TITLE:
Autonomous Data Exchange: The Malady and a Possible Path to Its Cure
AUTHORS:
Eli Rohn
KEYWORDS:
Software Engineering, Data Definition, Schema Matching, Data Integration, Complex Adaptive Systems
JOURNAL NAME:
Intelligent Information Management,
Vol.7 No.1,
January
28,
2015
ABSTRACT: 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.