The analysis of relationships between key performance indicators is one of the challenging tasks in modern business applications. On the one hand, a complex network of key performance indicators, based on sensor data and calculations, is obviously available in technical systems, but on the other hand, the final human decision is based on the information provided by visualization types like dashboards. But in most cases dashboards only cover static information and neglects temporal dependencies. In this paper, we present an approach for the integration of a temporal perspective into a graph-based visualization for the analysis of key performance indicators using multi-level graphs.
[ALA07] ARNOLD A., LIU Y., ABE N.: Temporal causal modeling with graphical granger methods. In Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining (New York, NY, USA, 2007), KDD ’07, ACM, pp. 66–75. 3
[APP11] ARCHAMBAULT D., PURCHASE H. C., PINAUD B.: Difference map readability for dynamic graphs. In Proceedings of the 18th international conference on Graph drawing (Berlin, Heidelberg, 2011), GD’10, Springer-Verlag, pp. 50–61. 3
[BBD08] BURCH M., BECK F., DIEHL S.: Timeline trees: visualizing sequences of transactions in information hierarchies. In Proceedings of the working conference on Advanced visual interfaces (New York, NY, USA, 2008), AVI ’08, ACM, pp. 75–82. 3
[BdMM08] BENDER-DEMOLL S., MORRIS M., MOODY J.: Prototype packages for managing and animating longitudinal network data: dynamicnetwork and rsonia. Journal of Statistical Software 24, 7 (5 2008), 1–36. 3
[BHPS12] BASOLE R. C., HU M., PATEL P., STASKO J. T.: Visual analytics for converging-business-ecosystem intelligence. IEEE Computer Graphics and Applications 32 (2012), 92–96. 3
[DeS84] DESANCTIS G.: Computer graphics as decision aids: Directions for research. Decision Sciences 15, 4 (1984), 463–487. 3
[DGK01] DIEHL S., GOERG C., KERREN A.: Preserving the mental map using foresighted layout. In Data Visualization 2001, Ebert D., Favre J., Peikert R., (Eds.), Eurographics. Springer Vienna, 2001, pp. 175–184. 3
[DKM*13] DENNERT A., KRAUSE J., MONTEMAYOR J. A. G. I., HESSE S., LASTRA J. L. M., WOLLSCHLAEGER M.: Advanced concepts for flexible data integration in heterogeneous production environments. In 11th IFAC Workshop on Intelligent
Manufacturing Systems (IMS 2013) (2013). 5
[DT11] DOGANATA Y., TOPKARA M.: Visualizing meetings as a graph for more accessible meeting artifacts. In Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems (New York, NY, USA, 2011), CHI EA ’11, ACM, pp. 1939–1944. 3
[EB12] ELIAS M., BEZERIANOS A.: Annotating bi visualization dashboards: needs and challenges. In Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems (New York, NY, USA, 2012), CHI ’12, ACM, pp. 1641–1650. 3
[EHK*04] ERTEN C., HARDING P., KOBOUROV S., WAMPLER K., YEE G.: Graphael: Graph animations with evolving layouts. In Graph Drawing, Liotta G., (Ed.), vol. 2912 of Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2004, pp. 98–110. 3
[ELS91] EADES P., LAI W., SUGIYAMA K. M. K.: Preserving the mental map of a diagram. Research Report Iias-rr-91-16e, International Institute For Advanced Study Of Social Information Science, Fujitsu Laboratories Limited, (August 1991). 4
[FG90] FITZ-GIBBON C. T.: Performance Indicators. BERA Dialogues Series. Multilingual Matters Ltd, 1990. ISBN:1853590924. 2
[FSC99] FERNANDES SILVA S., CATARCI T.: Graphical interaction with historical databases. In Scientific and Statistical Database Management, 1999. Eleventh International Conference on (1999), pp. 184–193. 3
[FWSL12] FENG K.-C., WANG C., SHEN H.-W., LEE T.-Y.: Coherent time-varying graph drawing with multifocus+context interaction. Visualization and Computer Graphics, IEEE Transactions on 18, 8 (aug. 2012), 1330 –1342. 3
[GBD09] GREILICH M., BURCH M., DIEHL S.: Visualizing the evolution of compound digraphs with timearctrees. Computer Graphics Forum 28, 3 (2009), 975–982. 3
[GRC04] GOLFARELLI M., RIZZI S., CELLA I.: Beyond data warehousing: what’s next in business intelligence? In Proceedings of the 7th ACM international workshop on Data warehousing and OLAP (New York, NY, USA, 2004), DOLAP ’04, ACM, pp. 1–6. 3
[Hil12] HILGEFORT I.: Reporting and analysis with SAP BusinessObjects, 2. ed., updated for release 4.0 fp3 ed. Galilep Pr., Bonn [u.a.], 2012. 3
