehension of CD compared to natural language (NL) with computer science students. This experiment took the form of a web-based competition in which 33 participants were given instructions and training on either CD or the equivalent NL specification expressions, and then after each example, they responded to three multiple-choice questions requiring the interpretation of expressions in their particular notation. Although the CD group spent more time on the training and had less confidence, they obtained comparable interpretation scores to the NL group and took less time to answer the questions, although they had no prior experience of CD notation. The third approach was an experiment on the construction of CD. 20 participants were given instructions and training on either CD or the equivalent NL specification expressions, and then after each example, they responded to three questions requiring the construction of expressions in their particular notation. We built an editor to allow the construction of the two notations, which automatically logged their interactions. In general, for constructing program specification, the CD group had more accurate answers, they had spent less time in training, and their returns to the training examples were fewer than those of the NL group. Overall it was found that CD is understandable, usable, intuitive, and expressive with unambiguous semantic notation

A diagrammatic calculus of fermionic quantum circuits

We introduce the fermionic ZW calculus, a string-diagrammatic language for fermionic quantum computing (FQC). After defining a fermionic circuit model, we present the basic components of the calculus, together with their interpretation, and show how the main physical gates of interest in FQC can be represented in our language. We then list our axioms, and derive some additional equations. We prove that the axioms provide a complete equational axiomatisation of the monoidal category whose objects are systems of finitely many local fermionic modes (LFMs), with maps that preserve or reverse the parity of states, and the tensor product as monoidal product. We achieve this through a procedure that rewrites any diagram in a normal form. As an example, we show how the statistics of a fermionic Mach-Zehnder interferometer can be calculated in the diagrammatic language. We conclude by giving a diagrammatic treatment of the dual-rail encoding, a standard method in optical quantum computing used to perform universal quantum computation

The Semiotics of Spider Diagrams

Spider diagrams are based on Euler and Venn/Peirce diagrams, forming a system which is as expressive as monadic first orderlogic with equality. Rather than being primarily intended for logicians,spider diagrams were developed at the end of the 1990s in the context of visual modelling and software specification. We examine the original goals of the designers, the ways in which the notation has evolved and itsconnection with the philosophical origins of the logical diagrams of Euler, Venn and Peirce on which spider diagrams are based. Using Peirce's concepts and classification of signs, we analyse the ways in which different sign types are exploited in the notation. Our hope is that this analysis may be of interest beyond those readers particularly interested in spider diagrams, and act as a case study in deconstructing a simple visual logic. Along the way, we discuss the need for a deeper semiotic engagement in visual modelling

Euler diagram-based notations

Euler diagrams have been used for centuries as a means for conveying logical statements in a simple, intuitive way. They form the basis of many diagrammatic notations used to represent set-theoretic relationships in a wide range of contexts including software modelling, logical reasoning systems, statistical data representation, database search queries and file system management. In this paper we survey notations based on Euler diagrams with particular emphasis on formalization and the development of software tool support

A cognitive exploration of the “non-visual” nature of geometric proofs

Why are Geometric Proofs (Usually) “Non-Visual”? We asked this question as a way to explore the similarities and differences between diagrams and text (visual thinking versus language thinking). Traditional text-based proofs are considered (by many to be) more rigorous than diagrams alone. In this paper we focus on human perceptual-cognitive characteristics that may encourage textual modes for proofs because of the ergonomic affordances of text relative to diagrams. We suggest that visual-spatial perception of physical objects, where an object is perceived with greater acuity through foveal vision rather than peripheral vision, is similar to attention navigating a conceptual visual-spatial structure. We suggest that attention has foveal-like and peripheral-like characteristics and that textual modes appeal to what we refer to here as foveal-focal attention, an extension of prior work in focused attention

Reasoning with concept diagrams about antipatterns

Ontologies are notoriously hard to define, express and reason about. Many tools have been developed to ease the debugging and the reasoning process with ontologies, however they often lack accessibility and formalisation. A visual representation language, concept diagrams, was developed for expressing and reasoning about ontologies in an accessible way. Indeed, empirical studies show that concept diagrams are cognitively more accessible to users in ontology debugging tasks. In this paper we answer the question of “ How can concept diagrams be used to reason about inconsistencies and incoherence of ontologies?”. We do so by formalising a set of inference rules for concept diagrams that enables stepwise verification of the inconsistency and/or incoherence of a set of ontology axioms. The design of inference rules is driven by empirical evidence that concise (merged) diagrams are easier to comprehend for users than a set of lower level diagrams that offer a one-to-one translation of OWL ontology axioms into concept diagrams. We prove that our inference rules are sound, and exemplify how they can be used to reason about inconsistencies and incoherence. Finally, we indicate how our rules can serve as a foundation for new rules required when representing ontologies in diverse new domains