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Data Infrastructure for Common Challenges
  • Data Landscape Playbook
    • Data Landscape Playbook: status
    • What is this playbook for?
    • Who is this playbook for?
  • Play one: Explore the problem and how data can address it
    • Define how improving access to data can help address your problem
    • What type of data infrastructure does the initiative aim to create or maintain?
      • Build or manage data assets
      • Create or adopt data standards
      • Build or improve technologies
      • Create guidelines and policies
      • Build or support organisations and communities
    • Carry out initial research and engagement
    • Summary of Play One
  • Play two: Map the data ecosystem
    • Engage with key stakeholders
    • Create an ecosystem map
    • Identify gaps, barriers and opportunities
    • Summary of Play Two
  • Play three: Assess the policy, regulatory and ethical context
    • Understand the legal, regulatory and policy context of the initiative
    • Understand the ethical issues impacting your initiative
    • Summary of Play Three
  • Play four: Assess the existing data infrastructure
    • Make a data inventory
    • Assess open standards for data
    • Assess data skills and literacies
    • Summary of Play Four
  • Play five: Plan for impact when designing your data initiative
    • Plan an impactful initiative
    • Identify risks, assumptions and dependencies
    • Sketch your evaluation framework
    • Summary of Play Five
  • What comes next?
  • Acknowledgements
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  1. Play one: Explore the problem and how data can address it
  2. What type of data infrastructure does the initiative aim to create or maintain?

Build or manage data assets

PreviousWhat type of data infrastructure does the initiative aim to create or maintain?NextCreate or adopt data standards

Last updated 4 years ago

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Data assets include:

  • : unique labels that we assign to things. These are often considered the first building block of data infrastructure. They provide a clear point of reference for things we might want to collect and publish data about, which helps people to know when they are talking about the same thing, and join datasets together.

  • : lists of reference data that help to improve consistency and quality in how data is published and used. They help us to build confidence and trust in data by clarifying where different data stewards are referring to the same things in the same way.

  • Datasets: can be data collected directly for research or monitoring purposes, a combination of data collected by others, or the output of a model or analysis. When we think about data assets, we are most likely to think about datasets. At the ODI, we think of data as existing on a , from closed to open.

The Data Spectrum. Image credit: ODI

Some example of data access initiatives building data assets include:

– customers use Thomson Reuter’s open identifiers to gain new analytical insight and to build new products and services

– pharmaceutical companies share data from their global antibiotic surveillance studies to build a more complete picture of the antimicrobial resistance

– researchers access the Broad Institute’s dataset of thousands of market approved drugs to identify ways drugs can be repurposed to solve additional health problems

Thomson Reuters’ data services go open
AMR Research Initiative
Drug Repurposing Hub
Identifiers
Registers
spectrum