Skip to main content
SpringerLink
Log in

Aesthetic Knowledge Diagrams: Bridging Understanding and Communication

  • Chapter
  • First Online:
Knowledge Management, Arts, and Humanities

Part of the book series: Knowledge Management and Organizational Learning ((IAKM,volume 7))

Abstract

Knowledge diagrams represent all substantial aspects of information involved in designing, codifying and representing company or domain knowledge assets. The chapter considers not only design but also the use of such maps including but not limited to facilitation of learning; eliciting, capturing, archiving and using expert knowledge; planning instruction; assessment of deep understandings; research planning; collaborative knowledge modelling; creation of knowledge portfolios; curriculum design; e-learning; and administrative and strategic planning and monitoring. Knowledge diagrams belong to the multidisciplinary fields of knowledge engineering (KE) and knowledge management (KM), bringing in concepts and methods from several computer science domains such as artificial intelligence, databases, expert systems, decision support systems and information systems. KE is strongly related to cognitive and social sciences and socio-cognitive engineering, where knowledge is considered to be produced by humans and structured according to mutual understanding of how human reasoning and logic work. Currently, KE is related to the construction of shared conceptual frameworks, often presented visually as knowledge diagrams. The chapter describes cognitive aspects of knowledge diagram design, using ideas coined by Gestalt psychology, involving good form and aesthetic perception. It is aimed at all researchers and practitioners interested in the use of knowledge diagrams, as outlined above.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alavi, M., & Leidner, D. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136.

    Article  Google Scholar 

  • Andersson, B., Bergholtz, M., Edirisuriya, A., Ilayperuma, T., Johannesson, P., Gordijn, J., et al. (2006). Towards a reference ontology for business models. Lecture Notes in Computer Science, 4215, 482–496.

    Article  Google Scholar 

  • Battista, A. D., Eades, P., Tamassia, R., & Tollis, I. (1999). Graph drawing: Algorithms for the visualization of graphs. Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Blackwell, A., & Engelhardt, Y. (2002). A meta-taxonomy for diagram research. In M. Anderson, B. Meyer, & P. Olivier (Eds.), Diagrammatic representation and reasoning (pp. 47–64). New York: Springer.

    Chapter  Google Scholar 

  • Bolotnikova, E., Gavrilova, T., & Gorovoy, V. (2011). To one method of ontology evaluation. International Journal of Computer and Systems Sciences, 50(3), 448–461.

    Article  Google Scholar 

  • Börner, K. (2011). Plug-and-play macroscopes. Communications of the ACM, 54(3), 60–69.

    Article  Google Scholar 

  • Börner, K., & Chen, C. (2001). Visual interfaces to digital libraries - its past, present, and future. In Proceedings of the 1st ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL’01) (pp. 482–485), JCDL workshop.

    Google Scholar 

  • Boyack, K., & Klavans, R. (2014). Creation of a highly detailed, dynamic, global model and map of science. Journal of the Association for Information Science and Technology, 65(4), 670–685.

    Article  Google Scholar 

  • Buergi, P., & Roos, J. (2003). Images of strategy. European Management Journal, 21(1), 69–78.

    Article  Google Scholar 

  • Cawthon, N., & Moere, A. (2007). The effect of aesthetic on the usability of data visualization. In Information visualization, IV’07, IEEE 11th international conference, 2007 (pp. 637–648).

    Google Scholar 

  • Chen, C. (2005). Top 10 unresolved information visualization problems. IEEE Computer Graphics and Applications, 25(4), 12–16.

    Article  Google Scholar 

  • Dettmer, H. W. (1997). Goldratt’s theory of constraints: A systems approach to continuous improvement. Milwaukee: ASQ Quality Press.

    Google Scholar 

  • Dicheva, D., Sosnovsky, S., Gavrilova, T., & Brusilovsky, P. (2005). Ontological web portal for educational ontologies. SW-EL’05: Applications of semantic web technologies for e-Learning (pp. 19–11).

    Google Scholar 

  • Dörk, M., Williamson, C., & Carpendale, S. (2009). Towards visual web search: Interactive query formulation and search result visualization. Madrid: WSSP.

    Google Scholar 

  • Eisenstadt, M., Domingue, J., Rajan, T., & Motta, E. (1990). Visual knowledge engineering. IEEE Transactions on Software Engineering, 16(10), 1164–1177.

