AN OVERVIEW OF OCEAN DATA THROUGH THE LENS OF THE DATA ECOSYSTEM

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Authors: Maya Bloch Haimson, Tomer Sagi, Yoav Lehahn
Cited by: 0

Abstract

The oceans, covering approximately 70% of Earth's surface, play a pivotal role in climate regulation, biodiversity, and biogeochemical processes. The large and growing volume and complexity of ocean data, spanning diverse disciplines and formats, and dispersed across a wide range of sources, presents opportunities and challenges for advancing scientific research, informing policy, and addressing societal needs. Here we present an easy-to-navigate map of the field of ocean data, which enables the establishment of a broad understanding of the ocean data sector and bridges gaps between different disciplines and levels of familiarity with ocean data. This is done through the concept of the “data ecosystem”, which is used to describe the actors, organizations, and infrastructures involved in all aspects of the data value chain. We propose a structured ocean data ecosystem model as a method for comprehensive mapping of the ocean data market landscape. The proposed model consists of five key elements: stakeholders, societal elements (such as the FAIR principles), interoperability tools (such as standards and best practices), data sources and product offering, and emerging solutions. We provide an up-to-date analysis and examples of ocean data sources (such as raw sources, repositories and portals) which serve as the infrastructural elements of the ocean data ecosystem, where data producers and data users interact, examples of emerging solutions and a summary of relevant data standardization efforts such as marine standards, vocabularies, and ontologies. All this will promote the development of needs-based solutions, components, products, services, and technologies, thus contributing to the evolution of the ocean data ecosystem and promoting data-based ocean research.

Fields of Study & Subjects

Research Data Management Practices Environmental Monitoring and Data Management Scientific Computing and Data Management

Publication details

Publication date
9 February 2026
Language
EN
Document type
Preprint