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JDR Vol.15 No.3 pp. 312-323
(2020)
doi: 10.20965/jdr.2020.p0312

Paper:

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User Stories-Based Requirement Elicitation for Data Visualization to Support Decision Making in Water Resource Management at Bago River Basin

Akira Kodaka*,†, Akiyuki Kawasaki**, Naruhiko Shirai*, Ralph Allen Acierto**, Win Win Zin***, and Naohiko Kohtake*

*Graduate School of System Design and Management, Keio University
Collaboration Complex, 4-1-1 Hiyoshi, Kohoku, Yokohama, Kanagawa 223-8526, Japan

†Corresponding author

**Department of Civil Engineering, The University of Tokyo, Tokyo, Japan

***Yangon Technological University, Yangon, Myanmar

Received:
September 20, 2019
Accepted:
February 20, 2020
Published:
March 30, 2020
Creative Commons License
Keywords:
requirement elicitation, decision making, water resource management, disaster, Myanmar
Abstract

Understanding of system requirements that satisfy end users’ needs is fundamental of system development, yet challenging when end users are unable to address their needs explicitly. Although a number of scholars have been designing and applying requirement elicitation techniques, there is a research gap in Spatial Decision Support System (SDSS) with Web-based Geographical Information System (Web-GIS) in water resource management for disaster risk reduction. The gap addresses especially design elicitation techniques and their performances 1) to understand data types used for decision making, 2) set timing for sharing the data to accomplish end users’ tasks, and 3) compile the data to be represented so as to facilitate end users’ decision making. This study therefore designed a requirement elicitation technique by advancing User Story Mapping (USM) and validated through a workshop using mock-up system interface with potential end users who are in charge of water resource management in Myanmar’s Bago River Basin. Through the research it could be validated that the user stories-based approach enabled end users to decompose their operation activities into tasks. It also allowed them to link to necessary data with visual image for facilitating their task accomplishments and decision making for water resource management. It was revealed that the benefits of using the designed approach are not only just to summarize necessary data and information for end users’ decision making but also to encourage them to proactively consider data utilization into their operations. For further development of the requirement elicitation to understand end users needs, insights and recommendations for the proposed technique designing and conducting of the workshop were obtained.