    Article  Google Scholar 

  • Eppler, M. (2003). The image of insight: The use of visual metaphors in the communication of knowledge. Proceedings of I-KNOW, 3, 2–4.

    Google Scholar 

  • Eppler, M. (2008). A process-based classification of knowledge maps and application examples. Knowledge and Process Management, 15(1), 59–71.

    Article  Google Scholar 

  • Eppler, M., & Burkhard, R. (2005). Knowledge visualization. In D. G. Schwartz (Ed.), Encyclopedia of knowledge management (pp. 551–560). Hershey, PA: IGI.

    Google Scholar 

  • Eppler, M., & Burkhard, R. (2007). Visual representations in knowledge management: Framework and cases. Journal of Knowledge Management, 11(4), 112–122.

    Article  Google Scholar 

  • Eppler, M., & Jianxin, G. (2008). Communicating with diagrams: How intuitive and cross-cultural are business graphics? Euro Asia Journal of Management, 18(35), 3–22.

    Google Scholar 

  • Eppler, M., Hoffmann, F., & Bresciani, S. (2011). New business models through collaborative idea generation. International Journal of Innovation Management, 15(6), 1323–1341.

    Article  Google Scholar 

  • Few, S. (2006). Information dashboard design. Toronto, ON: O’Reilly Media.

    Google Scholar 

  • Frank, U. (2002). Multi-perspective enterprise modeling (Memo). Conceptual framework and modeling languages. In Proceedings of Hawaii International Conference on System Sciences (HICSS) (pp. 1258–1267).

    Google Scholar 

  • Gavrilova, T. (2003). Ontological approach to knowledge management in the development of corporate information systems. Journal News of Artificial Intelligence, 2, 2003.

    Google Scholar 

  • Gavrilova, T. (2010). Orchestrating ontologies for courseware design. In A. Tzanavari & N. Tsapatsoulis (Eds.), Affective, interactive and cognitive methods for E-learning design: Creating an optimal education experience (pp. 155–172). Hershey, PA: IGI Global.

    Chapter  Google Scholar 

  • Gavrilova, T., & Voinov, A. (1998). Work in progress: Visual specification of knowledge bases. In A. Pasqual del Pobil, J. Mira, & M. Ali (Eds.), Tasks and methods in applied artificial intelligence (Vol. 1416, pp. 717–726). Berlin: Springer.

    Chapter  Google Scholar 

  • Gibson, J. (2014). The ecological approach to visual perception (Classic ed.). Routledge: Taylor & Francis.

    Google Scholar 

  • Govareshki, M., Hosseini, S., & Taghinejad, R. (2017). Use of knowledge maps in collaborative networks management (case study: SSFR company). International Journal of Computer Science and Network Security, 17(9), 21.

    Google Scholar 

  • Grigoriev, L., & Kudryavtsev, D. (2011). Ontology-based business architecture engineering framework. Frontiers in Artificial Intelligence and Applications, 231, 233–252.

    Google Scholar 

  • Gruninger, M., & Fox, M. (1995). Methodology for the design and evaluation of ontologies. In Proceedings of IJCAI 1995, Workshop on basic ontological issues in knowledge sharing, Montreal (pp. 1–10).

    Google Scholar 

  • Guizzardi G., Pires L., van Sinderen M. (2006). Ontology-based evaluation and design of domain-specific visual modeling languages. Advances in information systems development. Springer, Boston, MA. 217–228.

    Google Scholar 

  • Harel D., & Rumpe B. (2000). Modeling languages: Syntax, semantics and all that stuff, Part I: The basic stuff. Technical report.

    Google Scholar 

  • Heidari, F., Loucopoulos, P., Brazier, F., & Barjis, J. (2013). A meta-meta-model for seven business process modeling languages. In Proceedings of 15th conference on business informatics (CBI) (pp. 216–221).

    Google Scholar 

  • Herman, B., Melanon, G., & Marshall, M. (2000). Graph visualization and navigation in information visualization: A survey. IEEE Transactions on Visualization and Computer Graphics, 6(1), 24–43.

    Article  Google Scholar 

  • Herrmann, C. S., & Bosch, V. (2001). Gestalt perception modulates early visual processing. Neuroreport, 12(5), 901–904.

