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http://www.scirp.org/journal/PaperInformation.aspx?PaperID=53603#.VMnrIyzQrzE
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.
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References
Rohn, E. (2015) Autonomous Data Exchange: The Malady and a Possible Path to Its Cure. Intelligent Information Management, 7, 22-32. doi: 10.4236/iim.2015.71003.
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