|Basic Metadata Registry Objects
|A Conceptual Domain describes a set of ideas that can be recorded using codes when storing data. When linked to multiple Value Domains, a Conceptual Domain can be used to find similarities in different code sets.
|A Data Element is a precise way of defining how a piece of data is recorded for a specific set of objects, using reusable metadata components. Data Elements are composed of a Data Element Concept, which describes the meaning of the data, and a Value Domain which describes how the data is recorded.
|Data Element Concepts
|A Data Element Concept defines an idea that could be recorded by data, without specifying how it would be stored or measured. Data Element Concepts are composed of an Object Class, which describes the thing of interest, and a Property that defines which attribute of the thing would be recorded. Data Element Concepts can be referenced by multiple different Data Elements that each specify the Value Domain used to record the data.
|Data Element Derivations
|A Data Element Derivation describes a standardised rule or equation that transforms a set of input Data Elements to produce a set of output Data Elements. application of a derivation rule to one or more input
|A Data Type describes a way of storing a specific form of data within a system.
|An Object Class defines a way of identifying or classifying a set of real objects, ideas or events that all share common measurable attributes.
|A Property is an attribute common to all members of a set of things defined by an Object Class.
|A Value Domain describes how to record the measurement of a particular type of data, either using a coded list of values or a description of the possible values. Value Domains can be linked to Data Elements that all share a common way of recording data, and its values can be linked to a Conceptual Domain to provide additional context.
A list of mutually exclusive categories representing values of the classification variable.
|Data set registration and management
|A Data Set describes a record of data, including any location or time boundaries for the data, that has been captured and is available for use under a specific licence. A Data Set may be included in a Data Catalog, and can reference multiple Distributions that record different parts or formats of the data that are available to download.
|Data Set Specifications
|A Data Set Specification describes an agreement to collect an ideal standard of data. A Data Set Specification may reference other Data Set Specifications or Data Elements to describe the data that should be collected under the agreement.
|A Distribution describes the structure and format of a specific downloadable collection of data. Multiple Distributions that capture different parts of data or provide different formats for data may be grouped into a single Data Set.
|ISO 11179 Edition 2 Backwards Compatibility Objects
|Performance Indicator Management Objects
|A Framework describes an organised collection of targets and strategic outcomes to assess a broad policy area. A Framework can collect multiple Indicator Sets and Outcome Areas to provide a complete understanding of the assessment of progress to a group of related goals.
|An indicator describes a measure that is regularly reported for tracking performance of a process or policy, and provides relevant and actionable information about system performance. Indicators can reference Data Elements when defining their component parts, such as numerators and denominators, and Indicators may be linked across multiple Indicator Sets to track performance over time.
|An Indicator Set describes a collection of targets and objectives. An Indicator Set collects multiple Indicators with common targets that are reported on together.
|An Outcome Area describes a strategic target or standard for a process or policy that may not be able to be measured directly or efficiently. An Outcome Area may be assesed by performance against a measurable Indicator.
|A Data Quality Statement records any known issues that may be related to a data asset. A Data Quality Statement assesses data against seven key factors: Institutional Environment, Relevance, Timeliness, Accuracy, Coherence, Interpretability & Accessibility.
|Business Glossary Objects
|A Glossary Item records a business term that is commonly used within the metadata registry. A collection of Glossary Items is commonly referred to as a business glossary.
|Object Class Specialisations
|An Object Class Specialisation describes a relationship between Object Classes, where multiple specialised Object Classes are all contained by a common broader Object Class.
|Relation and Link management