Abstract Various fuzzy data models such as fuzzy relational databases, fuzzy object-oriented databases, fuzzy object- relational databases and fuzzy XML have been proposed in the literature in order to represent and process fuzzy information in databases and XML. But little work has been done in modeling fuzzy data types. Actually in the fuzzy data models, each fuzzy value is associated with a fuzzy data type. Explicit representations of fuzzy data types are the foundation of fuzzy data processing. To fill this gap, in this paper, we propose several fuzzy data types, including fuzzy simple data types, fuzzy collection data types and fuzzy defined data types. We further investigate how to declare the fuzzy data types in the fuzzy object-oriented database model and fuzzy XML Schema. The proposed fuzzy data types can meet the requirement of modeling fuzzy data in the fuzzy databases and fuzzy XML.

References

[1] Bordogna G., Pasi G., and Lucarella D., A Fuzzy Object-Oriented Data Model for Managing Vague and Uncertain Information, International Journal of Intelligent Systems, vol. 14, no. 7, pp. 623-651, 1999. The International Arab Journal of Information Technology, Vol. 10, No. 6, November 2013

[2] Buckles P. and Petry E., A Fuzzy Representation of Data for Relational Database, Fuzzy Sets and Systems, vol. 7, no. 3, pp. 213- 226, 1982.

[3] Chelliah M., Sankaran S., Prasad S., Gopalan N., and Sivaselvan B., Routing for Wireless Mesh Networks with Multiple Constraints using Fuzzy Logic, International Arab Journal of Information Technology, vol. 9, no. 1, pp. 1-8, 2011.

[4] Cuevasa L., Mar nb N., Ponsb O., and Vilab A., pg4DB: A Fuzzy Object-Relational System, Fuzzy Sets and Systems, vol. 159, no. 12, pp. 1500-1514, 2008.

[5] Dietrich W. and Urban D., Fundamentals of Object Databases: Object-Oriented and Object- Relational Design, Morgan & Claypool Publishers, USA, 2010.

[6] Dubois D., Prade H., and Rossazza P., Vagueness, Typicality, and Uncertainty in Class Hierarchies, International Journal of Intelligent Systems, vol. 6, no. 2, pp. 167-183, 1991.

[7] Gaurav A. and Alhajj R., Incorporating Fuzziness in XML and Mapping Fuzzy Relational Data into Fuzzy XML, in Proceedings of the ACM Symposium on Applied Computing, France, pp. 456-460, 2006.

[8] George R., Srikanth R., Petry E., and Buckles P., Uncertainty Management Issues in the Object- Oriented Data Model, IEEE Transactions on Fuzzy Systems, vol. 4, no. 2, pp. 179-192, 1996.

[9] Gyseghem V. and Caluwe R., Imprecision and Uncertainty in UFO Database Model, Journal of the American Society for Information Science, vol. 49, no. 3, pp. 236-252, 1998.

[10] Ma M. and Yan L., Fuzzy XML Data Modeling with the UML and Relational Data Models, Data & Knowledge Engineering, vol. 63, no. 3, pp. 972-996, 2007.

[11] Ma M. and Yan L., A Literature Overview of Fuzzy Database Models, Journal of Information Science and Engineering, vol. 24, no. 1, pp. 189- 202, 2008.

[12] Ma M. and Yan L., A Literature Overview of Fuzzy Conceptual Data Modeling, Journal of Information Science and Engineering, vol. 26, no. 2, pp. 427-441, 2010.

[13] Ma M., Zhang J., and Ma Y., Extending Object- Oriented Databases for Fuzzy Information Modeling, Information Systems, vol. 29, no. 5, pp. 421-435, 2004.

[14] Ma M. and Yan L., Soft Computing in XML Data Management , Springer-Verlag, Germany, 2010.

[15] Oliboni B. and Pozzani G., Representing Fuzzy Information by using XML Schema, in Proceedings of the 19 th International Workshop on Database and Expert Systems Application, Italy, pp. 683-687, 2008.

[16] Prade H. and Testemale C., Generalizing Database Relational Algebra for the Treatment of Incomplete or Uncertain Information and Vague Queries, Information Sciences, vol. 34, no. 2, pp. 115-143, 1984.

[17] Raju N. and Majumdar K., Fuzzy Functional Dependencies and Lossless Join Decomposition of Fuzzy Relational Database Systems, ACM Transactions on Database Systems, vol. 13, no. 2, pp. 129-166, 1988.

[18] Umano M. and Fukami S., Fuzzy Relational Algebra for Possibility-Distribution-Fuzzy- Relational Model of Fuzzy Data, Journal of Intelligent Information Systems, vol. 3, no. 1, pp. 7-27, 1994.

[19] st nkaya E., Yazici A., and George R., Fuzzy Data Representation and Querying in XML Database, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 15, no. Supplement-1, pp. 43-57, 2007.

[20] Yan L., Ma M., and Liu J., Fuzzy Data Modeling Based on XML Schema, in Proceedings of the ACM International Symposium on Applied Computing, USA, pp. 1563-1567, 2009.

[21] Zadeh A., Fuzzy Sets, Information and Control, vol. 8, no. 3, pp. 338-353, 1965.

[22] Zadeh A., The Concept of Linguistic Variable and its Application to Approximate Reasoning I, Information Sciences, vol. 8, no. 3, pp. 199-251, 1975.

[23] Zadeh A., The Concept of Linguistic Variable and its Application to Approximate Reasoning II, Information Sciences, vol. 8, no. 4, pp. 301- 357, 1975.

[24] Zadeh A., The Concept of Linguistic Variable and Its Application to Approximate Reasoning III, Information Sciences, vol. 9, no. 1, pp. 43- 80, 1975.

[25] Zadeh A., Fuzzy Sets as a Basis for a Theory of Possibility, Fuzzy Sets and Systems, vol. 1, no. 1, pp. 3-28, 1978. Li Yan received her PhD degree from Northeastern University, China. She is currently an associate professor at Northeastern University, China. Her research interests include database modeling, XML data management, as well as imprecise and uncertain data processing. She has published some papers in international journals such as Information Systems Frontiers, International Journal of Intelligent Systems and Integrated Computer-Aided Engineering. Also, she has published several edited books with Springer and IGI Global.