Visual Notations for Viewing and Editing RDF Constraints with UnSHACLed

Tracking #: 2680-3894

This paper is currently under review
Authors: 
Sven Lieber
Ben De Meester
Pieter Heyvaert1
Femke Brückmann
Ruben Wambacq
Erik Mannens
Ruben Verborgh
Anastasia Dimou

Responsible editor: 
Karl Hammar

Submission type: 
Full Paper
Abstract: 
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 view and edit 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 about it. Although no statistical significant difference in mean error rates was observed, a majority of participants made less errors with ShapeVOWL and all preferred ShapeVOWL in a self-assessment to answer RDF constraint-related questions. 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 the potential for more user acceptance, 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. In the future, we plan to incorporate different editing approaches and non-linear workflows into UnSHACLed to improve its editing capabilities. Further research can built upon our findings and evaluate a ShapeUML variant with more visual features or investigate a mapping from both visual notations to ShEx constraints.
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Under Review