Modelos de Requisitos Basados en I* para Detectar Proactividad en Dashboards

  1. Pérez Acosta, Alain 1
  2. Moreno Espino, Mailyn 1
  1. 1 Instituto Superior Politécnico José Antonio Echeverría (CUJAE), Facultad de Ingeniería Informática
Aldizkaria:
Lámpsakos

ISSN: 2145-4086,  2145-4086

Argitalpen urtea: 2014

Zenbakien izenburua: Edición 12: Investigación, Desarrollo e Innovación Tecnológica

Zenbakia: 12

Orrialdeak: 101-109

Mota: Artikulua

DOI: 10.21501/21454086.1349 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Beste argitalpen batzuk: Lámpsakos

Garapen Iraunkorreko Helburuak

Laburpena

This paper aims to present models for the capture of the requirements of a dashboard that allow detecting a proactive behavior. These models follow a goals oriented approach and were created using the framework i *, which is based on the premises of the social modeling. In order to detect the proactive behavior patterns based on models of i * that allow detecting proactivity in the stage of requirements of a system of software were used. In the models obtained as a result of the paper were represented the actors, goals, intentions, tasks and resources necessary to model the requirements of a dashboard with a proactive behavior, and these models can be used in addition in different contexts of business.

Erreferentzia bibliografikoak

  • Zagorecki, A., et al., Executive Dashboard Systems for Emergency Management. COMMUNICATIONS, 2012. 4(2): p. 82-89.
  • Gröger, C., et al., The Operational Process Dashboard for Manufacturing. 2013: p. 6.
  • Lempinen, H., Constructing a Design Framework for Performance Dashboards, in Nordic Contributions in IS Research, C. Keller, et al., Editors. 2012, Springer Berlin Heidelberg. p. 109-130.
  • Elias, M. and A. Bezerianos, Exploration Views: Understanding Dashboard Creation and Customization for Visualization Novices, in Human-Computer Interaction – INTERACT 2011, P. Campos, et al., Editors. 2011, Springer Berlin Heidelberg. p. 274-291.
  • Eckerson, W.W., What Are Performance Dashboards?, in Performance Dashboards: Measuring, Monitoring, and Managing Your
  • Business, John Wiley & Sons.
  • Few, S., Information Dashboard Design: The Effective Visual Communication of Data 2006: O'Reilly.
  • Yigitbasioglu, O.M. and O. Velcu, A review of dashboards in performance management: Implications for design and research. International Journal of Accounting Information Systems, 2011. 13: p. 19.
  • Grant, A.M. and S.J. Ashford, The dynamics of proactivity at work. Research in Organizational Behavior, 2008. 28(-): p. 3-34.
  • Li, J. and Y. Feng, Construction of Multi-Agent System for Decision Support of Online Shopping, in Emerging Research in Artificial Intelligence and Computational Intelligence, H. Deng, et al., Editors. 2011, Springer Berlin Heidelberg. p. 318-324.
  • Srinivasan, S., J. Singh, and V. Kumar, Multi-agent based decision Support System using Data Mining and Case Based Reasoning. International Journal of Computer Science Issues, 2011. 8(4): p. 340-349.
  • Lindgren, H., D. Surie, and I. Nilsson, Agent-Supported Assessment for Adaptive and Personalized Ambient Assisted Living, in Trends in Practical Applications of Agents and Multiagent Systems, J. Corchado, et al., Editors. 2011, Springer Berlin Heidelberg. p. 25-32.
  • McNaull, J., et al., Multi-agent System Feedback and Support for Ambient Assisted Living, in 8th International Conference on Intelligent Environments. 2012: Guanajuato p. 319 - 322.
  • Ghorbani, J., M.A. Choudhry, and A. Feliachi, Real-time multi agent system modeling for fault detection in power distribution systems in North American Power Symposium. 2012: Champaign. p. 1-6.
  • Moreno, M., Patrones para incorporar proactividad en sistemas informáticos. 2013, Instituto Superior Politécnico José Antonio Echeverría: La Habana. p. 172.
  • Yu, E., Social Modeling and i*, in Conceptual Modeling: Foundations and Applications, T.B. Alexander, et al., Editors. 2009, Springer-Verlag. p. 99-121.
  • Yu, E., et al., Social Modeling for Requirements Engineering. 1st ed. 2011, Cambridge: The MIT Press. 760.
  • Mazón, J.N., J. Pardillo, and J. Trujillo, A Model-Driven Goal-Oriented Requirement Engineering Approach for Data Warehouses, in Advances in Conceptual Modeling – Foundations and Applications, J.-L. Hainaut, et al., Editors. 2007, Springer Berlin Heidelberg: Berlin. p. 255-264.
  • Frankl, V., Man's Search for Meaning. 2006: Beacon Press.
  • Jennings, N.R., An agent-based approach for building complex software systems. Communications of the ACM, 2001. 44(4): p. 35-41.
  • Sommerville, I., Integrated Requirements Engineering: A Tutorial. IEEE Software, 2005. 22(1): p. 16-23.
  • Sommerville, I. and P. Sawyer, Requirements Engineering: A Good Practice Guide. 1st ed. 1997: John Wiley & Sons. 404.
  • Jacobson, I., G. Booch, and J. Rumbaugh, The Unified Software Development Process. reprint ed. 2012: Prentice Hall.
  • Fuentes-Fernández, R., J. Gómez-Sanz, and J. Pavón, Understanding the human context in requirements elicitation. Requirements Engineering, 2010. 15(3): p. 267-283.
  • Horkoff, J. and E. Yu, Comparison and evaluation of goal-oriented satisfaction analysis techniques. Requirements Engineering, 2013. 18(3): p. 199-222.
  • Yu, E., Modelling Strategic Relationships for Process Reengineering, in Department of Computer Science. 1995, University of Toronto: Toronto, Canada.
  • Inmon, W.H., Building the Data Warehouse. 4th ed. 2005, Chichester: Wiley.
  • Burg, B., Foundation for Intelligent Physical Agents. 2004.
Datuen iturria: Dialnet