Abstract
Motivated by challenges that emerged from Complex Event Processing (CEP) in Big Data contexts, an Intelligent Event Broker (IEB) was previously proposed as a CEP system built on flexible and scalable Big Data technologies and techniques, being already applied to Industry 4.0 scenarios. A key feature of the IEB lies in an effective visualization system for meta-monitorization and management. An analysis of previous scientific and technical literature has shown scarcity of proposals or development of such mechanisms. This paper proposes a Web Visualization Platform for managing and monitoring an IEB system based on novel approaches that include interactive exploration techniques, tridimensional visualizations and mixed-reality environments. Being mainly targeted towards Industry 4.0, this paper presents a demonstration case at Bosch Car Multimedia Portugal. Results indicate that significant value can be obtained when the visualization system is applied to decision support scenarios within organizations foreseeing event processing, Big Data, and Industry 4.0 projects.
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References
Andrade, C., Correia, J., Costa, C., Santos, M.Y.: Intelligent event broker: a complex event processing system in big data contexts. In: AMCIS 2019 Proceedings, Cancún, Mexico (2019)
Pyne, S., Rao, B.L.S.P., Rao, S.B. (eds.): Big Data Analytics. Springer, New Delhi (2016). https://doi.org/10.1007/978-81-322-3628-3
Tsai, C.-W., Lai, C.-F., Chao, H.-C., Vasilakos, A.V.: Big data analytics: a survey. J. Big Data 2 (2015). https://doi.org/10.1186/s40537-015-0030-3
Gorodov, E.Y., Gubarev, V.V.: Analytical Review of Data Visualization Methods in Application to Big Data. https://doi.org/10.1155/2013/969458, https://www.hindawi.com/journals/jece/2013/969458/. Accessed 15 Dec 2018
Agrawal, R., Kadadi, A., Dai, X., Andres, F.: Challenges and opportunities with big data visualization. In: Proceedings of the 7th International Conference on Management of Computational and Collective Intelligence in Digital EcoSystems - MEDES 2015, Caraguatatuba, Brazil, pp. 169–173. ACM Press (2015). https://doi.org/10.1145/2857218.2857256
Chandler, T., et al.: Immersive analytics. In: 2015 Big Data Visual Analytics (BDVA), Hobart, Australia, pp. 1–8. IEEE (2015). https://doi.org/10.1109/BDVA.2015.7314296
Sicat, R., et al.: DXR: a toolkit for building immersive data visualizations. IEEE Trans. Visual Comput. Graphics 25, 715–725 (2019). https://doi.org/10.1109/TVCG.2018.2865152
Butscher, S., Hubenschmid, S., Müller, J., Fuchs, J., Reiterer, H.: Clusters, trends, and outliers: how immersive technologies can facilitate the collaborative analysis of multidimensional data. In: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI 2018, Montreal QC, Canada, pp. 1–12. ACM Press (2018). https://doi.org/10.1145/3173574.3173664
Donalek, C., et al.: Immersive and collaborative data visualization using virtual reality platforms. In: 2014 IEEE International Conference on Big Data (Big Data), pp. 609–614 (2014). https://doi.org/10.1109/BigData.2014.7004282
ElSayed, N.A.M., Thomas, B.H., Marriott, K., Piantadosi, J., Smith, R.T.: Situated analytics: demonstrating immersive analytical tools with augmented reality. J. Visual Lang. Comput. 36, 13–23 (2016). https://doi.org/10.1016/j.jvlc.2016.07.006
Mei, H., Ma, Y., Wei, Y., Chen, W.: The design space of construction tools for information visualization: a survey. J. Visual Lang. Comput. 44, 120–132 (2018). https://doi.org/10.1016/j.jvlc.2017.10.001
Shahzad, F., Sheltami, T.R., Shakshuki, E.M., Shaikh, O.: A review of latest web tools and libraries for state-of-the-art visualization. Procedia Comput. Sci. 98, 100–106 (2016). https://doi.org/10.1016/j.procs.2016.09.017
Kim, N.W., et al.: Data-driven guides: supporting expressive design for information graphics. IEEE Trans. Visual Comput. Graphics 23, 491–500 (2017). https://doi.org/10.1109/TVCG.2016.2598620
Butcher, P.W.S., Ritsos, P.D.: Building immersive data visualizations for the web. In: 2017 International Conference on Cyberworlds (CW), Chester, pp. 142–145. IEEE (2017). https://doi.org/10.1109/CW.2017.11
Flouris, I., et al.: FERARI: a prototype for complex event processing over streaming multi-cloud platforms. In: Proceedings of the 2016 International Conference on Management of Data, New York, NY, USA, pp. 2093–2096. ACM (2016). https://doi.org/10.1145/2882903.2899395
Acknowledgements
This work has been supported by national funds through FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019 and the Doctoral scholarship PD/BDE/135101/2017 and by European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 039479; Funding Reference: POCI-01-0247-FEDER-039479]. Authors acknowledge the Virtual and Augmented Reality work of Ana Dias, André Domingues, Maria Cardoso, Rui Faria and Vanessa Ferreira, the Bosch Car Multimedia and the 8thWall team that supported our work during the development phase.
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Rebelo, J., Andrade, C., Costa, C., Santos, M.Y. (2020). An Immersive Web Visualization Platform for a Big Data Context in Bosch’s Industry 4.0 Movement. In: Themistocleous, M., Papadaki, M. (eds) Information Systems. EMCIS 2019. Lecture Notes in Business Information Processing, vol 381. Springer, Cham. https://doi.org/10.1007/978-3-030-44322-1_6
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