Data transparency and open data sharing

What do we mean by data transparency and open data sharing?

The practice of maximising the transparency with which data is processed and making certain data sets freely available for wider use ensuring accessibility, re-usability, interoperability, and timeliness of release.

Open data sharing enables individuals, organisations, and others to access and use data sets for a variety of purposes and can aid innovation.

Essential for:

• Encouraging data innovation.
• Building trust in data use.

Knowledge

• Knowledge of data quality management
• Understanding of legal and ethical considerations, including data regulations, data protection, privacy, and equality laws.
• Understanding of accessible data formats including CSV, JSON, XML.
• Knowledge of open data licensing – e.g. Creative Commons.

Skills

Able to:

• Think strategically: Recognise the value of open data and its role in enabling data led innovation.
• Review legal and ethical considerations: Prior to determining which data to release and to inform how this is achieved, ensuring compliance with the law and awareness of ethical risks.
• Prepare data for open release: Including data quality, anonymisation of personally identifiable information, accessibility, re-usability, appropriate use of metadata and timeliness of release.
• Document the data: Creating comprehensive data definitions and a purpose statement, including any limitations or constraints.
• Apply version control: To ensure that updates are easily comprehensible, and changes can be tracked over time.
• Create licence definitions: Clearly specifying the terms on which the open data can be used and shared, selecting an open licence that aligns to the desired level of transparency.
• Determine the publishing route: Publishing on the most appropriate public platform or repository that enables open data sharing to encourage maximum usage, ensuring ease of download / access.
• Facilitate findability: Making the dataset discoverable by using keywords, tags, and labels.
• Encourage use: Actively promote the use of the dataset or sets, including celebrating and promoting how they are being used.
• Encourage feedback: Provide a mechanism, or mechanisms, for users to feed back on the usefulness of the data, encouraging further collaboration.
• Communicate and collaborate effectively: With stakeholders at all levels, including technical and non-technical teams.
• Manage risk: Understand the risks associated with open data sharing and apply appropriate controls to ensure lawful processing and ethical use, ensuring risks are documented, managed, and mitigated effectively.

Behaviours

• Collaborative
• Analytical
• Solution focused
• Inclusive
• Committed to continual learning