 But precious things need to be handled properly. And that's where data governance comes in. Meet Catherine. She's a medical researcher. Catherine has heard from a colleague about a data set that could really help her project. But there's a problem. When Catherine reached out to the organisation that conducted the research, nobody was certain about data sharing agreements or who even had authority over the data. The data set also hadn't been de-identified. It still had things attached like names, phone numbers, even dates of birth of the people with whom the data was initially associated. It soon became clear that accessing the data set was going to be anything but simple. It seems Catherine could be waiting for months. Let's rewind that scene. She's a medical researcher. Catherine has heard from a colleague about a data set that could really help her project. And the good news? Effective governance has been applied. The patients involved in the initial research consented to further use of the data. The data authority roles were assigned, making clear who's responsible for the data. Even better, procedures defined how it could be accessed and by whom. And in this case, all the personal information of the patients has been removed. In other words, the data was de-identified. So that meant Catherine could log into a secure portal and just download the data set after meeting certain usage and licensing conditions. The defined access procedure was in line with the fair principles for research data, making data findable, accessible, interoperable and reusable. And by the way, that data was the missing piece in Catherine's research puzzle. The fact she was able to make use of it was thanks to good research data governance. So what is data governance? In a research context, the term refers to the established rules that allow for the use and sharing of data. Data governance defines who can take what action upon what data, in what situations and using what methods. Good governance means data can be used with maximum efficiency and impact while ensuring the rights of stakeholders are preserved. Let's face it, the world is awash with data. Using that data responsibly requires a solid and sustainable framework. Good data governance. A process that helps the wider research community maintain data integrity well into the future. Good data governance relies on policy, roles and responsibilities and procedures. Policy components are the high-level strategic decisions usually made at an organisational level. That could include things such as data retention and infrastructure policies, as well as links to relevant privacy legislation and codes of conduct. Roles and responsibilities are at the heart of good data governance. The main role to be defined is the one which has authority over the data, who's accountable, who decides what can be done with the data but what happens when that person leaves the organisation? It all needs to be defined. Procedures are the specific instructions which ensure policies are adhered to. These could include security procedures, quality processes and how access to the data is provided. Policy, roles and responsibilities and procedures. The three critical components to data governance. We all know the value of data. This is the path to using data responsibly and efficiently into the future.