摘要
Data exchange is a goal-oriented social communications system implemented through computerized technology. Data definition languages (DDLs) provide the syntax for communicating within and between organizations, illocutionary acts, such as informing, ordering and warning. Data exchange results in meaning-preserving mapping between an ensemble (a constrained variety) and its external (unconstrained) variety. Research on unsupervised structured and semi-structured data exchange has not produced any significant successes over the past fifty years. As a step towards finding a solution, this article proposes a new look at data exchange by using the principles of complex adaptive systems (CAS) to analyze current shortcomings and to propose a direction that may indeed lead to workable and mathematically grounded solution. Three CAS attributes key to this research are variety, tension and entropy. We use them to show that older and contemporary DDLs are identical in their core, thus explaining why even XML and Ontologies have failed to a create fully automated data exchange mechanism. Then we show that it is possible to construct a radically different DDL that overcomes existing data exchange limitations—its variety, tension and entropy are different from existing solutions. The article has these major parts: definition of key CAS attributes;quantitative examination of representative old and new DDLs using these attributes;presentation of the results and their pessimistic ramification;a section that proposes a new theoretical way to construct DDLs that is based entirely on CAS principles, thus enabling unsupervised data exchange. The theory is then tested, showing very promising results.
Data exchange is a goal-oriented social communications system implemented through computerized technology. Data definition languages (DDLs) provide the syntax for communicating within and between organizations, illocutionary acts, such as informing, ordering and warning. Data exchange results in meaning-preserving mapping between an ensemble (a constrained variety) and its external (unconstrained) variety. Research on unsupervised structured and semi-structured data exchange has not produced any significant successes over the past fifty years. As a step towards finding a solution, this article proposes a new look at data exchange by using the principles of complex adaptive systems (CAS) to analyze current shortcomings and to propose a direction that may indeed lead to workable and mathematically grounded solution. Three CAS attributes key to this research are variety, tension and entropy. We use them to show that older and contemporary DDLs are identical in their core, thus explaining why even XML and Ontologies have failed to a create fully automated data exchange mechanism. Then we show that it is possible to construct a radically different DDL that overcomes existing data exchange limitations—its variety, tension and entropy are different from existing solutions. The article has these major parts: definition of key CAS attributes;quantitative examination of representative old and new DDLs using these attributes;presentation of the results and their pessimistic ramification;a section that proposes a new theoretical way to construct DDLs that is based entirely on CAS principles, thus enabling unsupervised data exchange. The theory is then tested, showing very promising results.
