Active Data

TL;DR

This paper introduces Active Data, a bottom-up approach where data as active objects interact with environments, improving design comprehension and handling complexity, demonstrated through air traffic management.

Contribution

It presents a novel Active Data framework that treats data as active objects, enhancing reasoning over complex datasets and domains.

Findings

Active Data improves understanding of complex data sets.

Implementation in air traffic management shows promising performance.

Bottom-up data interaction aids in managing computational complexity.

Abstract

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.