skip to main content
10.1145/3550355.3552412acmconferencesArticle/Chapter ViewAbstractPublication PagesmodelsConference Proceedingsconference-collections

Advanced visualization and interaction in GLSP-based web modeling: realizing semantic zoom and off-screen elements

Published:24 October 2022Publication History

ABSTRACT

Conceptual modeling is widely adopted in industrial practices, e.g., process, software, and systems modeling. Providing adequate and usable modeling tools is essential for the efficient adoption of modeling. Metamodeling platforms provide a rich set of functionalities and maturely realize state-of-the-art modeling tools. However, despite their maturity and stability, most of these platforms only slowly - if at all - leverage the full extent of functionalities and the ease of exploitation and integration enabled by web technologies. With the Graphical Language Server Protocol (GLSP), it is now possible to realize much richer, advanced opportunities for visualizing and interacting with conceptual models. This paper presents a concept and a prototypical implementation of two advanced model visualization and interaction functionalities with the Eclipse GLSP platform: Semantic Zoom and Off-Screen Elements. We believe such advanced functionalities pave the way for a prosperous modeling future and spark innovation in modeling tool development.

References

  1. Lyn Bartram, Albert Ho, John Dill, and Frank Henigman. 1995. The continuous zoom: A constrained fisheye technique for viewing and navigating large information spaces. In Proceedings of the 8th annual ACM symposium on User interface and software technology. 207--215.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Patrick Baudisch and Ruth Rosenholtz. 2003. Halo: a technique for visualizing off-screen objects. In Proceedings of the SIGCHI conference on Human factors in computing systems. 481--488.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Dominik Bork, Antonio Garmendia, and Manuel Wimmer. 2020. Towards a Multi-Objective Modularization Approach for Entity-Relationship Models. In ER Forum, Demo and Posters 2020 co-located with 39th International Conference on Conceptual Modeling (ER 2020), Vienna, Austria, November 3--6, 2020 (CEUR Workshop Proceedings, Vol. 2716), Judith Michael and Victoria Torres (Eds.). CEURWS.org, 45--58.Google ScholarGoogle Scholar
  4. Dominik Bork, Dimitris Karagiannis, and Benedikt Pittl. 2018. Systematic analysis and evaluation of visual conceptual modeling language notations. In 2018 12th International Conference on Research Challenges in Information Science (RCIS). IEEE, 1--11.Google ScholarGoogle ScholarCross RefCross Ref
  5. Dominik Bork and Ben Roelens. 2021. A technique for evaluating and improving the semantic transparency of modeling language notations. Softw. Syst. Model. 20, 4 (2021), 939--963.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Hendrik Bünder. 2019. Decoupling Language and Editor-The Impact of the Language Server Protocol on Textual Domain-Specific Languages.. In MODELSWARD. 129--140.Google ScholarGoogle Scholar
  7. Giuliano De Carlo, Philip Langer, and Dominik Bork. 2022. Rethinking Model Representation - A Taxonomy of Advanced Information Visualization in Conceptual Modeling. In International Conference on Conceptual Modeling (ER'22).Google ScholarGoogle Scholar
  8. William C Donelson. 1978. Spatial management of information. In Proceedings of the 5th annual conference on Computer graphics and interactive techniques. 203--209.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Dustin Dunsmuir. 2009. Selective Semantic Zoom of a Document Collection. Available at, (Oct. 30, 2009) (2009), 1--9.Google ScholarGoogle Scholar
  10. Eclipse Foundation. [n. d.]. Eclipse Graphical Language Server Platform. https://github.com/eclipse-glsp/glsp. Accessed: 10.05.2022.Google ScholarGoogle Scholar
  11. Ulrich Frank, Stefan Strecker, Peter Fettke, Jan Vom Brocke, Jörg Becker, and Elmar Sinz. 2014. The research field modeling business information systems. Bus. Inf. Syst. Eng. 6, 1 (2014), 39--43.Google ScholarGoogle ScholarCross RefCross Ref
  12. Mathias Frisch and Raimund Dachselt. 2013. Visualizing offscreen elements of node-link diagrams. Information Visualization 12, 2 (2013), 133--162.Google ScholarGoogle ScholarCross RefCross Ref
  13. Mathias Frisch, Raimund Dachselt, and Tobias Brückmann. 2008. Towards seamless semantic zooming techniques for UML diagrams. In 4th ACM Symposium on Software Visualization. 207--208.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. George W Furnas. 1986. Generalized fisheye views. Acm Sigchi Bulletin 17, 4 (1986), 16--23.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Giancarlo Guizzardi, Tiago Prince Sales, João Paulo A. Almeida, and Geert Poels. 2021. Automated conceptual model clustering: a relator-centric approach. Software and Systems Modeling (2021). Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Jens Gulden. 2016. Recommendations for Data Visualizations Based on Gestalt Patterns. In International Conference on Enterprise Systems, Gang Li and Yale Yu (Eds.). 168--177.Google ScholarGoogle Scholar
  17. Jens Gulden, Hajo A Reijers, J Grabis, and K Sandkuhl. 2015. Toward Advanced Visualization Techniques for Conceptual Modeling.. In CAiSE Forum. Citeseer, 33--40.Google ScholarGoogle Scholar
  18. Sean Gustafson, Patrick Baudisch, Carl Gutwin, and Pourang Irani. 2008. Wedge: clutter-free visualization of off-screen locations. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 787--796.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Sean G Gustafson and Pourang P Irani. 2007. Comparing visualizations for tracking off-screen moving targets. In Extended Abstracts on Human Factors in Computing Systems. 2399--2404.Google ScholarGoogle Scholar
