Difference between revisions of "Fusion Data Mapper"

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== Overview ==
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[[Category:Fusion Data Mapper]]
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== Overview – Fusion Data Mapper==
 
This document provides guidance and operating procedures for creating and managing mapped
 
This document provides guidance and operating procedures for creating and managing mapped
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datasets using Fusion Registry 9 and the Fusion Data Mapper.
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datasets using Fusion Registry 10 and the Fusion Data Mapper.
 +
 
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'''Use Case'''
  
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====== 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.
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Mapper provides an easy-to-use user interface for defining and management the mapping rules.
 
Mapper provides an easy-to-use user interface for defining and management the mapping rules.
  
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====== Audience ======
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'''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 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.
 
* 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.
 
* 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.
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====== Prerequisites ======
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'''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 ======
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'''Terminology'''
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Dataset Dataset            
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{|
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|-style="vertical-align: top;"
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| 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.
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 +
 
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|-style="vertical-align: top;"
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| 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.
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 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.
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 +
 
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|-style="vertical-align: top;"
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| Time Series Database||   The source of time series observation data without metadata that Fusion Registry maps to Mapped Datasets using the defined mapping rules.
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|}
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==Related Pages==
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For further guidance on Fusion Data Mapper:
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[[Add a Mapped Dataset – Fusion Data Mapper]]
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[[Add Series to a Dataset – Fusion Data Mapper]]
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[[Browse Privileges – Fusion Data Mapper]]
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[[Bulk Maintenance of Metadata Values using Excel Import / Export – Fusion Data Mapper]]
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[[Changing the Dimensionality of a Dataset – Fusion Data Mapper]]
  
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refers to a named collection of series that typically all fall under a
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[[Clone a Dataset – Fusion Data Mapper]]
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specific topic, for instance ‘National Accounts’. In Fusion Registry, an SDMX
 
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Dataflow represents a dataset.
 
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Mapped Dataset A Mapped Dataset is an SDMX Dataflow where data is taken from a
 
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‘source’ Dataflow and transformed to different dimensionality using
 
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defined mapping rules. The Fusion Data Mapper manages these mapping
 
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rules.
 
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In this document, the source Dataflow is assumed to be observation data
 
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from the Time Series Database which is described by a Data Structure
 
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Definition having only SERIES_CODE, TIME_PERIOD and OBS_VALUE
 
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dimensions.
 
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Time Series Database The source of time series observation data without metadata that Fusion
 
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Registry maps to Mapped Datasets using the defined mapping rules.
 
  
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= The Fusion Data Mapper User Interface =
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[[Codelists - Adding and Removing Codes – Fusion Data Mapper]]
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The Fusion Data Mapper is a web user interface providing the following main functions:
 
  
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'''Authenticated users with sufficient structural metadata maintenance privileges'''
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[[Codelists – Adding and Changing Multilingual Code Names with Impact Analysis - Fusion Data Mapper]]
  
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* Add and remove mapped datasets
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[[Content Security Caveats – Fusion Data Mapper]]
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* Add and remove series on mapped datasets
 
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* Interactively set and change the metadata values on a series by series basis
 
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* Export metadata values for selected series to Excel
 
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* Import metadata values for defined series from Excel
 
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* Change code names with impact analysis
 
  
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'''Anonymous or authenticated users with sufficient privileges to view but not change the structural metadata'''
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[[Content Security Metadata Management Use Cases – Fusion Data Mapper]]
  
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* Browse the catalogue of mapped datasets
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[[Default Code Values – Fusion Data Mapper]]
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* Examine the ‘definition’ of a dataset – its dimensionality and list of possible codes for each
 
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* Dimension or Attribute
 
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* Browse the series in each dataset
 
  
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= The Fusion Registry Administration Interface =
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[[Maintaining Metadata Values on Series Interactively using the Web Interface – Fusion Data Mapper]]
  
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The Administration Interface is Fusion Registry’s main web user interface.
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[[Maintenance Privileges – Fusion Data Mapper]]
  
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For the purposes of managing the metadata on mapped datasets, it provides the following functions:
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[[Registering a Series – Fusion Data Mapper]]
  
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'''Authenticated users with sufficient structural metadata management privileges'''
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[[Remove a Mapped Dataset – Fusion Data Mapper]]
  
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* Create and modify SDMX Data Structure Definitions (DSDs)
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[[Removing Series from a Dataset – Fusion Data Mapper]]
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* Create and modify SDMX Concepts
 
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* Create and modify SDMX Codelists
 
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* Add and remove codes from SDMX Codelists
 
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* Register a series (series must be ‘registered’ before they can be mapped in dataset by adding the Series Code and Series Name to the relevant SERIES_CODE Codelist)
 
  
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Refer to the ''Fusion Registry Structural Metadata Management Guide'' for general information on using the Fusion Registry Administration Interface for creating and maintaining core SDMX structure
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[[The Fusion Data Mapper User Interface]]
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metadata artefacts including DSDs, Dataflows, Concepts, Categories and Codelists.
 

Latest revision as of 05:41, 11 September 2023

Overview – Fusion Data Mapper

This document provides guidance and operating procedures for creating and managing mapped datasets using Fusion Registry 10 and the Fusion Data Mapper.

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.

Related Pages

For further guidance on Fusion Data Mapper:

Add a Mapped Dataset – Fusion Data Mapper

Add Series to a Dataset – Fusion Data Mapper

Browse Privileges – Fusion Data Mapper

Bulk Maintenance of Metadata Values using Excel Import / Export – Fusion Data Mapper

Changing the Dimensionality of a Dataset – Fusion Data Mapper

Clone 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

Default Code Values – Fusion Data Mapper

Maintaining Metadata Values on Series Interactively using the Web Interface – Fusion Data Mapper

Maintenance Privileges – Fusion Data Mapper

Registering a Series – Fusion Data Mapper

Remove a Mapped Dataset – Fusion Data Mapper

Removing Series from a Dataset – Fusion Data Mapper

The Fusion Data Mapper User Interface

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