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SDMX Global Conference - Addis Ababa, 2-5 October 2017
New developments to have SDMX facing the challenges of the post-truth society SDMX Global Conference - Addis Ababa, 2-5 October 2017 Dr. Patricia Staab, Statistical Information Management, Deutsche Bundesbank
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Post-truth Word of the Year 2016 Oxford Dictionaries Post-Truth
Objective facts, like statistical results, are less influential in shaping public opinion than emotion and personal belief. Post-truth Word of the Year 2016 Oxford Dictionaries How can we improve comprehensibility, visibility and trust in statistical statements? Be able to explain your approach and convince with your results! SDMX and Post-Truth
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Be able to explain your approach
How SDMX can help Explain the data you use Describe, classify, standardize your data. If possible, standardize the methods by which the sources collect their data. If possible, use data from different domains, in order to get diverse input for your statements. This implies that you have to integrate the data. Explain the methods you use Use a “proper” statistical / scientific approach to verify your theories. (“The data lake told me…”, “Big data showed me…” is not a good argument). For this, the semantic understanding of the data is crucial. If possible, provide reproducibility. For example by using standardized research data sets. Convince with your results Visualize your results, illustrate your point, make it interactive and interesting SDMX and Post-Truth
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Example Special Data Dissemination Standard (SDDS) Plus IMF initiative
Strengthening credibility of statistical systems by using internationally harmonized indicators Uses the SDMX standard for Describing, classifying, standardizing the data: uniform SDMX data structure definitions, for worldwide use; provided via a central repository, operated by the IMF Bringing together data from different sources: Decentralized provision of data, by the statistical offices, central banks and other institutions of participating countries; on National Summary Data Pages (NSDP) Generating high-quality reports and graphics: Interactive presentation „Principal Global Indicators (PGI)“ on the web site „Inter-Agency Group on Financial & Economics Statistics (IAG)”; smart data presentation provided by the IMF Data App SDMX and Post-Truth
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„Measuring the Data Universe“
Data Integration Using the Statistics Standard SDMX German version available since July 2017 English version beginning 2018
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Measuring the Data Universe
Why a Book about SDMX? The SDMX community has been aware of a "lack of publicity" regarding SDMX for some time now. Therefore, one measure explicitly named in the current SDMX 2020 Roadmap is "Better communication and capacity building ... Improve communication about SDMX with senior managers, policy-makers, users and bodies that implement SDMX.“ Current discussions in the SMDX community emphasize the need for more easily readable documentation, aimed at non-experts, to foster the distribution of our standard beyond its current range, not only regarding user regions but also regarding topics or industry branches. One goal to by achieved by the Roadmap is "being a standard that is applicable to both public and private sectors." 23/11/2018 Measuring the Data Universe
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Why Do we Propagate a Wider Distribution of the SDMX standard?
A uniform data model in combination with an order system for data is a necessary step on the path to data integration. Current efforts in the field of semantics (i.e., data content classification and description), such as dictionaries, repositories and ontologies, unfold their strength only when they are supported by a strong standard for the ordered storage of data. SDMX can form the bridge to the technical implementation. With a wider adoption, the range of available (commercial or free) SDMX-compatible software solutions will also grow. Or in other words: The impact of standards is driven less by the "genius" of their concept but by how intensively they are being used. 23/11/2018 Measuring the Data Universe
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