RDF

Table of Contents

• Documentation
• Pros and Cons
• Example use cases
• FAIR Principles

Documentation

• Technology Description

  • The Resource Description Framework (RDF) is a framework for expressing information about resources. Resources can be anything, including documents, people, physical objects, and abstract concepts.

    RDF is intended for situations in which information on the Web needs to be processed by applications, rather than being only displayed to people. RDF provides a common framework for expressing this information so it can be exchanged between applications without loss of meaning. Since it is a common framework, application designers can leverage the availability of common RDF parsers and processing tools. The ability to exchange information between different applications means that the information may be made available to applications other than those for which it was originally created.

• Learn from an expert

  • Recorded presentation from Mark Wilkinson: https://youtu.be/c8fZaGU3d0A

• More Information

  • https://www.w3.org/TR/rdf11-primer/

Pros and Cons

• Cost to setup

  • Free to implement yourself, you can hire a third party to manage and implement everything

• Pros

  • Shallot allows for privacy-preserving, pre-approved queries to be run over multiple resources, allowing for different privacy levels
  • YARRRML allows any database that can export in tabular format to become FAIR with the use of its templates
  • RDF is backed by Tim Berners-Lee and W3C, and was designed to comply with the FAIR principles. After the initial time cost of creating models, implementation is easy

• Cons

  • The usage of limited, pre-approved queries requires of an organism that checks if the requirements from all stakeholders are met
  • Semantic models can be hard to set-up.

Example use cases

• Sharing Limited by International Treaties

  • A research center wants to share phenotipic experiment and -omics data, but needs to do so in compliance with the international treaties that govern the sharing of that kind of information

FAIR Principles

• Findability - Metadata and data should be easy to find for both humans and computers.

  • F1 - (Meta)data are assigned a globally unique and persistent identifier

    RDF Enforces the use of globally unique persistent identifiers

  • F2 - Data are described with rich metadata (defined by R1 below)

    Uses widely-used standards for metadata

• Accessibility - Once the user finds the required data, it should be clear how the data can be fully accessed.

  • A1 - (Meta)data are retrievable by their identifier using a standardized communications protocol

    Any SPARQL based tools allow for standardized retrieval of data and metadata

  • A1.1 - The protocol is open, free, and universally implementable

    SPARQL is free and open source

• Interoperability - The data should easily interoperate with other data, as well as applications for analysis, storage, and processing.

  • I1 - (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.

    RDF enforces the use of standardized vocabularies like ontologies. RDF itself is formal, accessible, and widespread.

  • I3 - (Meta)data include qualified references to other (meta)data

    RDF is base on the linked data ideologies, which requires references between data

• Reusability - Metadata and data should be well-described so that they can be replicated and/or combined in different settings.

  • R1 - (Meta)data are richly described with a plurality of accurate and relevant attributes

    RDF gives importance to the licensing and provenance of the data, using community standards.

  • R1.3 - (Meta)data meet domain-relevant community standards

    RDF is very flexible, allowing data structures to conform to community standards