Synthesized data quality requirements and roadmap for improving reusability of in-situ marine data
Paper i proceeding, 2023

Background: In-situ marine data has a low reusability rate, primarily due to differences in data usage objectives among stakeholders in data ecosystems. The extreme cost of collecting and maintaining in-situ marine data threatens the sustainable usage of the ocean.
Aims: This paper provides an overview of current data and data quality (DQ) requirements. We also investigate limitations in the current practices that obstruct data reusability. The ultimate objective is to improve data requirements elicitation, leading to enhanced data reusability.
Method: We interviewed 14 marine practitioners and researchers from 7 organizations with extensive experience in collecting, managing, and utilizing in-situ marine data.
Results: We identify 9 representative use cases in the fishery, energy, and marine sciences industries, as well as their data and DQ requirements. The results give guidance to data producers to produce data meeting demands of a wider range of data consumers. At the same time, data consumers can refer to the compilation to identify existing data suiting their needs. Furthermore, we recommend a roadmap taken into account during requirements elicitation to improve 6 limitations in the current practices that obstruct data reusability.

Författare

Thanh Ngoc Nguyen

Høgskulen på Vestlandet (HVL)

Keila Lima

Høgskulen på Vestlandet (HVL)

Astrid Marie Skalvik

Universitetet i Bergen

Rogardt Heldal

Chalmers, Data- och informationsteknik, Software Engineering

Göteborgs universitet

Eric Knauss

Göteborgs universitet

Chalmers, Data- och informationsteknik, Interaktionsdesign och Software Engineering

Tosin Daniel Oyetoyan

Høgskulen på Vestlandet (HVL)

Patrizio Pelliccione

Göteborgs universitet

Software Engineering 1

Camilla Saetre

Universitetet i Bergen

Proceedings of the IEEE International Conference on Requirements Engineering

1090705X (ISSN) 23326441 (eISSN)

Vol. 2023 IEEE 31st International Requirements Engineering Conference (RE)
979-8-3503-2689-5 (ISBN)

2023 IEEE 31st International Requirements Engineering Conference (RE)
Hannover, Germany,

Ämneskategorier (SSIF 2025)

Datavetenskap (datalogi)

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Senast uppdaterat

2025-07-01