Cite this article as:
A. Kodaka, A. Kawasaki, N. Shirai, R. Acierto, W. Zin, and N. Kohtake, “User Stories-Based Requirement Elicitation for Data Visualization to Support Decision Making in Water Resource Management at Bago River Basin,” J. Disaster Res., Vol.15 No.3, pp. 312-323, 2020.
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References
  1. [1] J. T. Peterson and M. C. Freeman, “Integrating modeling, monitoring, and management to reduce critical uncertainties in water resource decision making,” J. of Environmental Management, Vol.183, Part 2, pp. 361-370, doi: 10.1016/j.jenvman.2016.03.015, 2016.
  2. [2] F. E. A. Horita, J. P. de Albuquerque, and V. Marchezini, “Understanding the decision-making process in disaster risk monitoring and early-warning: A case study within a control room in Brazil,” Int. J. of Disaster Risk Reduction, Vol.28, pp. 22-31, doi: 10.1016/j.ijdrr.2018.01.034, 2018.
  3. [3] N. Leelawat, A. Muhari, M. Srivichai, A. Suppasri, F. Imamura, and J. D. Bricker, “Preference for Information During Flood Disasters: A Study of Thailand and Indonesia,” B. McLellan (Ed.), “Sustainable Future for Human Security: Security, Cities and Governance,” pp. 335-349, Springer, 2018.
  4. [4] I. Demir and W. F. Krajewski, “Towards an integrated Flood Information System: Centralized data access, analysis, and visualization,” Environmental Modelling & Software, Vol.50, pp. 77-84, doi: 10.1016/j.envsoft.2013.08.009, 2013.
  5. [5] L. Zhou, X. Wu, Z. Xu, and H. Fujita, “Emergency decision making for natural disasters: An overview,” Int. J. of Disaster Risk Reduction, Vol.27, pp. 567-576, doi: 10.1016/j.ijdrr.2017.09.037, 2018.
  6. [6] M. R. Leipnik, K. K. Kemp, and H. A. Loaiciga, “Implementation of GIS for Water Resources Planning and Management,” J. of Water Resources Planning and Management, Vol.119, No.2, pp. 184-205, doi: 10.1061/(ASCE)0733-9496(1993)119:2(184), 1993.
  7. [7] Z. C. Aye, T. Sprague, V. J. Cortes, K. Prenger-Berninghoff, M. Jaboyedoff, and M.-H. Derron, “A collaborative (web-GIS) framework based on empirical data collected from three case studies in Europe for risk management of hydro-meteorological hazards,” Int. J. of Disaster Risk Reduction, Vol.15, pp. 10-23, doi: 10.1016/j.ijdrr.2015.12.001, 2016.
  8. [8] A. M. F. A. Lagmay, B. A. Racoma, K. A. Aracan, J. Alconis-Ayco, and I. L. Saddi, “Disseminating near-real-time hazards information and flood maps in the Philippines through Web-GIS,” J. of Environmental Sciences, Vol.59, pp. 13-23, doi: 10.1016/j.jes.2017.03.014, 2017.
  9. [9] N. R. Cadiz, “UP NOAH in Building Resilient Philippines; Multi-hazard and Risk Mapping for the Future,” Procedia Engineering, Vol.212, pp. 1018-1025, doi: 10.1016/j.proeng.2018.01.131, 2018.
  10. [10] R. Jeberson Retna Raj and T. Sasipraba, “Disaster management system based on GIS web services,” Proc. of the Recent Advances in Space Technology Services and Climate Change 2010 (RSTS & CC-2010), pp. 252-261, doi: 10.1109/RSTSCC.2010.5712855, 2010.
  11. [11] A. Ribeiro and A. Cardoso, “Prototype of a GIS web-based platform integrating sensor data geoprocessing for disaster management,” Proc. of the 2015 3rd Experiment Int. Conf. (exp.at’15), pp. 36-40, doi: 10.1109/EXPAT.2015.7463210, 2015.
  12. [12] F. E. A. Horita, J. P. de Albuquerque, L. C. Degrossi, E. M. Mendiondo, and J. Ueyama, “Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks,” Computers & Geosciences, Vol.80, pp. 84-94, doi: 10.1016/j.cageo.2015.04.001, 2015.
  13. [13] M. Evers, “An analysis of the requirements for DSS on integrated river basin management,” Management of Environmental Quality, Vol.19, No.1, pp. 37-53, doi: 10.1108/14777830810840354, 2008.
  14. [14] B. Nuseibeh and S. Easterbrook, “Requirements Engineering: A Roadmap,” Proc. of the Conf. on the Future of Software Engineering (ICSE’00), pp. 35-46, doi: 10.1145/336512.336523, 2000.
  15. [15] R. H. Thayer and M. Dorfman, “System and Software Requirements Engineering (IEEE Computer Society Press tutorial),” IEEE Computer Society Press, 1990.
  16. [16] A. Azadegan, K. N. Papamichail, and P. Sampaio, “Applying collaborative process design to user requirements elicitation: A case study,” Computers in Industry, Vol.64, Issue 7, pp. 798-812, doi: 10.1016/j.compind.2013.05.001, 2013.
  17. [17] M. J. Simonette, F. L. L. Sanches, and E. Spina, “Soft Systems Engineering Tools in Requirements Elicitation,” Int. J. of Systems Applications, Engineering & Development, Vol.4, Issue 3, pp. 65-75, 2010.
  18. [18] D. Würfel, R. Lutz, and S. Diehl, “Grounded requirements engineering: An approach to use case driven requirements engineering,” J. of Systems and Software, Vol.117, pp. 645-657, doi: 10.1016/j.jss.2015.10.024, 2016.
  19. [19] X. Mao and Q. Li, “Ontology-based web spatial decision support system,” Proc. of the 2011 19th Int. Conf. on Geoinformatics, pp. 1-4, doi: 10.1109/GeoInformatics.2011.5980936, 2011.
  20. [20] M. van den Homberg, R. Monné, and M. Spruit, “Bridging the information gap of disaster responders by optimizing data selection using cost and quality,” Computers & Geosciences, Vol.120, pp. 60-72, doi: 10.1016/j.cageo.2018.06.002, 2018.