  20. Tan Kim Heok and Daut Daman. 2004. A review on level of detail. In Proceedings. International Conference on Computer Graphics, Imaging and Visualization, 2004. CGIV 2004. IEEE, 70--75.Google ScholarGoogle ScholarCross RefCross Ref
  21. Takeo Igarashi and Ken Hinckley. 2000. Speed-dependent automatic zooming for browsing large documents. In ACM symposium on User interface software and technology. 139--148.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Huzefa Kagdi and Jonathan I Maletic. 2007. Onion graphs for focus+ context views of UML class diagrams. In Int. Workshop on Visualizing Software for Understanding and Analysis. 80--87.Google ScholarGoogle ScholarCross RefCross Ref
  23. Banda KalyanaChakravarthy. 2008. Visualizing the MPI Programs: Using Continuous Semantic Zooming. (2008).Google ScholarGoogle Scholar
  24. A Chris Long, Brad Myers, Juan Casares, Scott Stevens, and Albert Corbett. 2004. Video Editing Using Lenses and Semantic Zooming. (2004).Google ScholarGoogle Scholar
  25. microsoftlspimpl [n.d.]. Microsoft language server protocol implementations. https://microsoft.github.io/language-server-protocol/implementors/servers/. Accessed: 23.04.2021.Google ScholarGoogle Scholar
  26. microsoftlspspec [n.d.]. Microsoft language server protocol specification. https://microsoft.github.io/language-server-protocol/specifications/specification-current/. Accessed: 23.04.2021.Google ScholarGoogle Scholar
  27. Daniel Moody. 1997. A multi-level architecture for representing enterprise data models. In International Conference on Conceptual Modeling. Springer, 184--197.Google ScholarGoogle ScholarCross RefCross Ref
  28. John Mylopoulos. 1992. Conceptual modelling and Telos. Conceptual modelling, databases, and CASE: An integrated view of information system development (1992), 49--68.Google ScholarGoogle Scholar
  29. Tom Owen, George Buchanan, Parisa Eslambochilar, and Fernando Loizides. 2010. Supporting early document navigation with semantic zooming. In International Conference on Asian Digital Libraries. Springer, 168--178.Google ScholarGoogle ScholarCross RefCross Ref
  30. Ken Perlin and David Fox. 1993. Pad: an alternative approach to the computer interface. In Proceedings of the 20th annual conference on Computer graphics and interactive techniques. 57--64.Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Parsa Pourali and Joanne M. Atlee. 2018. An Empirical Investigation to Understand the Difficulties and Challenges of Software Modellers When Using Modelling Tools. In Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2018, Andrzej Wasowski, Richard F. Paige, and Øystein Haugen (Eds.). ACM, 224--234. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Tobias Reinhard, Silvio Meier, and Martin Glinz. 2007. An improved fisheye zoom algorithm for visualizing and editing hierarchical models. In Second International Workshop on Requirements Engineering Visualization (REV 2007). IEEE, 9--9.Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Roberto Rodriguez-Echeverria, Javier Luis Cánovas Izquierdo, Manuel Wimmer, and Jordi Cabot. 2018. Towards a language server protocol infrastructure for graphical modeling. In Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems. 370--380.Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Ben Roelens and Dominik Bork. 2020. An evaluation of the intuitiveness of the PGA modeling language notation. In Enterprise, Business-Process and Information Systems Modeling. Springer, 395--410.Google ScholarGoogle Scholar
  35. Kurt Sandkuhl, Hans-Georg Fill, Stijn Hoppenbrouwers, John Krogstie, Florian Matthes, Andreas Opdahl, Gerhard Schwabe, Ömer Uludag, and Robert Winter. 2018. From Expert Discipline to Common Practice: A Vision and Research Agenda for Extending the Reach of Enterprise Modeling. Bus. Inf. Syst. Eng. 60, 1 (2018), 69--80.Google ScholarGoogle ScholarCross RefCross Ref
  36. George Schussel. 1995. Client/server past, present, and future. Formerly Available URL: http://news.dci.com/geos/dbsejava.htm (1995).Google ScholarGoogle Scholar
  37. Michael Stengel, Mathias Frisch, Sven Apel, Janet Feigenspan, Christian Kästner, and Raimund Dachselt. 2011. View infinity: a zoomable interface for feature-oriented software development. In Proceedings of the 33rd International Conference on Software Engineering. 1031--1033.Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Christian Tominski, James Abello, Frank Van Ham, and Heidrun Schumann. 2006. Fisheye tree views and lenses for graph visualization. In Tenth International Conference on Information Visualisation (IV'06). IEEE, 17--24.Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. YoungSeok Yoon and Brad A Myers. 2015. Semantic zooming of code change history. In 2015 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). IEEE, 95--99.Google ScholarGoogle ScholarCross RefCross Ref
  40. Polle T Zellweger, Jock D Mackinlay, Lance Good, Mark Stefik, and Patrick Baudisch. 2003. City lights: contextual views in minimal space. In CHI'03 extended abstracts on Human factors in computing systems. 838--839.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Advanced visualization and interaction in GLSP-based web modeling: realizing semantic zoom and off-screen elements

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        MODELS '22: Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems
        October 2022
        412 pages
        ISBN:9781450394666
        DOI:10.1145/3550355

        Copyright © 2022 Owner/Author

        This work is licensed under a Creative Commons Attribution International 4.0 License.

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 24 October 2022

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        MODELS '22 Paper Acceptance Rate35of125submissions,28%Overall Acceptance Rate118of382submissions,31%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader