Active Data
For developers of complex systems, this work offers an intuitive decomposition method, but the lack of concrete results makes its significance unclear.
The paper introduces Active Data, a bottom-up approach where data objects actively interact with environments, to improve reasoning over large, complex datasets. An implementation in air traffic flow management is described, but no concrete performance numbers are provided.
In some complex domains, certain problem-specific decompositions can provide advantages over monolithic designs by enabling comprehension and specification of the design. In this paper we present an intuitive and tractable approach to reasoning over large and complex data sets. Our approach is based on Active Data, i.e., data as atomic objects that actively interact with environments. We describe our intuition about how this bottom-up approach improves designs confronting computational and conceptual complexity. We describe an implementation of the base Active Data concepts within the air traffic flow management domain and discuss performance for this implementation.