    Article  Google Scholar 

  • Hinkelmann, K., Gerber, A., Karagiannis, D., Thoenssen, B., van der Merwe, A., & Woitsch, R. (2015). A new paradigm for the continuous alignment of business and IT: Combining enterprise architecture modelling and enterprise ontology. Computers in Industry., 79, 77–86.

    Article  Google Scholar 

  • Huff, A. (1990). Mapping strategic thought. Hoboken: Wiley.

    Google Scholar 

  • Karagiannis, D., & Höfferer, P. (2006). Metamodeling as an integration concept. In Software and data technologies (pp. 37–50). Berlin: Springer.

    Google Scholar 

  • Kingston, J., & Macintosh, A. (2000). Knowledge management through multi-perspective modelling: Representing and distributing organizational memory. Knowledge-Based Systems, 13(2), 121–131.

    Article  Google Scholar 

  • Kosslyn, S. (2006). Graph design for the eye and the mind. New York, NY: Oxford University Press.

    Book  Google Scholar 

  • Koznov D. (2011). Process model of DSM solution development and evolution for small and medium-sized software companies. In Proceedings of 15th IEEE International Enterprise Distributed Object Computing Workshop, Helsinki (EDOC 2011) (pp. 85–92).

    Google Scholar 

  • Kudryavtsev, D., & Gavrilova, T. (2011). Diagrammatic knowledge modeling for managers: Ontology-based approach. In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (pp. 386–389).

    Google Scholar 

  • Kudryavtsev, D., & Gavrilova, T. (2017). From anarchy to system: A novel classification of visual knowledge codification techniques. Knowledge and Process Management, 24(1), 3–13.

    Article  Google Scholar 

  • Lengler R., Eppler M. (2007). Towards a periodic table of visualization methods for management. In Proceedings of the Conference on Graphics and Visualization in Engineering (pp. 1–6).

    Google Scholar 

  • Lohse, G., Biolsi, K., Walker, N., & Rueter, H. (1994). A classification of visual representations. Communications of the ACM, 37(12), 36–49.

    Article  Google Scholar 

  • Luchins, A., & Luchins, E. (1982). An introduction to the origins of Wertheimer’s Gestalt psychology. Gestalt Theory, 4(3–4), 145–171.

    Google Scholar 

  • Manovich, L. (2009, March). Cultural analytics: Visualising cultural patterns in the era of “more media”. Domus.

    Google Scholar 

  • Mayer, R., Painter, K., & deWitte, P. (1992). IDEF family of methods for concurrent engineering and business re-engineering applications. College Station, TX: Knowledge Based Systems.

    Google Scholar 

  • Miller, G. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81.

    Article  Google Scholar 

  • Musen, M. (1992). Dimensions of knowledge sharing and reuse. Computers and Biomedical Research, 25(5), 435–467.

    Article  Google Scholar 

  • Mutschke, P., Scharnhorst, A., Belkin, N., Skupin, A., & Mayr, P. (2017). Guest editors’ introduction to the special issue on knowledge maps and information retrieval. (KMIR). International Journal on Digital Libraries, 18(1), 1. https://doi.org/10.1007/s00799-016-0204-4

    Article  Google Scholar 

  • Nicolini, D. (2007). Studying visual practices in construction. Building Research & Information., 35, 576–580.

    Article  Google Scholar 

  • Ren, Y., Parvizi, A., Mellish, C., Pan, J., Van Deemter, K., & Stevens, R. (2014). Towards competency question-driven ontology authoring. In The semantic web: Trends and challenges (pp. 752–767). New York: Springer.

    Chapter  Google Scholar 

  • Rumbaugh, J., Jacobson, I., & Booch, G. (2004). Unified modeling language reference manual. Boston, MA: Pearson Higher Education.

    Google Scholar 

  • Sandkuhl, K. (2014). Knowledge reuse: Survey of existing techniques and classification approach. In Business intelligence (Vol. 205, pp. 126–148). Berlin: Springer.

    Chapter  Google Scholar 

  • Santucci, G. (2013). Visual analytics and information retrieval. In M. Agosti et al. (Eds.), Information retrieval meets information visualization (pp. 116–131). New York: Springer.

