The RAGE Software Asset Model and Metadata Model

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• 关键词：Serious games ; Software assets ; Game assets ; Asset model ; Asset metadata model ; Metadata editor ; Gamification
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9894
• 期：1
• 页码：191-203
• 全文大小：1,667 KB
• 参考文献：1.van der Vegt, G.W., Westera, W., Nyamsuren, N., Georgiev, A., Martinez Ortiz, I.: RAGE architecture for reusable serious gaming technology components. Int. J. Comput. Games Technol. 2016 (2016). http://​dx.​doi.​org/​10.​1155/​2016/​5680526
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  8.Peeters, M., Van den Bosch, K., Meijer, J.-J.Ch., Neerincx, M.A.: An ontology for integrating didactics into a serious training game. In: Bocconi, S., Klamma, R., Bachvarova, Y.S. (eds) Proceedings of the 1st International Workshop on Pedagogically-Driven Serious Games (PDSG 2012). CEUR Workshop Proceedings, vol. 898, pp. 1–10. CEUR, Aachen (2012). ISSN 1613-0073
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• 作者单位：A. Georgiev (18)
  A. Grigorov (18) (23)
  B. Bontchev (18)
  P. Boytchev (18)
  K. Stefanov (18)
  K. Bahreini (19)
  E. Nyamsuren (19)
  W. van der Vegt (19)
  W. Westera (19)
  R. Prada (20)
  Paul Hollins (21)
  Pablo Moreno (22)
  
  18. Faculty of Mathematics and Informatics, Sofia University “St. Kliment Ohridski”, Sofia, Bulgaria
  23. Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgaria
  19. Open University of the Netherlands, Heerlen, The Netherlands
  20. University of Lisbon, Lisbon, Portugal
  21. The University of Bolton, Bolton, UK
  22. Universidad Complutense de Madrid, Madrid, Spain
  
• 丛书名：Serious Games
• ISBN：978-3-319-45841-0
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9894

文摘

Software assets are key output of the RAGE project and they can be used by applied game developers to enhance the pedagogical and educational value of their games. These software assets cover a broad spectrum of functionalities – from player analytics including emotion detection to intelligent adaptation and social gamification. In order to facilitate integration and interoperability, all of these assets adhere to a common model, which describes their properties through a set of metadata. In this paper the RAGE asset model and asset metadata model is presented, capturing the detail of assets and their potential usage within three distinct dimensions – technological, gaming and pedagogical. The paper highlights key issues and challenges in constructing the RAGE asset and asset metadata model and details the process and design of a flexible metadata editor that facilitates both adaptation and improvement of the asset metadata model.