The QUANTUM Maturity assessment

Maturity Assessment

This page presents the QUANTUM Maturity Assessment framework for evaluating the organisational maturity of data holders. It helps readers understand which maturity dimensions are assessed, what each dimension means, and which levels can be assigned when reporting how mature the organisation's data management and data quality processes are.
  • Level 1: InitialA new or undocumented process; unpredictable, poorly controlled, and reactive.
  • Level 2: Emerging / Documented / StructuredThe process is documented sufficiently so that repeating the same steps may be attempted.
  • Level 3: DefinedThe process is defined and confirmed as a standard process.
  • Level 4: ManagedThe process is quantitatively and proactively managed in accordance with agreed-upon metrics.
  • Level 5: OptimisedProcess management includes deliberate process optimisation.
 
1. Data collection process Maturity dimension

Definition: The processes relating to the capture of data from multiple sources for secondary purposes.

Maturity levels 5 levels
  • Level 1: InitialNo data collection or capture process for secondary purposes.
  • Level 2: Emerging / Documented / StructuredAd hoc processes exist for data collection.
  • Level 3: DefinedDefined processes exist for some data collection.
  • Level 4: ManagedDefined processes exist for all data collection and are used for secondary purposes.
  • Level 5: OptimisedProcesses are automated for all data collection, with a focus on continuous process improvement.
2. Data management - governance Maturity dimension

Definition: The level of maturity of the data management processes.

Maturity levels 5 levels
  • Level 1: InitialNo documented data management governance.
  • Level 2: Emerging / Documented / StructuredA documented data management plan covering collection, auditing, and management is available for the dataset.
  • Level 3: DefinedEvidence that the data management plan has been implemented is available.
  • Level 4: ManagedDemonstrated compliance with the data management plan.
  • Level 5: OptimisedExternally verified compliance with the data management plan.
3. Data management - infrastructure Maturity dimension

Definition: The level of implementation and development of the data holder's data management infrastructure.

Maturity levels 5 levels
  • Level 1: InitialNo data management infrastructure.
  • Level 2: Emerging / Documented / StructuredAn emerging data management infrastructure, with some validation and verification.
  • Level 3: DefinedData management infrastructure defined and confirmed as a standard process.
  • Level 4: ManagedData management infrastructure with partially automated, verified and validated real-time data management.
  • Level 5: OptimisedA robust and comprehensive data management infrastructure, with fully automated, verified and validated real-time data management.
4. Data provenance Maturity dimension

Definition: Clear description of the lineage of the dataset, providing transparent and comprehensive documentation of the data pipeline used to obtain the dataset.

Maturity levels 5 levels
  • Level 1: InitialNo documented provenance.
  • Level 2: Emerging / Documented / StructuredThe source of the dataset is documented.
  • Level 3: DefinedThe source of the dataset and any transformations, rules, and exclusions are documented.
  • Level 4: ManagedAll original data items are listed, and all transformations, rules, and exclusions are listed, including their impact.
  • Level 5: OptimisedEarlier versions can be viewed, including the raw or source dataset, and the impact of each stage or step can be reviewed.
5. Data access Maturity dimension

Definition: How well defined and implemented data access processes are, from a legal, ethical, and technical perspective.

Maturity levels 5 levels
  • Level 1: InitialNo data access processes or procedures.
  • Level 2: Emerging / Documented / StructuredProcesses and procedures exist, but they do not respond in a timely and consistent manner.
  • Level 3: DefinedProcesses and procedures exist and respond in a timely and consistent manner.
  • Level 4: ManagedA data access system covers both technical and policy areas, in accordance with agreed metrics.
  • Level 5: OptimisedA comprehensive data access system covers technical, ethical, and policy areas, including allowable uses, API documentation, access and approvals, and is compliant with EU policy.
6. Data analytics environment Maturity dimension

Definition: Analytical services, tooling, and access to secure data environments.

Maturity levels 5 levels
  • Level 1: InitialNo data environment is available.
  • Level 2: Emerging / Documented / StructuredRequested analyses can be undertaken by internal teams and provided back to data requestors in anonymised format.
  • Level 3: DefinedThe dataset can be used in a secure data environment (SDE).
  • Level 4: ManagedThe dataset can be used in an SDE, and other data and tools can be brought in as required.
  • Level 5: OptimisedThe dataset can be used in a federated organised environment.
7. Data enhancement - augmentation Maturity dimension

Definition: The application of various techniques to make data more usable for specific purposes.

Maturity levels 5 levels
  • Level 1: InitialNo data augmentation.
  • Level 2: Emerging / Documented / StructuredSome techniques are used to make data more usable for specific purposes.
  • Level 3: DefinedDefined techniques are used to make data more usable for specific purposes.
  • Level 4: ManagedManaged techniques are used to make data more usable for specific purposes.
  • Level 5: OptimisedComprehensive application of various techniques and mapping to data models, for example OMOP, to make data more usable for specific purposes.
8. Data enhancement - enrichment Maturity dimension

Definition: Data sources enriched, for example, with annotations, image labels, phenomes, derivations, and NLP-derived data labels.

Maturity levels 5 levels
  • Level 1: InitialThe data has no additional derived fields or enriched data.
  • Level 2: Emerging / Documented / StructuredThe data includes additional derived fields or enriched data.
  • Level 3: DefinedThe data includes additional derived fields or enriched data used by other available data sources.
  • Level 4: ManagedThe derived fields or enriched data were generated from, or used by, a peer-reviewed algorithm.
  • Level 5: OptimisedThe data includes derived fields or enriched data from an inter/national report.
9. Data Model Maturity dimension

Definition: Availability of a clear, documented data model that provides structure and standardisation.

Maturity levels 5 levels
  • Level 1: InitialThere is no data model.
  • Level 2: Emerging / Documented / StructuredA known and accepted data model exists, but some key fields are uncoded or stored as free text.
  • Level 3: DefinedKey fields are coded using a local standard and updated over time.
  • Level 4: ManagedKey fields are coded using a national or international standard and updated.
  • Level 5: OptimisedThe data model conforms to an inter/national standard and key fields are codified using a national or international standard.
10. Data Dictionary Maturity dimension

Definition: Provided documented data dictionary and terminologies.

Maturity levels 5 levels
  • Level 1: InitialNo data dictionary.
  • Level 2: Emerging / Documented / StructuredData definitions are available.
  • Level 3: DefinedDefinitions are compiled into a local data dictionary which is available online.
  • Level 4: ManagedThe dictionary relates to national definitions.
  • Level 5: OptimisedThe dictionary is based on international standards and includes mapping.