Abstract
The use of visualizations to access and process enterprise data has been proposed as a boost to the usability of enterprise systems. Yet, novel user interfaces do not always yield the expected gains in performance. To realize the potential benefits from using a visual approach, it is important to examine the effectiveness of visualizations in a specific task context and to follow an iterative, evaluation-driven process for identifying and addressing shortcomings in their design and execution. In this paper, we present the results of a study examining the effectiveness of a visual interface called Association Map (AM) for exploring ternary associations of data versus a typical tabular interface from a popular enterprise system. This latest version of AM evolved from earlier versions that underwent similar evaluations and we discuss the design choices that were important for achieving user performance gains in accuracy and time-on-task compared to earlier versions and to table-based interfaces. Findings presented here help build the case for incorporating task-driven visual interfaces into traditional table-based representations used in enterprise systems to improve both the user experience and task-related outcomes. Furthermore, they provide insights for investigating the theoretical foundations behind what makes a visual interface work.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Babaian, T., Lucas, W., Chircu, A.M., Power, N.: Interactive visualizations for workplace tasks. In: Hammoudi, S., Maciaszek, L.A., Missikoff, M.M., Camp, O., Cordeiro, J. (eds.) ICEIS 2016. LNBIP, vol. 291, pp. 389–413. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62386-3_18
Babaian, T., Lucas, W., Chircu, A., Power, N.: Extending an association map to handle large data sets. In: Yamamoto, S. (ed.) HIMI 2017. LNCS, vol. 10273, pp. 3–21. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-58521-5_1
Barlow, T., Neville, P.: A comparison of 2-D visualizations of hierarchies. In: INFOVIS, p. 131. IEEE (2001)
Calisir, F., Calisir, F.: The relation of interface usability characteristics, perceived usefulness, and perceived ease of use to end-user satisfaction with enterprise resource planning (ERP) systems. Comput. Hum. Behav. 20, 505–515 (2004)
Cardinaels, E.: The interplay between cost accounting knowledge and presentation formats in cost-based decision-making. Acc. Organ. Soc. 33, 582–602 (2008)
Chang, R., et al.: Scalable and interactive visual analysis of financial wire transactions for fraud detection. Inf. Vis. 7, 63–76 (2008)
Deakins, J.: Unveiling the ERP Pain-O-Meter. https://www.cio.com/article/3253963/enterprise-resource-planning/unveiling-the-erp-pain-o-meter.html
Dilla, W.N., Raschke, R.L.: Data visualization for fraud detection: practice implications and a call for future research. Int. J. Acc. Inf. Syst. 16, 1–22 (2015)
Elting, L.S., Martin, C.G., Cantor, S.B., Rubenstein, E.B.: Influence of data display formats on physician investigators’ decisions to stop clinical trials: prospective trial with repeated measures. BMJ 318, 1527–1531 (1999)
Field, A.: Discovering Statistics Using IBM SPSS Statistics. SAGE, Thousand Oaks (2013)
Heer, J., Bostock, M., Ogievetsky, V.: A tour through the visualization zoo. Commun. ACM 53, 59 (2010)
Hevner, A., March, S., Park, J., Ram, S.: Design science in information systems research. MIS Q. 28, 75–105 (2004)
Kettelhut, V.V., Vanschooneveld, T.C., McClay, J.C., Mercer, D.F., Fruhling, A., Meza, J.L.: Empirical study on the impact of a tactical biosurveillance information visualization on users’ situational awareness. Mil. Med. 182, 322–329 (2017)
Kobsa, A.: User experiments with tree visualization systems. In: Proceedings of the IEEE Symposium on Information Visualization, pp. 9–16. IEEE Computer Society (2004)
Lambeck, C., Fohrholz, C., Leyh, C., Müller, R.: (Re-) Evaluating user interface aspects in ERP systems - an empirical user study. In: Proceedings of the 47th Hawaiian International Conference on System Sciences. IEEE Computer Society (2014)
McKendrick, J.: Enterprise software slows down digital transformation, survey suggests. https://www.zdnet.com/article/enterprise-software-is-the-biggest-roadblock-to-digital-transformation/
Munzner, T.: Visualization Analysis and Design. A K Peters/CRC Press, Boca Raton (2014)
Parks, N.E.: Testing & quantifying ERP usability. In: Proceedings of the 1st Annual Conference on Research in Information Technology, pp. 31–36. ACM (2012)
Patterson, R.E., et al.: A human cognition framework for information visualization. Comput. Graph. 42, 42–58 (2014)
Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24, 45–77 (2007)
Pike, W.A., Stasko, J., Chang, R., O′Connell, T.A.: The science of interaction. Inf. Vis. 8, 263–274 (2009)
Saket, B., Endert, A., Stasko, J.: Beyond usability and performance: a review of user experience-focused evaluations in visualization. In: Proceedings of the Sixth Workshop on Beyond Time and Errors on Novel Evaluation Methods for Visualization, pp. 133–142. ACM (2016)
Sedlmair, M., Isenberg, P., Baur, D., Butz, A.: Information visualization evaluation in large companies: challenges, experiences and recommendations. Inf. Vis. 10, 248–266 (2011)
Sedlmair, M., Bernhold, C., Herrscher, D., Boring, S., Butz, A.: MostVis: an interactive visualization supporting automotive engineers in MOST catalog exploration. In: Proceedings of the International Conference on Information Visualisation, pp. 173–182 (2009)
Stasko, J., Catrambone, R., Guzdial, M., Mcdonald, K.: An evaluation of space-filling information visualizations for depicting hierarchical structures. Int. J. Hum.-Comput. Stud. 53, 663–694 (2000)
Tarrell, A., Fruhling, A., Borgo, R., Forsell, C., Grinstein, G., Scholtz, J.: Toward visualization-specific heuristic evaluation. In: Proceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization, pp. 110–117. ACM (2014)
Toker, D., Conati, C., Steichen, B., Carenini, G.: Individual user characteristics and information visualization: connecting the dots through eye tracking. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 295–304. ACM (2013)
Vessey, I.: Cognitive fit: a theory-based analysis of the graphs versus tables literature*. Decis. Sci. 22, 219–240 (1991)
Ware, C.: Information Visualization: Perception for Design, 3rd edn. Morgan Kaufmann, Waltham (2012)
Ziemkiewicz, C., Crouser, R.J., Yauilla, A.R., Su, S.L., Ribarsky, W., Chang, R.: How locus of control influences compatibility with visualization style. In: 2011 IEEE Conference on Visual Analytics Science and Technology (VAST), pp. 81–90. IEEE (2011)
Ziemkiewicz, C., Kosara, R.: The shaping of information by visual metaphors. IEEE Trans. Vis. Comput. Graph. 14, 1269–1276 (2008)
Zimmerman, J., Forlizz, J., Evenson, S.: Research through design as a method for interaction design research in HCI. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 493–502. New York, NY (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Babaian, T., Lucas, W., Chircu, A. (2019). Mapping Data Associations in Enterprise Systems. In: Tulu, B., Djamasbi, S., Leroy, G. (eds) Extending the Boundaries of Design Science Theory and Practice. DESRIST 2019. Lecture Notes in Computer Science(), vol 11491. Springer, Cham. https://doi.org/10.1007/978-3-030-19504-5_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-19504-5_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-19503-8
Online ISBN: 978-3-030-19504-5
eBook Packages: Computer ScienceComputer Science (R0)