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Similar to 2016 SDMX Experts meeting, Making data discoverable in SDMX, Andreas Hake
2016 SDMX Experts meeting, Making data discoverable in SDMX, Andreas Hake
- 1. Reproductions of thismaterial, or any parts of it, should refer to the IMF Statistics Department as the source. IMF Statistics Department Andreas Hake Division Chief, IMF Statistics Department 2016 SDMX Expert Group Meeting Aguascalientes, Mexico, October 17-20, 2016 1 Making data discoverable in SDMX Managing metadata with an SDMX registry
- 2. IMF Statistics Department Evolutionof data dissemination diagram 2 Human Readable Human Readable and Indexed Human, Machine Readable and Indexed Human, Machine Readable, Rich Metadata- driven and Indexed 10/18/2016
- 3. IMF Statistics Department HumanReadable Data Dissemination 3 Country 1 Country 2 10/18/2016
- 4. IMF Statistics Department HumanReadable and Indexed 410/18/2016
- 5. IMF Statistics Department Human& Machine Readable and Indexed 510/18/2016
- 6. IMF Statistics Department Human& Machine Readable, Indexed and Rich Metadata-driven Datasets Metadata-driven datasets for • an SDMX registry enabled • machine to machine • automated data exchange SDMX structures help making data more discoverable • Data Structures Definition (DSD), • Provision Agreements, etc.. SDMX notifications services reduce data exchange delay between data provider and consumer Data is more discoverable 610/18/2016
- 7. IMF Statistics Department IMFSDMX Central 710/18/2016
- 8. IMF Statistics Department ConvertExcel to SDMX – (1) Load 810/18/2016
- 9. IMF Statistics Department ConvertExcel to SDMX – (2) Transform 1010/18/2016
- 10. IMF Statistics Department PublishSDMX datasets to the Cloud 1110/18/2016
- 11. IMF Statistics Department RegisterSDMX Files (here: SDDS Plus) 1210/18/2016
- 12. IMF Statistics Department BrowseSDMX datasets 1310/18/2016
- 13. IMF Statistics Department ManageSDMX artifacts 1410/18/2016
- 14. IMF Statistics Department IntegratedSDMX notification service 1510/18/2016
- 15. IMF Statistics Department THANKYOU 1610/18/2016 Andreas Hake ahake@imf.org +1 (202) 623 8130
Editor's Notes
- #4 For hundreds of years, tables were the main way to disseminate statistical data In the early years of the internet, data came online, but still mainly in tables and other two-dimensional presentations (e.g. charts and maps) These are so popular because they are easy for humans to understand But finding the right table or chart can be tricky… Data dissemination has evolved to a point where rich, metadata-driven discovery can help users (human or machine) find and access data quickly
- #5 As the internet developed, disseminated datasets became bigger and multidimensional These datasets were indexed in two ways: Internally, so human users could search for the variables of interest Externally, so human users could search for the right datasets The SDDS National Summary Data Page (NSDP) is an example of such an index
- #6 Implementation of SDMX provides a standard for providing machine readable data Early SDMX versions focused on providing a structure for internal definition of datasets Dissemination mostly by bilateral exchange or posting or hosting datasets
- #8 More than just a SDMX registry fully integrated, metadata-driven service using the SDMX standard as the foundation enhance data dissemination process building on the SDMX information model used to describe datasets by defining the dimensionality of a dataset allowable content for each of the dimensions Provision agreements are used to define which data complier or agency supplies which data, aiding discovery Registrations can drive notifications, supporting automated machine retrieval of data Human users can browse all datasets registered with SDMX Central, no matter where the SDMX data resides
- #12 Load Data to Validate, Transform, Publish, Register and Receive SDMX notification