  21. [21] C. Pacheco, I. García, and M. Reyes, “Requirements elicitation techniques: a systematic literature review based on the maturity of the techniques,” IET Software, Vol.12, No.4, pp. 365-378, doi: 10.1049/iet-sen.2017.0144, 2018.
  22. [22] A. Saad and C. Dawson, “Requirement elicitation techniques for an improved case based lesson planning system,” J. of Systems and Information Technology, Vol.20, No.1, pp. 19-32, doi: 10.1108/JSIT-12-2016-0080, 2018.
  23. [23] D. Mishra, A. Mishra, and A. Yazici, “Successful requirement elicitation by combining requirement engineering techniques,” Proc. of the 2008 1st Int. Conf. on the Applications of Digital Information and Web Technologies (ICADIWT), pp. 258-263, doi: 10.1109/ICADIWT.2008.4664355, 2008
  24. [24] E.-M. Schön, J. Thomaschewski, and M. J. Escalona, “Agile Requirements Engineering: A systematic literature review,” Computer Standards & Interfaces, Vol.49, pp. 79-91, doi: 10.1016/j.csi.2016.08.011, 2017.
  25. [25] J. Rehman, O. Sohaib, M. Asif, and B. Pradhan, “Applying systems thinking to flood disaster management for a sustainable development,” Int. J. of Disaster Risk Reduction, Vol.36, Article No.101101, doi: 10.1016/j.ijdrr.2019.101101, 2019.
  26. [26] C. G. Harrison and P. R. Williams, “A systems approach to natural disaster resilience,” Simulation Modelling Practice and Theory, Vol.65, pp. 11-31, doi: 10.1016/j.simpat.2016.02.008, 2016.
  27. [27] M. Aoyama, T. Nakatani, S. Saito, M. Suzuki, K. Fujita, H. Nakazaki, and R. Suzuki, “A Model and Architecture of REBOK (Requirements Engineering Body of Knowledge) and its Evaluation,” Proc. of the 2010 Asia Pacific Software Engineering Conf., pp. 50-59, doi: 10.1109/APSEC.2010.16, 2010.
  28. [28] N. Shirai, S. S. Bhagabati, A. Kodaka, N. Kohtake, A. Kawasaki, R. A. Acierto, and W. W. Zin, “Data Communication for Efficient Water Resource Management Among Multiple Stakeholders – A Case Study in the Bago River Basin, Myanmar –,” J. Disaster Res., Vol.13, No.1, pp. 70-79, doi: 10.20965/jdr.2018.p0070, 2018.
  29. [29] Y. Sugimori, K. Kusunoki, F. Cho, and S. Uchikawa, “Toyota production system and Kanban system Materialization of just-in-time and respect-for-human system,” Int. J. of Production Research, Vol.15, No.6, pp. 553-564, doi: 10.1080/00207547708943149, 1977.
  30. [30] M. O. Ahmad, D. Dennehy, K. Conboy, and M. Oivo, “Kanban in software engineering: A systematic mapping study,” J. of Systems and Software, Vol.137, pp. 96-113, doi: 10.1016/j.jss.2017.11.045, 2018.
  31. [31] D. Anderson, “Kanban: Successful Evolutionary Change for Your Technology Business,” Blue Hole Press, 2010.
  32. [32] J. Patton and P. Economy, “User Story Mapping: Discover the Whole Story, Build the Right Product,” 1st edition, O’Reilly Media, Inc., 2014.
  33. [33] J. Patton, “It’s All in How You Slice It: Design your project in working layers to avoid half-baked incremental releases,” Better Software, Vol.2005, Issue 1, pp. 16-40, 2005.
  34. [34] A. Kawasaki, N. Ichihara, Y. Ochii, R. A. Acierto, A. Kodaka, and W. W. Zin, “Disaster response and river infrastructure management during the 2015 Myanmar floods: A case in the Bago River Basin,” Int. J. of Disaster Risk Reduction, Vol.24, pp. 151-159, doi: 10.1016/j.ijdrr.2017.06.004, 2017.
  35. [35] A. Kawasaki, A. Yamamoto, P. Koudelova, R. Acierto, T. Nemoto, M. Kitsuregawa, and T. Koike, “Data Integration and Analysis System (DIAS) Contributing to Climate Change Analysis and Disaster Risk Reduction,” Data Science J., Vol.16, Article No.41, doi: 10.5334/dsj-2017-041, 2017.
  36. [36] S. S. Bhagabati and A. Kawasaki, “Consideration of the rainfall-runoff-inundation (RRI) model for flood mapping in a deltaic area of Myanmar,” Hydrological Research Letters, Vol.11, No.3, pp. 155-160, doi: 10.3178/hrl.11.155, 2017.
  37. [37] W. W. Zin, A. Kawasaki, and S. Win, “River flood inundation mapping in the Bago River Basin, Myanmar,” Hydrological Research Letters, Vol.9, No.4, pp. 97-102, doi: 10.3178/hrl.9.97, 2015.
  38. [38] S. Win, W. W. Zin, A. Kawasaki, and Z. M. L. T. San, “Establishment of flood damage function models: A case study in the Bago River Basin, Myanmar,” Int. J. of Disaster Risk Reduction, Vol.28, pp. 688-700, doi: 10.1016/j.ijdrr.2018.01.030, 2018.
  39. [39] Japan Science and Technology Agency (JST), “Development of a Comprehensive Disaster Resilience System and Collaboration Platform in Myanmar,” https://www.jst.go.jp/global/english/kadai/h2607_myanmar.html [accessed September 30, 2010]
  40. [40] R. A. Acierto, A. Kawasaki, W. W. Zin, A. T. Oo, K. Ra, and D. Komori, “Development of a Hydrological Telemetry System in Bago River,” J. Disaster Res., Vol.13, No.1, pp. 116–124, doi: 10.20965/jdr.2018.p0116, 2018.
  41. [41] A. Zerger and D. I. Smith, “Impediments to using GIS for real-time disaster decision support,” Computers, Environment and Urban Systems, Vol.27, No.2, pp. 123-141, doi: 10.1016/S0198-9715(01)00021-7, 2003.
  42. [42] P. Thamarux, A. Suppasri, N. Leelawat, M. Matsuoka, and F. Imamura, “Disaster Emergency Response Plan of the Royal Thai Embassy in Tokyo, Japan: A Review,” J. Disaster Res., Vol.14, No.7, pp. 959-971, doi: 10.20965/jdr.2019.p0959, 2019.

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