A data-flow oriented software architecture for heterogeneous marine data streams
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arXiv
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| Format: | Preprint |
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2024
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| author | Lima, Keila Nguyen, Ngoc-Thanh Heldal, Rogardt Kristensen, Lars Michael Oyetoyan, Tosin Daniel Pelliccione, Patrizio Knauss, Eric |
| author_facet | Lima, Keila Nguyen, Ngoc-Thanh Heldal, Rogardt Kristensen, Lars Michael Oyetoyan, Tosin Daniel Pelliccione, Patrizio Knauss, Eric |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_13231 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A data-flow oriented software architecture for heterogeneous marine data streams Lima, Keila Nguyen, Ngoc-Thanh Heldal, Rogardt Kristensen, Lars Michael Oyetoyan, Tosin Daniel Pelliccione, Patrizio Knauss, Eric Software Engineering 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. |
| title | A data-flow oriented software architecture for heterogeneous marine data streams |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2407.13231 |