Store
We need to maintain our data in a structure and location that makes it readily available to the whole University community.
The Data Strategy will create a well-defined set of methods for determining the platform where online data is stored and processed, how data is archived for disaster recovery and how it is protected.
We need to consider:
- data distributed across multiple locations including the cloud, University systems and multiple desktops
- privacy and protection
- duplication
Because privacy and data protection legislation makes it a risk to store multiple copies of data, we must track all existing copies of datasets. The Data Strategy will make data easily available, which will remove the need for individuals to create duplicate copies. An integration programme will standardise, combine and remove duplicate data from multiple locations.
Processing data is no longer the sole responsibility of the IT service; it has become an end-user activity. The Data Strategy will include training to support all users to become self- sufficient data processors.
Data Principles
These data principles will be used by the Data Design Authority (DDA – see Component 5. Govern) to support and guide the development of systems and applications.
| Item | Principle | Description |
|---|---|---|
| 1 | All data is valuable | Accurate data contributes to the delivery of safe, compassionate and effective education and research, and informs decision making. |
| 2 | All data has an owner | It is important that we ensure we understand what role we are fulfilling in relation to the data we hold or access. |
| 3 | Data must be understood | Data is a representation of some aspect of reality. It can only contribute to valuable outcomes if it is properly understood. |
| 4 | Data must have a known purpose | Data purposes must be recorded. Data may have multiple purposes but there will usually be one primary reason the data is valuable to us. If we don’t know why we need data, we shouldn’t gather it. |
| 5 | Data must have context | To be able to understand data and reuse it effectively it is important that we understand some basics about the data itself. |
| 6 | Data must have known quality | So that it can be used to drive design and decision making it is important that the quality of data is recorded. |
| 7 | Data should be open | Where possible we will work to open-data and cross-government standards to avoid quality erosion through unecessary transformation or translation. |
| 8 | Data use is traceable, legal and ethical | Our data usage will be bound within the legal and ethical framework we work within. |
| 9 | Use data to prompt appropriate action | Data should be used to initiate traceable action when appropriate. Over time we will be able to identify patterns in problematic data. The nature and severity of problems associated with data patterns will prompt action within our systems. |
| 10 | Data should be digital by default | Where possible and appropriate we will digitise physical data to maximise its utility. |
| 11 | Reuse data, don’t recreate it | To reuse data effectively it must be in media and formats that assist its reuse with minimum effort. |