A data-flow oriented software architecture for heterogeneous marine data streams

TL;DR

This paper proposes a data-flow oriented software architecture tailored for managing heterogeneous marine in-situ data streams, emphasizing architectural decisions informed by expert knowledge and empirical analysis.

Contribution

It introduces a novel architecture for marine data streams, combining a component and connector view with empirical insights from marine domain experts.

Findings

Architecture effectively manages diverse marine data sources

Prototype demonstrates practical applicability

Empirical process validates design choices

Abstract

Marine in-situ data is collected by sensors mounted on fixed or mobile systems deployed into the ocean. This type of data is crucial both for the ocean industries and public authorities, e.g., for monitoring and forecasting the state of marine ecosystems and/or climate changes. Various public organizations have collected, managed, and openly shared in-situ marine data in the past decade. Recently, initiatives like the Ocean Decade Corporate Data Group have incentivized the sharing of marine data of public interest from private companies aiding in ocean management. However, there is no clear understanding of the impact of data quality in the engineering of systems, as well as on how to manage and exploit the collected data. In this paper, we propose main architectural decisions and a data flow-oriented component and connector view for marine in-situ data streams. Our results are based on a longitudinal empirical software engineering process, and driven by knowledge extracted from the experts in the marine domain from public and private organizations, and challenges identified in the literature. The proposed software architecture is instantiated and exemplified in a prototype implementation.