Data Management and Governance

Data management and governance is a key part of trustworthy, transparent data-centric manufacturing. Any insights will be dependent on the data used and so for auditing purposes it is essential that the data be managed and governed appropriately. In many manufacturing settings, especially those with safety concerns there will be a minimum requirement to keep data for a certain length of time. To be most effective, organisations should have consistent data management and governance implemented. We have therefore provided a template for data management based on the Microsoft Team Data Science data definitions. 

Good data management includes:

• what data to collect,

• how to collect the correct data,

• assessing the quality of the data,

• where and how to store data,

• who will access the data and how,

• what metadata or schema will be used to ensure information about the data is kept.

As well as successful identification and implementation of the above, it is also necessary to record the information. Typically, this is done using a data management plan but most available resources are long documents that are difficult to follow (although they do contain all the relevant information). We have attempted to streamline these documents and include an element of version control in the process. 

A good data management strategy will also identify those that are responsible for the data and its governance. At the University of Sheffield (and beyond) there are Data Stewards that support and advocate for good data management and a network that aims to provide support across all groups. The AMRC is part of the Data Steward Network at TUoS.