MAST(Metadata Analysis Standards Teamwork) Methodology and IDEAL Framework

The MAST at Aristotle Metadata has come up with "The MAST Methodology," a human-centric approach to data based on our proven experience delivering change programs to improve data governance.
The Metadata Analysis Standards Team (MAST) uses the MAST™ methodology to help clients analyse and create metadata in Aristotle (see below). This methodology can be replicated by organisations to develop collaborative metadata practices.

The MAST Manifesto

The MAST Methodology

The MAST methodology uses the IDEAL Framework to provide a consistent organisational approach to metadata management and data governance, and is underpinned by of the Inventory, Documentation, Endorsement, Audit and Leadership (IDEAL™) metadata framework (see below).

Goals, actions and pitfalls when implementing the IDEAL Framework

The IDEAL framework is an iterative process that recognises that quality metadata promotes data literacy within an organisation.
  • I (Investigate and Inventory Data)

In this phase a client organisation starts to consider the benefits of documenting their metadata in a more discoverable way.
For example, an organisation may want a better understanding of how their organisational data is collected and managed. This includes having more clarity about definitions and duplication of content, as well as greater visibility of their metadata.
MAST’s role at this stage is to show a potential client how Aristotle can help them. This can be customised to an organisation’s needs and level of metadata maturity. Some organisations may prefer a pilot study that enables them to see the benefits of a metadata registry before committing to a large-scale metadata project.
MAST may research organisational data assets during the investigation phase. This includes Word and/or PDF documents, and published data on their website. A sample of the client’s data assets can be displayed in an Excel spreadsheet to highlight the benefits of metadata management within their organisation.
The inventory stage will help clients to focus on those assets that have the most value to the organisation and therefore inform the scope of the work.
  • D (Document data and metadata)
The documentation phase aims to increase an organisation’s understanding of the structure and content of their data. This involves migrating information from multiple locations into a single metadata repository based on an international standard for metadata registries, ISO 11179.
The source metadata is often contained in spreadsheets, Word documents, data dictionaries and/or databases. There may be duplication of content, given that client organisations often use several applications across an organisation in collecting data. This step includes to capturing the information into machine readable formats.
During this phase, MAST support will be tailored to meet client needs. In some cases, MAST may do the documentation in Aristotle for the client. Other organisations may document their data in Aristotle independently, and seeking help on an ‘as needed’ basis.
  • E (Endorse and publish metadata)
After completing the documentation phase, the content can be made visible for peer review. Sharing content allows it to be explored, assessing issues such as fitness for purpose, redundancies, and duplication of content.
Client organisations have control over the processes for making their metadata visible to others. Assigning registration statuses to metadata makes it visible and allows stakeholders to approve the content.
Sharing and approval of content occurs through registration authorities within Aristotle. Registration authorities are groups of people with authority to approve metadata. They include committees or agencies with specific governance arrangements.
  • A (Audit and Harmonise terms)
The audit stage of the IDEAL™ framework aims to standardise the representation of organisational data. Although this may be challenging in practical terms, the iterative nature of IDEAL™ means that it may be achievable in the future.
Stakeholder engagement is key to improving the comparability and interoperability of the metadata. This involves asking questions about how users interpret data and terms and seeking consensus about content. MAST can provide guidance on quality metadata based on the ISO 11179 standard to help with decision-making.
This stage includes harmonising content by finding duplicate content and redundant metadata. MAST can help this process by highlighting metadata issues and making recommendations for remedial action.
  • L (Leadership and long-term strategy)
Implementing the IDEAL framework within an organisation will help users to have a better understanding of their data. Teams who work in this area can be leaders in educating users about the benefits of a centralised metadata repository that can be updated as business requirements change.
Aristotle promotes leadership in metadata through stewardship organisations. These organisations are responsible for maintaining the accuracy and relevance of content within their metadata registry. They provide a leadership role for the long-term management of organisational metadata.
Other long-term strategies include examining and disposing of data which is not being used by or within the client organisation. This role may be undertaken by a data consultancy organisation, although there is scope for Aristotle to do this work in the future.