IJMLC 2015 Vol. 5(2): 153-159 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2015.V5.500

Agile Methodology to Develop Architecture of Information and Knowledge in Organizations (MADAIKE)

Nieto Bernal Wilson and Luna Amaya Carmenza

Abstract—In This article presents a methodology based on the articulation of emerging paradigms for architecture development of information and knowledge (MADAIKE) that in turn promote the integration of various standards and justify the value to the organization. The first one comes from the agile methods and it is inspired on the Scrum model which aim to simplify the complex task of developing a quality software, the second one takes as a reference the processes models whose are oriented toward the development of Architectures of business information as Zachmantm, TOGAFtm, SOMFtm, TOGAF, UPDM and others, whose purpose is to articulate in a single model the business architecture and the information architecture, it is framed, of course, in a paradigm of the model driven generation (MDG), and the third approach with project planning (PP) inspired by the PMBOK standard and especially in the projects planning process group, in addition to this, there are important aspects related to the UML 2.5 and the business process modeling that become tools to obtain the products in the MADAIKE methodology. These approaches are integrated eventually leading to the formulation and presentation of an agile methodology called – MADAIKE.

Index Terms—Agile methodology, architecture information enterprise, software process, project planning, validation, verification, management knowledge, systems engineering.

Nieto Bernal Wilson and Luna Amaya Carmenza are with Universidad del Norte Colombia, Colombia (e-mail: wnieto@uninorte.edu.co).


Cite: Nieto Bernal Wilson and Luna Amaya Carmenza, "Agile Methodology to Develop Architecture of Information and Knowledge in Organizations (MADAIKE)," International Journal of Machine Learning and Computing vol. 5, no. 2, pp. 153-159, 2015.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net