research-article

Perceptual factors in knowledge map visual design

Authors:

Tatiana Gavrilova,

Artem Alsufyev,

Margarita GladkovaAuthors Info & Claims

i-KNOW '15: Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business

Article No.: 39, Pages 1 - 4

https://doi.org/10.1145/2809563.2809599

Published: 21 October 2015 Publication History

Abstract

Knowledge visualization is an effective instrument for knowledge creation, acquisition and transfer. Knowledge maps are the most common knowledge visualization techniques, specifically, mind maps. Managers frequently use these instruments in their work for business analytics purposes, but the preparation of such maps must follow several laws in order to make them effective.

The goal of the current paper is to develop the methodology and some practical recommendations how to design knowledge maps that can be used for knowledge codification, transfer, sharing and dissemination in companies. The paper also evaluates proposed visualization laws for creating knowledge maps based on the principles of cognitive psychology. The knowledge maps visual design methodology is based on perceptual factors and include the law of pragnanz (the law of good shape) and the law of parsimony (the Ockham's razor principle). The results were obtained through the qualitative analysis of group mind maps of 48 top-managers of Russian companies. We may assert that for the knowledge map to be effective in knowledge codification, transfer, sharing and dissemination in companies it should follow laws of good shape, parsimony and tips related to knowledge maps design.

The proposed framework of visualization laws is important for many reasons. It is targeted at the development of methodologies and related technologies that can scaffold the process of knowledge structuring and transfer for managers' business analytics tasks and decision-making. The paper contributes to managerial practice by describing the practical recommendations for effective visual knowledge structuring.

References

[1]

Bauer M. I., Johnson-Laird P. N. 1993. How diagrams can improve reasoning. Psychological Review. 4, 6, pp. 72--378.

[2]

Buzan T. 2003. The Mind Map Book. London: BBC Active.

[3]

Card K. S., Mackinlay J. D., Shneiderman B. 1999. Readings in Information Visualization, Using Vision to Think. San Francisco: Morgan Kaufmann.

Digital Library

[4]

Eppler M. J. 2006. A comparison between concept maps, mind maps, conceptual diagrams, and visual metaphors as complementary tools for knowledge construction and sharing. Information Visualization. 5, 3, pp. 202--210.

[5]

Eppler M. J., Burkhard R. A. 2004. Knowledge Visualization-Towards a New Discipline and its Fields of Application. ICA Working Paper 2/2004. University of Lugano.

[6]

Eppler M. J., Burkhard R. A. 2007. Visual representations in knowledge management: Framework and cases. Journal of Knowledge Management. 11, 4, pp. 112--122.

[7]

Eppler M. J., Hoffmann F., Bresciani S. 2011. New Business Models Through Collaborative Idea Generation. International Journal of Innovation Management. 6, 15, pp. 1323--1341.

[8]

Eppler M. J., Platts K. 2009. Visual Strategizing: The Systematic Use of Visualization in the Strategic Planning Process. Long Range Planning. 2, pp. 42--74.

[9]

Gavrilova T. 2010. Orchestrating Ontologies for Courseware Design. In Affective, Interactive and Cognitive Methods for E-Learning Design: Creating an Optimal Education Experience, Eds. A. Tzanavari, N. Tsapatsoulis. Hershey, PA: IGI Global, pp. 155--172.

[10]

Glenberg A. M., Langston W. E. 1992. Comprehension of illustrated text: Pictures help to build mental models. Journal of Memory and Language. 31,1, pp. 129--151.

[11]

Larkin J. H., Simon H. A. 1987. Why a diagram is (sometimes) worth ten thousand words. Cognitive Science. 11, 1, pp. 65--100.

[12]

Lurie N. H., Mason C. H. 2007. Visual representation: Implications for decision making. Journal of Marketing. 71, pp. 160--177.

[13]

Mason K., Spring M. 2011. The Sites and Practices of Business Models. Industrial Marketing Management. 40, 6, pp. 1032--1041.

[14]

Mento A. J., Martinelli P., Jones R. M. 1999. Mind mapping in executive education: Applications and outcomes. Journal of Management Development. 18, 4, pp. 390--416.

[15]

Schneiderman B. 1996. The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings of the IEEE Symposium on Visual Languages. IEEE Computer Society Press, pp. 336--343.

Digital Library

[16]

Tufte E. R. 1991. Envisioning information. Optometry & Vision Science. 68, 4, pp. 322--324.

[17]

Tversky B. 2005. Visuospatial reasoning. In The Cambridge Handbook of Thinking and Reasoning, Eds. K. Holyoak, R. G. Morrison. New York: Cambridge University Press, pp. 209--240.

[18]

Vessey I. 1991. Cognitive fit: A theory-based analysis of the graphs versus tables literature. Decision Sciences. 22, pp. 219--241.

