Unit 4: Sharing Open Data

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Learning objectives

This unit provides a foundation in sharing principles and data interoperability including frameworks, data structures, architectural interoperability and semantics for agronomic data. At the end of this unit, you will be able to;

understand and apply the principles of conceptual frameworks for sharing open data
make informed decisions on how to make the data findable, accessible, interoperable and reusable.
adopt relevant technologies and data standards

Lesson 4.1: Guiding frameworks for data sharing

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The lesson aims to introduce the most endorsed guiding frameworks for data sharing, and match the principles and indications from such frameworks with practical guidelines on how to implement them. After studying this lesson, you should be able to understand the principles of most important guiding frameworks for sharing open data, understand the major practical implications of these guiding frameworks, and evaluate different ways of publishing data, including tools, against these frameworks.

Lesson 4.2: Introduction to data interoperability

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The lesson aims to explain basics of data interoperability. After studying this lesson, you should be able to understand the basics of data interoperability and the different types and layers of interoperability of data.

Lesson 4.3: Structural and architectural interoperability

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The lesson aims to explain the basics of structural interoperability; data formats and structures, the basics of architectural interoperability including protocols and technical frameworks, and provide guidance on the advantages and disadvantages of specific solutions. After studying this lesson, you should be able to understand the basics of structural interoperability and current best practices, assess formats and protocols that better fit your needs, adopt the most interoperable solutions.

Lesson 4.4: Semantic interoperability

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The lesson aims to explain the basics of semantic interoperability and what vocabularies are, provide guidance on how to choose the most suitable vocabularies and how to use vocabularies in the (meta)data. After studying this lesson, you should be able to understand the basics of semantic interoperability, choose the vocabularies that better fit your needs and use vocabularies in the (meta)data.

Lesson 4.4.1: Using published semantics for agronomic data

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The lessons aims to provide guidance and examples on how to encode (meta)data using published semantics with specific examples for agronomic data. After studying this lesson, you should be able to understand how to identify suitable data standards to share agronomic data, how semantics are embedded in the (meta)data, and adopt the most suitable vocabularies for data of a specific type.