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Abstract

This documents presents Juma, a visual representation based on the block metaphor paradigm.

1. The Jigsaw Puzzles for Representing Mappings (Juma) approach

Juma, jigsaw puzzles for representing mappings, is a method based on the block (or jigsaw) metaphor. In this metaphor, concepts are represented as blocks that can only be combined with other compatible blocks. The block metaphor targets different types of users, allowing them to focus on the logic instead of the language’s syntax.

We have applied Juma to the R2RML mapping language (see publications 1 and 2). A screenshot of the tool can be seen in Figure 1.

Juma applied to R2RML mappings

Figure 1: Juma applied to R2RML mappings
A second implementation of the method is available. This implementation offers a higher level of abstraction, being able to generate R2RML and SML mappings, called Juma Uplift (see publications 3 and 5).
Juma Uplift

Figure 2: Juma Uplift

2. Video

Juma R2RML
Juma Uplift

3. Get access

Juma R2RML is available at Juma R2RML.

Juma Uplift is available at Juma Uplift.

For more information about the applications, please contact the authors.

4. Publications

  1. Juma: an Editor that Uses a Block Metaphor to Facilitate the Creation and Editing of R2RML Mappings.
    Ademar Crotti Junior, Christophe Debruyne and D O'Sullivan.
    In: Proceedings of the 14th Extended Semantic Web Conference: Posters and Demos, ESWC 2017.
  2. Using a Block Metaphor for Representing R2RML Mappings.
    Ademar Crotti Junior, Christophe Debruyne and Declan O'Sullivan.
    In: Proceedings of the 3rd International Workshop on Visualization and Interaction for Ontologies and Linked Data co-located with the 16th International Semantic Web Conference (VOILA@ISWC 2017).
  3. Juma Uplift: Using a Block Metaphor for Representing Uplift Mappings.
    Ademar Crotti Junior, Christophe Debruyne and Declan O'Sullivan.
    In: Proceedings of the 12th IEEE International Conference on Semantic Computing, ICSC 2018.
  4. An Editor that Uses a Block Metaphor for Representing Semantic Mappings in Linked Data.
    Ademar Crotti Junior, Christophe Debruyne and Declan O'Sullivan.
    In: Proceedings of the 15th Extended Semantic Web Conference: Posters and Demos, ESWC 2018.
  5. On the Mental Workload Assessment of Uplift Mapping Representations in Linked Data.
    Ademar Crotti Junior, Christophe Debruyne, Luca Longo and Declan O'Sullivan.
    In: Human Mental Workload: Models and Applications. H-WORKLOAD 2018.

5. Acknowledgments

This study is supported by CNPQ, National Counsel of Technological and Scientific Development – Brazil and the Science Foundation Ireland ADAPT Centre for Digital Content Technology (Grant 13/RC/2106).

6. References

[R2RML]
Souripriya Das; Seema Sundara; Richard Cyganiak. W3C. R2RML: RDB to RDF Mapping Language. 27 September 2012. W3C Recommendation. URL: http://www.w3.org/TR/r2rml/