[19]

Ware C. 2010. Visual Thinking for Design. Kaufmann Morgan

Digital Library

Cited By

Diván MSánchez-Reynoso M(2022)Towards a Distributed Record of Measurement Adapters Powered by Blockchain TechnologyTransformations Through Blockchain Technology10.1007/978-3-030-93344-9_5(113-135)Online publication date: 8-Mar-2022
https://doi.org/10.1007/978-3-030-93344-9_5
Menaouer BMohammed SNada M(2020)Towards a Model to Improve Boolean Knowledge Mapping by Using Text Mining and Its ApplicationsInternational Journal of Information Retrieval Research10.4018/IJIRR.202007010310:3(35-56)Online publication date: 1-Jul-2020
https://doi.org/10.4018/IJIRR.2020070103
Sensuse DDiar ALusa SElisabeth D(2020)An Overview of Knowledge Mapping in Digital Business Industry: A Systematic Literature Review2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI)10.23919/EECSI50503.2020.9251878(216-221)Online publication date: 1-Oct-2020
https://doi.org/10.23919/EECSI50503.2020.9251878
Show More Cited By

Index Terms

Perceptual factors in knowledge map visual design
1. Human-centered computing
  1. Visualization

Recommendations

Knowledge maps and organisations: an overview and interpretation

The 'knowledge map' is a relatively new Knowledge Management (KM) tool. Yet the applications of knowledge maps in the organisational context have been insufficiently developed. This paper conducts a critical literature review and offers an alternative ...
Visualization Based on Concept Maps: An Efficient Way to Knowledge Sharing and Knowledge Discovery in E-science Environment
FSKD '09: Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02

Knowledge visualization is a fascinating study field that has received more attention. In e-Science environment, people pay more attention to the scientific visualization and data visualization. Visualization about information exchange and knowledge ...
The Using of Knowledge Visualization Tools in E-science Environment Take Concept Maps for Example
CASE '09: Proceedings of the 2009 IITA International Conference on Control, Automation and Systems Engineering (case 2009)

In e-Science environment, people pay more attention to the scientific visualization and data visualization. Visualization about information exchange and knowledge sharing is rare to be mentioned. Knowledge sharing is an important part in e-Science ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

i-KNOW '15: Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business

October 2015

314 pages

ISBN:9781450337212

DOI:10.1145/2809563

General Chairs:
Stefanie Lindstaedt
Know-Center Graz, Austria & Graz University of Technology
,
Tobias Ley
Tallin University, Estonia
,
Harald Sack
Hasso-Platter Institute for IT Systems Engineering, Germany

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 October 2015

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Russian Science Foundation

Conference

i-KNOW '15

i-KNOW '15: 15th International Conference on Knowledge Technologies and Data-Driven Business

October 21 - 22, 2015

Graz, Austria

Acceptance Rates

i-KNOW '15 Paper Acceptance Rate 25 of 78 submissions, 32%;

Overall Acceptance Rate 77 of 238 submissions, 32%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
208
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)2

Reflects downloads up to 21 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Diván MSánchez-Reynoso M(2022)Towards a Distributed Record of Measurement Adapters Powered by Blockchain TechnologyTransformations Through Blockchain Technology10.1007/978-3-030-93344-9_5(113-135)Online publication date: 8-Mar-2022
https://doi.org/10.1007/978-3-030-93344-9_5
Menaouer BMohammed SNada M(2020)Towards a Model to Improve Boolean Knowledge Mapping by Using Text Mining and Its ApplicationsInternational Journal of Information Retrieval Research10.4018/IJIRR.202007010310:3(35-56)Online publication date: 1-Jul-2020
https://doi.org/10.4018/IJIRR.2020070103
Sensuse DDiar ALusa SElisabeth D(2020)An Overview of Knowledge Mapping in Digital Business Industry: A Systematic Literature Review2020 7th International Conference on Electrical Engineering, Computer Sciences and Informatics (EECSI)10.23919/EECSI50503.2020.9251878(216-221)Online publication date: 1-Oct-2020
https://doi.org/10.23919/EECSI50503.2020.9251878
Renaud Kvan Biljon Jde Villiers CSmuts H(2019)A Framework to Maximise the Communicative Power of Knowledge VisualisationsProceedings of the South African Institute of Computer Scientists and Information Technologists 201910.1145/3351108.3351111(1-10)Online publication date: 17-Sep-2019
https://dl.acm.org/doi/10.1145/3351108.3351111
Menaouer BNada M(2019)The relationship between knowledge mapping and the open innovation process: the case of education systemArtificial Intelligence for Engineering Design, Analysis and Manufacturing10.1017/S089006041900032534:1(17-29)Online publication date: 28-Nov-2019
https://doi.org/10.1017/S0890060419000325
renaud kvan Biljon JMasinde M(2017)Charting the path towards effective knowledge visualisationsProceedings of the South African Institute of Computer Scientists and Information Technologists10.1145/3129416.3129421(1-10)Online publication date: 26-Sep-2017
https://dl.acm.org/doi/10.1145/3129416.3129421

View Options

Login options

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

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents