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Building an ontology for system analysis

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Języki publikacji
EN
Abstrakty
EN
System analysis as scientific and engineering discipline underpins research and development in other areas. However, system analysis models and methods are often taught separately and, as a result, system analyst cannot form a holistic understanding of this area. In order to deepen our understanding of system analysis’ concepts and relations the ontology of this area was built. It was constructed based on models and methods of system analysis considered as knowledge patterns. The concept of system was selected as a central concept of ontology. Other important concepts, such as goal, function, decision and process are relating to it. Finally, the applications of created system analysis ontology for teaching system analysis in high school and as a part of semantic grid are discussed.
Słowa kluczowe
Twórcy
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
autor
  • Lviv Polytechnic National University, Lviv, Ukraine
Bibliografia
  • 1. A. Katrenko 2011. System analysis. -Lviv, Novy Svit-2000 press, 396 p. (in Ukrainian).
  • 2. M. Zgurovskij. 2006. The Bologna process: the main principles and processes of structural reform of Higher education in Ukraine.- Kyiv, NTU KPI.- 544 p. (in Ukrainian).
  • 3. The Ukrainian standard of higher education for specialty of system analysis.2016. Kyiv. (in Ukrainian).
  • 4. J. Barros-Justo, F. Benitti, A.Cravero-Leal. 2018. Software patterns and requirements engineering activities in real-world settings: A systematic mapping study. Computer Standards & Interfaces., Volume 58. 23-42.
  • 5. M. Fayad. 2017. Stable Analysis Patterns for Systems. Auerbach publications. 316 p.
  • 6. P. Wohed. 2000. Conceptual Patterns for Reuse in Information Systems Analysis. Proceedings of the 12th International Conference on Advanced Information Systems Engineering, June 05-09, Springer-Verlag London. 157-175.
  • 7. M. Mora, R. Mahesh, O. Gelman, M. Angel Sicilia. 2011. Onto-servsys: A service system ontology. The Science of Service Systems.-Springer, Boston, MA. 151-173
  • 8. N. Guarino D. Oberle D, S. Staab. 2009. What Is an Ontology? Handbook on Ontologies. Springer Berlin Heidelberg. 1–17.
  • 9. J. Gennari, M. Musen, R. Fergerson, 2003. The evolution of Protégé: an environment for knowledge-based systems development. Intern. Journal of Human-computer studies, 58(1).-, P.89-123.
  • 10. B. Dutta, C. Usashi, M. Devika. 2015. YAMO: Yet Another Methodology for large-scale faceted Ontology construction. J. Knowledge Management 19. 6-24.
  • 11. R. Iqbal, A. Masrah, M. Azmi, M. Aida, S. Nurfadhlina. 2013. An Analysis of Ontology Engineering Methodologies: A Literature Review, Research Journal of Applied Sciences, Engineering and Technology 6(16). 2993-3000.
  • 12. K. Badr, A. Badr. 2013. Phases in Ontology Building Methodologies: A Recent Review. /Ontology-Based Applications for Enterprise Systems and Knowledge Management. 100-123.
  • 13. P. Buitelaar, P. Cimiano, B. Magnini. 2005. Ontology learning from text: an overview. IOS Press.
  • 14. A. Alves, B. Antunes, F. Pereira, C. Bento. 2009. Semantic enrichment of places: Ontology learning from web. /International Journal of Knowledge- Based and Intelligent Engineering Systems, IOS Press, vol 13. 19-30.
  • 15. C. Toro, J. Vaquero, M. Grana C. Sanin, Szczerbicki E, J. Posada. 2012. Building Domain Ontologies from Engineering Standards. Cybernetics and Systems: An International Journal. 114-126.
  • 16. Y. Burov, V. Pasichnyk. 2018. Software systems based on ontological task models: monograph. – Saarbrücken, Germany: LAP LAMBERT Academic Publishing. – 100 p.
  • 17. IDEF5 – Ontology Description Capture Method – IDEF. [Electronic resource]/- access method: www.idef.com/idef5-ontology-description-capture-method/
  • 18. A. Gómez-Pérez. 2004. Ontology evaluation Handbook on ontologies. Springer Berlin Heidelberg. 251-273.
  • 19. M. Fernández-López, A. Gómez-Pérez, C. Suárez- Figueroa. 2013. Methodological guidelines for reusing general ontologies. Data Knowl. Eng. 86. 242- 275.
  • 20. M. Zgurovskij, A. Petrenko.2010. E-science on the path to semantic grid. Part 2: Semantic web and semantic grid. Systemic research and information technologies. 1-25. (in Ukrainian).
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5bd76b4b-6ee1-411d-8b29-55d1415942ad
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