Languages of Art: An Approach to a Theory of Symbols.

O'Neill, Brittany; Goodman, Nelson

doi:10.2307/2066203

Cited by 240 publications

(4 citation statements)

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“…We analyzed both visual notations with respect to Moody's design principles, which itself is based on seminal works of human cognition such as communication theory [58], feature integration theory [61], Bertin's work on Semiology of Graphics [4], or Goodman's theory of symbols [23]; and in the following discuss our findings which are summarized in Table 1.…”

Section: Discussionmentioning

confidence: 99%

“…We compare the notations with respect to design principles for visual notations [43] derived from several seminal works in human cognition [4,23,58,61,65] and evaluate them in a comparative user study. 3 We implemented both visual notations in UnSHACLed to allow creating and editing constraints in a constraint language independent way.…”

Section: Contributionsmentioning

confidence: 99%

“…Furthermore, the design principles include measures of anomalies in the correspondence between symbols of the visual notation and the semantic constructs they represent. Therefore it can be measured whether a visual notation fulfills the requirements of a notational system according to Goodman's theory of symbols [23].…”

Section: Visual Notations For Human Cognitionmentioning

confidence: 99%

“…Semiotic clarity relates to the correspondence between symbols and their referent concepts [43], there must be a one-to-one correspondence for a visual notation to satisfy the requirements of a notational system [23,43]. If there is no one-to-one correspondence between semantic constructs and visual symbols, one of the following four anomalies can occur: symbol redundancy, symbol overload, symbol excess or symbol deficit [43].…”

Section: Semiotic Claritymentioning

confidence: 99%

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Visual notations for viewing RDF constraints with UnSHACLed

Lieber

Meester

Heyvaert

et al. 2022

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The quality of knowledge graphs can be assessed by a validation against specified constraints, typically use-case specific and modeled by human users in a manual fashion. Visualizations can improve the modeling process as they are specifically designed for human information processing, possibly leading to more accurate constraints, and in turn higher quality knowledge graphs. However, it is currently unknown how such visualizations support users when viewing RDF constraints as no scientific evidence for the visualizations’ effectiveness is provided. Furthermore, some of the existing tools are likely suboptimal, as they lack support for edit operations or common constraints types. To establish a baseline, we have defined visual notations to represent RDF constraints and implemented them in UnSHACLed, a tool that is independent of a concrete RDF constraint language. In this paper, we (i) present two visual notations that support all SHACL core constraints, built upon the commonly used visualizations VOWL and UML, (ii) analyze both notations based on cognitive effective design principles, (iii) perform a comparative user study between both visual notations, and (iv) present our open source tool UnSHACLed incorporating our efforts. Users were presented RDF constraints in both visual notations and had to answer questions based on visualization task taxonomies. Although no statistical significant difference in mean error rates was observed, all study participants preferred ShapeVOWL in a self assessment to answer RDF constraint-related questions. Furthermore, ShapeVOWL adheres to more cognitive effective design principles according to our performed comparison. Study participants argued that the increased visual features of ShapeVOWL made it easier to spot constraints, but a list of constraints – as in ShapeUML – is easier to read. However, also that more deviations from the strict UML specification and introduction of more visual features can improve ShapeUML. From these findings we conclude that ShapeVOWL has a higher potential to represent RDF constraints more effective compared to ShapeUML. But also that the clear and efficient text encoding of ShapeUML can be improved with visual features. A one-size-fits-all approach to RDF constraint visualization and editing will be insufficient. Therefore, to support different audiences and use cases, user interfaces of RDF constraint editors need to support different visual notations.

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Section: Discussionmentioning

confidence: 99%