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| | + | [[Category:FR Core]] |
| | '''SDMX statistical data engine and structural metadata registry.''' | | '''SDMX statistical data engine and structural metadata registry.''' |
| | + | Fusion Registry is for central banks, international organisations, national statistics offices, development banks and regional statistics authorities who need an enterprise SDMX statistical data warehouse for storage of aggregated time series, data cataloguing and public dissemination. |
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| | This is the main engine at the heart of all Fusion-based SDMX systems providing data collection, integration, processing, storage, query execution and time-series calculation services.<br> | | This is the main engine at the heart of all Fusion-based SDMX systems providing data collection, integration, processing, storage, query execution and time-series calculation services.<br> |
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| | * Authoring and maintaining reference metadata | | * Authoring and maintaining reference metadata |
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| − | ==Specification== | + | == More Information == |
| − | {| class="wikitable"
| + | [[Fusion_Registry_Core_Software_Stack | Software Stack]]<br> |
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| − | | Application Type || Server
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| − | | User Interface || Web user interface accessible using a standard web browser [https://demo.metadatatechnology.com/FusionRegistry/overview.html Live Demo]
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| − | | API || SDMX-compliant REST API with proprietary extensions [https://demo.metadatatechnology.com/FusionRegistry/webservice/data.html Data API Example]
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| − | | Technology || Java web application
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| − | | Compatible platforms || Linux, Windows, Mac and other platforms supporting a Java web runtime environment
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| − | | Minimum operating configuration || The minimim list of components required to deploy a Fusion Registry Core service are:<br>
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| − | The Fusion Registry web app (WAR file)<br>
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| − | Java Runtime Environment<br>
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| − | Java web application server (for instance Apache Tomcat)<br>
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| − | SQL database (MySQL, SQL Server or Oracle
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| − | |}
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| − | [[Category:Components and Modules]] | + | [[Fusion_Registry_Editions | Editions]] |
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| − | ==Functionality by Edition==
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| − | {| class="wikitable"
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| − | ! style="width:300px"| !! style="width:150px" | Community !! style="width:150px" | Data Essentials !! style="width:150px" | Enterprise !! style="width:150px" | Cloud
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| − | | Structural Metadata Registry || style="background:#00FF55 | Full|| style="background:#00FF55 | Full || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Data Collection || No || One data provider, pull from registered data sources not supported || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Data Integration || No || Registry managed SQL data stores only || style="background:#00FF55 | Full || Registry managed datastores and registered data sources only
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| − | | Data Storage || No || Registry managed SQL data stores only || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Data Structural Validation || style="background:#00FF55 | Full|| style="background:#00FF55 | Full || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Data Business Rules Validation using Metadata Technology's proprietary expression language|| Arithmetic rules only || Arithmetric rules only || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Data Structural Transformation || style="background:#00FF55 | Full|| style="background:#00FF55 | Full || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Time Series Calculations || No || No || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Data Conversion || SDMX formats only || style="background:#00FF55 | Full || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Data Query Execution Engine || No || style="background:#00FF55 | Full || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Mapped Datasets || No ||style="background:#00FF55 | Full || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Reference Metadata || No || No || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Audit || No || No || style="background:#00FF55 | Full|| style="background:#00FF55 | Full
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| − | | Content Security || No || No || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | SDMX REST API || Structures only || style="background:#00FF55 | Full|| style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | Extended REST API || Validation and transformation only || style="background:#00FF55 | Full || style="background:#00FF55 | Full || style="background:#00FF55 | Full
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| − | | VTL source code repository || colspan="4" | No - Planned for April 2021
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| − | | VTL execution engine || colspan="4" | No - Planned for 2021/2022
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| − | |}
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SDMX statistical data engine and structural metadata registry.
Fusion Registry is for central banks, international organisations, national statistics offices, development banks and regional statistics authorities who need an enterprise SDMX statistical data warehouse for storage of aggregated time series, data cataloguing and public dissemination.
This is the main engine at the heart of all Fusion-based SDMX systems providing data collection, integration, processing, storage, query execution and time-series calculation services.
Its integrated SDMX structural metadata registry acts as the central repository, authoring and maintenance tool for all of the structures including Codelists, Concepts and Data Structure Definitions.
Key Use Cases
- Statistical data warehouse
- Collecting and integrating data from multiple data providers
- Data dissemination - Fusion Registry's SDMX-compliant REST API is suitable for driving a range of dissemination services
- Authoring, maintaining and storing SDMX structural metadata
- Validating SDMX data prior to submission to another organisation
- Converting data between different formats (SDMX to SDMX, non-SDMX to SDMX, SDMX to non-SDMX)
- Transforming the structure of data to different dimensionality and coding schemes using SDMX Structure Mapping (for instance, map a dataset to a simplier DSD with fewer dimensions suitable for publication)
- Transforming single-dimension FAME series into multi-dimensional SDMX series
- Authoring and maintaining reference metadata
More Information
Software Stack
Editions
