Information system ecology: An application of dataphoric ascendancy. (March 2020)

• Record Type: Journal Article
• Authors: Pritchard, Michael J.; Martel, J.C.
• Is Part Of: Information systems. Volume 89(2020)
• Publication Date: 2020-03
• Subjects: Theory of dataphoric ascendancy -- Information ecology -- Information diversity -- Information theory -- Information systems diversity -- Dataphoric space -- Dataphore -- Dataphora; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2019.101486
• Languages: English
• ISSNs: 0306-4379

Abstract

Abstract: Information systems, like biological systems, are susceptible to external perturbations. Similar to flora and fauna in a biome, species of data can be classified within a dataphora. While entropic properties and data geometries can be used to describe local species of data within a dataphora, they are not designed to describe the global properties of an information system or evaluate its stability. Ecologists have used Information Theories to describe macro-level properties of biological ecosystems and statistical tools to evaluate biological systems. This research leverages an ecological perspective to model information systems as a living system. Our findings support the theory of dataphoric ascendancy with Wikipedia having a Diversity Index value of 0.68, within the range of 0.65 and 0.80 that indicates a balanced state. We further support our findings with additional evaluations of other ecosystems including the predicted collapse of the information service known as the Digital Universe. This research allows for an information system's stability to be (a) characterized and (b) predicted using ecological measures specific to the diversity of data within the ecosystem. Highlights: A biologically-stylized theory of data and the information system. Utilizing ecological concepts such as dominance, diversity and uniformity. Inception of dataphoric research ontology grounded in the Theory of Dataphoric Space. Creation of information system data species via diversity, dominance and uniformity. Dataphoric stability patterns of a dataphora that are measurable and predictive. We find support for a Theory of Dataphoric Ascendancy.