    Chapter  Google Scholar 

  • Sarrafzadeh, B., Vtyurina, A., Lank, E., & Vechtomova, O. (2016). Knowledge graphs versus hierarchies: An analysis of user behaviours and perspectives in information seeking. In Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval (pp. 91–100).

    Google Scholar 

  • Shadbolt, N., & Milton, N. (1999). From knowledge engineering to knowledge management. British Journal of Management, 10(4), 309–322.

    Article  Google Scholar 

  • Shiffrin, R., & Boerner, K. (2004). Mapping knowledge domains. Proceedings of the National Academy of Sciences of the USA, 101(1), 5183–5185.

    Article  Google Scholar 

  • Skupin, A. (2004). The world of geography: Visualizing a knowledge domain with cartographic means. Proceedings of the National Academy of Sciences of the USA, 101(1), 5274–5278.

    Article  Google Scholar 

  • Strakhovich, E. (2014). Ontological engineering in education: Tools for knowledge transfer and knowledge assessment. In Advanced learning technologies (ICALT), IEEE 14th International Conference (pp. 714–715).

    Google Scholar 

  • Studer, R., Benjamins, V. R., & Fensel, D. (1998). Knowledge engineering: Principles and methods. Data and Knowledge Engineering, 25(1), 161–198.

    Article  Google Scholar 

  • Sun, D., & Wong, K. (2005). On evaluating the layout of UML class diagrams for program comprehension. In Program comprehension, IWPC, Proceedings, IEEE 13th International Workshop (pp. 317–326).

    Google Scholar 

  • Tangherlini, T. (2013). The folklore macroscope: Challenges for a computational folkloristics. The 34th Archer Taylor memorial lecture. Western Folklore, 72(1), 7–27.

    Google Scholar 

  • The Open Group. (2012). ArchiMate 2.1 specification. The Open Group Publications catalog, 2012–2013. Accessed February 23, 2016, from http://pubs.opengroup.org/architecture/archimate2-doc/

  • van Vijk, J. (2006). Views on visualization. IEEE Transaction on Visualization and Computer Graphics, 12, 421–432.

    Article  Google Scholar 

  • Wei, F., Liu, S., Song, Y., Pan, S., Zhou, M., Qian, W., et al. (2010). TIARA: A visual exploratory text analytic system. In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’10) (pp. 153–162).

    Google Scholar 

  • Wells, D. (1990). Are these the most beautiful? The Mathematical Intelligencer, 12, 37–41. https://doi.org/10.1007/BF03024015.

    Article  Google Scholar 

  • Werthheimer, M. (1945). Productive thinking. New York: Harper Collins.

    Google Scholar 

  • Wielinga, B., Sandberg, J., & Schreiber, G. (1997). Methods and techniques for knowledge management: What has knowledge engineering to offer? Expert Systems with Applications, 13(1), 73–84.

    Article  Google Scholar 

  • Yudelson, M., Gavrilova, T., & Brusilovsky, P. (2005). Towards user modeling meta-ontology. In International conference on user modeling, Springer, Berlin (pp. 448–452).

    Google Scholar 

  • Zachman, J. (2003). The Zachman framework for enterprise architecture: A primer for enterprise engineering and manufacturing. Monument, CO: Zachman International.

    Google Scholar 

Download references

Acknowledgments

This research was partially supported financially by Russian Science Foundation grant (project No. 17-07-00228 А).

Author information

Authors and Affiliations

  1. Graduate School of Management, Saint-Petersburg University, Saint-Petersburg, Russia

    Tatiana Gavrilova, Dmitry Kudryavtsev & Elvira Grinberg

Authors
  1. Tatiana Gavrilova
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dmitry Kudryavtsev
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Elvira Grinberg
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Dept. Management & InfoTech, International Burch University, Sarajevo, Bosnia and Herzegovina

    Meliha Handzic

  2. Department of European and Mediterranean Cultures, Environment and Cultural Heritage (DICEM), University of Basilicata, Matera, Italy

    Daniela Carlucci

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gavrilova, T., Kudryavtsev, D., Grinberg, E. (2019). Aesthetic Knowledge Diagrams: Bridging Understanding and Communication. In: Handzic, M., Carlucci, D. (eds) Knowledge Management, Arts, and Humanities. Knowledge Management and Organizational Learning, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-030-10922-6_6

Download citation

Publish with us

Policies and ethics

Search

Navigation