Difference between revisions of "Category:Fusion Data Mapper"
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==== Use Case ==== | ==== Use Case ==== | ||
The primary use case is transforming single dimensional datasets to SDMX multi-dimensional | The primary use case is transforming single dimensional datasets to SDMX multi-dimensional | ||
| − | structures. | + | structures. Single dimensional datasets are those with a single unique identifier for each series (e.g. Series Code) |
| + | such as created by FAME or similar time-series production systems. One-to-one transformations only are supported by this version of the Fusion Data Mapper. | ||
| − | + | The transformation is performed by Fusion Registry using SDMX Structure Mapping. Fusion Data Mapper provides an easy-to-use user interface for defining and management the mapping rules. | |
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| − | |||
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| − | The transformation is performed by Fusion Registry using SDMX Structure Mapping. Fusion Data | ||
| − | Mapper provides an easy-to-use user interface for defining and management the mapping rules. | ||
==== Audience ==== | ==== Audience ==== | ||
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* System Administrators – those responsible for administering Fusion Registry 9 as part of the integrated statistical data and metadata system, and managing the Time Series Database as the source of observation data. | * System Administrators – those responsible for administering Fusion Registry 9 as part of the integrated statistical data and metadata system, and managing the Time Series Database as the source of observation data. | ||
==== Prerequisites ==== | ==== Prerequisites ==== | ||
| − | Readers are assumed to have an understanding of basic SDMX principles and the purpose of the | + | Readers are assumed to have an understanding of basic SDMX principles and the purpose of the main SDMX structural metadata artefacts including Concepts, Codes and Codelists, Categories, Data |
| − | main SDMX structural metadata artefacts including Concepts, Codes and Codelists, Categories, Data | ||
Structure Definitions (DSDs), Dataflows, Provision Agreements, Structure Sets and Dataflow Maps. | Structure Definitions (DSDs), Dataflows, Provision Agreements, Structure Sets and Dataflow Maps. | ||
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==== Terminology ==== | ==== Terminology ==== | ||
{| | {| | ||
|-style="vertical-align: top;" | |-style="vertical-align: top;" | ||
| Dataset || Dataset refers to a named collection of series that typically all fall under a specific topic, for instance ‘National Accounts’. In Fusion Registry, an SDMX Dataflow represents a dataset. | | Dataset || Dataset refers to a named collection of series that typically all fall under a specific topic, for instance ‘National Accounts’. In Fusion Registry, an SDMX Dataflow represents a dataset. | ||
| − | |||
| − | |||
|-style="vertical-align: top;" | |-style="vertical-align: top;" | ||
| Mapped Dataset|| A Mapped Dataset is an SDMX Dataflow where data is taken from a ‘source’ Dataflow and transformed to different dimensionality using defined mapping rules. The Fusion Data Mapper manages these mapping rules. | | Mapped Dataset|| A Mapped Dataset is an SDMX Dataflow where data is taken from a ‘source’ Dataflow and transformed to different dimensionality using defined mapping rules. The Fusion Data Mapper manages these mapping rules. | ||
In this document, the source Dataflow is assumed to be observation data from the Time Series Database which is described by a Data Structure Definition having only SERIES_CODE, TIME_PERIOD and OBS_VALUE dimensions. | In this document, the source Dataflow is assumed to be observation data from the Time Series Database which is described by a Data Structure Definition having only SERIES_CODE, TIME_PERIOD and OBS_VALUE dimensions. | ||
| − | |||
|-style="vertical-align: top;" | |-style="vertical-align: top;" | ||
| Time Series Database|| The source of time series observation data without metadata that Fusion Registry maps to Mapped Datasets using the defined mapping rules. | | Time Series Database|| The source of time series observation data without metadata that Fusion Registry maps to Mapped Datasets using the defined mapping rules. | ||
|} | |} | ||
Revision as of 06:25, 11 September 2023
Overview
Fusion Data Mapper is a web interface for mapping uni-dimensional series to multi-dimensional. The main use case is transforming FAME style series with a single series code dimension to multi-dimensional series using 1-to-1 or 1-to-many SDMX structure mapping.
Use Case
The primary use case is transforming single dimensional datasets to SDMX multi-dimensional structures. Single dimensional datasets are those with a single unique identifier for each series (e.g. Series Code) such as created by FAME or similar time-series production systems. One-to-one transformations only are supported by this version of the Fusion Data Mapper.
The transformation is performed by Fusion Registry using SDMX Structure Mapping. Fusion Data Mapper provides an easy-to-use user interface for defining and management the mapping rules.
Audience
- Metadata Managers – those responsible for managing the metadata mappings on the Bank’s catalogue of time series on a day to day basis.
- Metadata Superusers – those responsible for managing the core structural metadata including Agencies, Concepts, Data Structure Definitions and Codelists.
- System Administrators – those responsible for administering Fusion Registry 9 as part of the integrated statistical data and metadata system, and managing the Time Series Database as the source of observation data.
Prerequisites
Readers are assumed to have an understanding of basic SDMX principles and the purpose of the main SDMX structural metadata artefacts including Concepts, Codes and Codelists, Categories, Data Structure Definitions (DSDs), Dataflows, Provision Agreements, Structure Sets and Dataflow Maps.
Terminology
| Dataset | Dataset refers to a named collection of series that typically all fall under a specific topic, for instance ‘National Accounts’. In Fusion Registry, an SDMX Dataflow represents a dataset. |
| Mapped Dataset | A Mapped Dataset is an SDMX Dataflow where data is taken from a ‘source’ Dataflow and transformed to different dimensionality using defined mapping rules. The Fusion Data Mapper manages these mapping rules.
In this document, the source Dataflow is assumed to be observation data from the Time Series Database which is described by a Data Structure Definition having only SERIES_CODE, TIME_PERIOD and OBS_VALUE dimensions. |
| Time Series Database | The source of time series observation data without metadata that Fusion Registry maps to Mapped Datasets using the defined mapping rules. |
Pages in category "Fusion Data Mapper"
The following 24 pages are in this category, out of 24 total.
A
B
C
- Changing the Dimensionality of a Dataset – Fusion Data Mapper
- Clone a Dataset – Fusion Data Mapper
- Cloning a dataset - Fusion Data Mapper
- Codelists - Adding and Removing Codes – Fusion Data Mapper
- Codelists – Adding and Changing Multilingual Code Names with Impact Analysis - Fusion Data Mapper
- Content Security Caveats – Fusion Data Mapper
- Content Security Metadata Management Use Cases – Fusion Data Mapper