[HTB*11] HORSFALL F., TANEV S., BONTCHEV B., GIGILEV T., GRUEV A.: Visualization of complex data relationships and maps: using the bloom platform to provide business insights. In Proceedings of the 12th International Conference on Computer Systems and Technologies (New York, NY, USA, 2011), Comp-
SysTech ’11, ACM, pp. 266–272. 3
[HVNK13] HESSE S., VASYUTYNSKYY V., NADOVEZA D., KIRITSIS D.: Visual analysis of performance indicators and processes in modern manufacturing. In 11th Global Conference on Sustainable Manufacturing (GCSM 2013), Berlin, Germany (Berlin, Germany, September 2013), Seliger G., (Ed.), Technische Universitaet Berlin, Institut of Machine Tools and Factory Management, UniversitÃd’tsverlag der TU Berlin, pp. 455–460. 3
[HVRH13] HESSE S., VASYUTYNSKYY V., ROSJAT M., HENGSTLER C.: Modeling and presentation of interdependencies between key performance indicators for visual analysis support. In Advances in Production Management Systems. Competitive Manufacturing for Innovative Products and Services, Emmanouilidis C., Taisch M., Kiritsis D., (Eds.), vol. 398 of IFIP Advances in Information and Communication Technology. Springer Berlin Heidelberg, 2013, pp. 281–288. 3
[ISO14] ISO: Automation systems and integration - Key performance indicators (KPIs) for manufacturing operations management - Part 2: Definitions and descriptions. Tech. rep., International Organization for Standardization, 2014. 2
[Kei02] KEIM D. A.: Datenvisualisierung und data mining. DatenbankSpektrum 2, 1 (2002), 30–39. 3
[KKS*09] KEIM D. A., KOHLHAMMER J., SANTUCCI G., MANSMANN F., WANNER F., SCHAEFER M.: Visual analytics challenges. In Proceedings of eChallenges 2009 (2009), p. 8. Echallenges 2009, Istanbul, Turkey. 3
[KN92] KAPLAN R. S., NORTON D. P.: The balanced scorecard - measures that drive performance. Harvard Business Review January-February (1992), 71–79. 2
[KNC*11] KHURANA U., NGUYEN V.-A., CHENG H.-C., WOOK AHN J., CHEN X., SHNEIDERMAN B.: Visual analysis of temporal trends in social networks using edge color coding and metric timelines. In Privacy, security, risk and trust (passat), 2011 ieee third international conference on and 2011 ieee third international conference on social computing (socialcom) (oct. 2011), pp. 549 –554. 3
[LBD07] LOUBIER E., BAHSOUN W., DOUSSET B.: Visualization and analysis of large graphs. In Proceedings of the ACM first Ph.D. workshop in CIKM (New York, NY, USA, 2007), PIKM ’07, ACM, pp. 41–48. 3
[MELS95] MISUE K., EADES P., LAI W., SUGIYAMA K.: Layout adjustment and the mental map. Journal of Visual Languages& Computing 6, 2 (1995), 183 – 10. 4
[PS06] PERER A., SHNEIDERMAN B.: Balancing systematic and flexible exploration of social networks. Visualization and Computer Graphics, IEEE Transactions on 12, 5 (2006), 693–700. 3
[RC13] RAINER R. K., CEGIELSKI C. G.: Introduction to information systems, 4. ed., international student version ed. Wiley, Singapore ; Hoboken, NJ, 2013. 3
[RSB09] RODRIGUEZ R. R., SAIZ J. J. A., BAS A. O.: Quantitative relationships between key performance indicators for supporting decision-making processes. Computers in Industry 60, 2 (2009), 104 – 113. 2
[SDM12] SCHMIDT B., DOEWELING S., MÜHLHÄUSER M.: Interaction history visualization. In Proceedings of the 30th ACM international conference on Design of communication (New York, NY, USA, 2012), SIGDOC ’12, ACM, pp. 261–270. 3
[SKM06] SCHRECK T., KEIM D. A., MANSMANN F.: Regular treemap layouts for visual analysis of hierarchical data. Spring Conference on Computer Graphics (SCCG’2006), Acm Siggraph, 2006, April 20-22, Casta Papiernicka, Slovak Republic„ 2006. 3
[SLN05] SARAIYA P., LEE P., NORTH C.: Visualization of graphs with associated timeseries data. In Information Visualization, 2005. INFOVIS 2005. IEEE Symposium on (2005), pp. 225–232. 3
[The06] THERÓN R.: Hierarchical-temporal data visualization using a tree-ring metaphor. In Smart Graphics (2006), Butz A., Fisher B., KrÃijger A., Olivier P., (Eds.), vol. 4073 of Lecture Notes in Computer Science, Springer, pp. 70–81. 3
[VHM12] VASYUTYNSKYY V., HENGSTLER C., MCCARTHY J., BRENNAN K., NADOVEZA D., DENNERT A.: Layered architecture for production and logistics cockpits. In Emerging Technologies Factory Automation (ETFA), 2012 IEEE 17th Conference on (2012), pp. 1–9. 5
[WLR11] WETZSTEIN B., LEITNER P., ROSENBERG F., DUSTDAR S., LEYMANN F.: Identifying influential factors of business process performance using dependency analysis. Enterprise Information Systems 5, 1 (2011), 79–98. 3
[Wu02] WU J.: Visualization of key performance indicators. http://www.information-management.com/news/5229-1.html?zkPrintable=true, May 2002. 2
