Generational analysis of variety in data structures: impact on automatic data integration and on the semantic web

作     者：Rohn, Eli 

作者机构：New Jersey Inst Technol Dept Informat Syst Newark NJ 07102 USA 

出 版 物：《KNOWLEDGE AND INFORMATION SYSTEMS》 (知识和信息系统季刊)

年 卷 期：2010年第24卷第2期

页      面：283-304页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 0701[理学-数学] 071101[理学-系统理论] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Research Grants Council 

主　　题：Data integration Semantic web Data definition languages Zipf distribution Law of requisite variety Coding and information theory Information systems models and principles 

摘      要：We examine data definition languages (DDLs) from various computing era spanning almost 50 years to date. We prove that contemporary DDLs are indistinguishable from older ones using Zipf distribution of words, Zipf distributions of meanings, and information theory. None addresses the Law of Requisite Variety, which is necessary for enabling automatic data integration from autonomous heterogeneous data sources and for the realization of the Semantic Web. The growth of the entire computing industry is hampered by the lack of progress in the development of DDLs suitable for these two goals. Our findings set the stage for the future development of a mathematically sound DDL better suited for the aforementioned purposes.