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The Role of Citizen Science Data Standardization for the Marine Strategy Framework Directive Implementation

Vasiliki Myrintzou; Nikolaos Kokkos; Dor Edelist; Garabet Kazanjian; Georgios Sylaios
Oceans · Vol. 7, Issue 3 · pp. 36 · 2026

Abstract

Over the past two decades, Citizen Science (CS) has experienced rapid growth, driven by technological advancements and the rise of digital platforms. This work examines the necessity for standardization in Citizen Science data management and discusses how existing data standards can enhance the impact of citizen-generated data. CS standardization ensures data quality, comparability, reusability, and interoperability, making data suitable for contributing to the Marine Strategy Framework Directive (MSFD) and the United Nations Sustainable Development Goals (SDGs). This paper examined 130 Citizen Science publications and found that most collected data referred to the MSFD Descriptor 1 (Biodiversity—44.96%) and Descriptor 10 (Marine Litter—20.93%), followed by the alien species distribution (D2—11.63%), hydrography (D7—6.20%), eutrophication (D5—6.20%), and marine pollution (D8—3.10%). Analysis of 108 publications on SDG alignment revealed that the majority (35.58%) focused on reducing marine pollution. This paper reviews the best practices for effective Citizen Science data management, including standards for data structures, content, values, and exchange. Based on this review, Darwin Core, Ecological Metadata Language (EML), and the OGC SensorThings API appear to be the most suitable standards for MSFD-relevant CS data. Therefore, policymakers could enable the formal integration of standardized CS datasets into MSFD monitoring workflows.

Bibliographic Information

JournalOceans
PublisherMDPI
Publication Date2026-04-24
Publication Year2026
Volume7
Issue3
Pages36
Document TypeJournal Article
eISSN2673-1924
DOI10.3390/oceans7030036

Access Information

NARA Access Coverage2019-08-12 → Current
Publisher PageOpen Publisher Page
This article is openly available from the publisher.