DOCSLIB.ORG

SDMX Metadata Structure

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
SDMX Metadata Structure SDMX GLOBAL CONFERENCE, PARIS, 19-21 January 2009 THE IMPLEMENTATION OF THE SDMX CONTENT-ORIENTED GUIDELINES WITH REGARD TO METADATA EXCHANGE IN THE EUROPEAN STATISTICAL SYSTEM (August Götzfried and Marco Pellegrino, Eurostat) This paper describes the implementation of a more advanced framework for metadata production, exchange and sharing making use of the new SDMX content-oriented guidelines published in January 2009. The combined use of technical standards and content guidelines can greatly support the standardisation, exchange, web dissemination and re-use of structural and reference metadata1 within the European Statistical System (ESS). With regard to structural metadata, Eurostat is not only implementing the content-oriented guidelines, but is also undertaking further harmonisation efforts for additional sets of metadata which are offered to be used at SDMX level in a second phase. With regard to reference metadata, the use of the Cross- domain Concepts (version 2009) is leading to the implementation of a Europe-wide standard for reference metadata called ESMS, Euro-SDMX Metadata Structure. The ESMS, currently being implemented within Eurostat, will be successively used for reporting metadata to Eurostat and for exchanging metadata between international organisations, for instance between Eurostat, the European Central Bank, the IMF and the OECD. The SDMX work has progressed considerably, in 2008, but more still needs to be done for taking advantage of the full potential that SDMX standards and content guidelines provide. 1. Background: Using SDMX standards for improving metadata exchange The dissemination of reference metadata on Eurostat's web site has considerably increased since the implementation of the free dissemination policy, in 2004. As more and more data got freely disseminated, metadata files also needed to keep pace. These metadata files, based on the SDDS standard, were explaining data content, methodology, re-use precautions and overall quality, providing users with a standard template across all of the statistical domains. The visibility of these metadata was high since the start (statistics on web usage show an average of more than 3000 consultations of reference metadata files per day on Eurostat's web site). A policy for central quality monitoring of the contents of the metadata files was put in place, together with training initiatives and specific actions for increasing the metadata coverage. In spite of this success, users are still confronted with a series of problems when trying to retrieve comparable methodological information per statistical domain for Eurostat, on one hand, and for different countries on the other hand. The European Statistical System as a whole still does not provide users with a common set of standardised, comparable and re-usable reference metadata describing both European statistics (produced by Eurostat) and national statistics produced by EU Member states or other associated countries. Reference metadata collected for countries are in most cases non-standardised and follow different structures, normally determined by the managers of the respective statistical domain. Even the SDDS, implemented by the IMF, hardly cover 5% of the whole dissemination of a statistical institute. 1 In SDMX, "structural metadata" are those metadata acting as identifiers and descriptors of the data, such as names of variables or dimensions of statistical cubes. Structural metadata must be associated with the data, otherwise it becomes impossible to identify, retrieve and browse the data. "Reference metadata" are metadata that describe the contents and the quality of the statistical data (concepts used, metadata, describing methods used for the generation of the data, and metadata, describing the different quality dimensions of the resulting statistics, e.g. timeliness, accuracy). While these metadata exist and may be exchanged independent of the data and its structural metadata, they are often linked (“referenced”) to data. 1 What is more, according to our assessment, many SDDS-based reference metadata are quite weak with regard to information on national statistical processes and on data quality. For these reasons, the standardisation process needed to be accelerated, so that comparable data and metadata could be made available more easily, reducing redundancies, minimising reporting efforts and establishing a stronger coordination of metadata requirements. These tasks involved the development of more advanced metadata standards in both the IT area (system architecture and tools) and in metadata content. And this is where SDMX fits into the picture. While version 1.0 of the SDMX standards was mainly concerned with data sets and its structural definitions, version 2.0 introduced a full metadata support, providing for the attachment of reference metadata to any part of the data tree, as well as for the reporting and exchange of metadata using XML formats. These functionalities can be very useful for supporting data quality initiatives, allowing for a better exchange of quality-related metadata. One of the most important features of the SDMX information model is the specification of formal rules for formatting data and metadata, so that these can be exchanged, read and processed without manual intervention. A web-service, using information about web locations of data and metadata, can navigate, find and automatically process the information for analytical and dissemination purposes, even querying metadata across various sites for retrieving a customised reporting in XML format. Chart 1 (taken from the version 2 package) depicts the essential characteristics supported in the SDMX model for data and metadata reporting. The pivot of this diagram is the Data or Metadata Flow, maintained by the organisation that collects data or metadata. A Data Flow is linked to a “Data Structure Definition” (DSD) while a Metadata flow is linked to a “Metadata Structure Definition” (MSD) which defines the structure of metadata and identifies the data elements to which metadata can be attached. Data or metadata may be made available by many providers and any provider may report or publish data or metadata for several data or metadata flows, according to a Provision Agreement. The Data or Metadata Flow may also be linked to one or more topics (Category) in a subject-matter scheme (Category Scheme). A category scheme provides a way of classifying data for collection, reporting or publication. Chart 1 - SDMX Data and Metadata Reporting 2 The core of the SDMX model for reference metadata is the concept of “Metadata Structure Definition”, which defines: • which metadata concepts are to be reported; • the identity of the metadata concept (for example, a code which may simply be derived from the cross-domain concepts scheme); • the format and representation (textual or coded); • the role in its usage, e.g., mandatory or conditional. Reference metadata may be attached to different object types (for instance a data set, a time series, or an observation). These files are however often attached at a high level (i.e. at data set or statistical domain level, or even at agency level) because the contents of the file often refers to several or even all of the data tables produced on the basis of the respective data set. A Metadata Structure Definition also needs to identify the object the metadata are attached to. For using this model, it was necessary: • to develop and manage standard Metadata Structure Definitions (MSD) compliant with the SDMX version 2.0, using a standardised list of metadata concepts; • to design and develop a set of IT tools allowing the creation and management of reference metadata, using as much as possible information already stored in existing metadata files; • to design and develop a system architecture (based on a registry) for transferring reference metadata to external users and to the web-site, independently on the respective IT platforms. During the course of 2007 and 2008, Eurostat dedicated significant resources to the development of a system architecture and IT tools aimed at supporting data and metadata exchange within the European Statistical System. At the same time, intensive consultations were conducted within several ESS working groups and task-forces, while the SPC (Statistical Programme Committee), the IT Directors' Group and the Directors' meeting expressed their favourable opinion and encouragement on the SDMX implementation. 2. Content-oriented guidelines: a step forward towards statistical standardisation The Content-Oriented Guidelines (COG) finally comes to complements the SDMX Technical Standards with a set of recommended practices for creating interoperable data and metadata across statistical domains. The release of the new package is therefore a big achievement with regard to the international harmonisation of metadata messages. From now on, metadata reports can be structured using the SDMX list of standard concepts – such as "contact", "timeliness", "dissemination format", "classification system", or "comparability" – with a common description and identification, so that IT systems which exchange data and metadata understand what the data or metadata refer to without any big problem in determining the semantic equivalence between concepts. The SDMX COG package comprises the following main elements: SDMX Cross-Domain Concepts: a list of 66 metadata concepts plus a series of sub-concepts, relevant to several statistical domains and recommended for use in data and metadata
Load more

Recommended publications
  • The Statistical Data and Metadata Exchange Standard (SDMX)
    UNITED NATIONS ECONOMIC AND SOCIAL COMMISSION FOR ASIA AND THE PACIFIC Expert Group Meeting: Opportunities and advantages of enhanced collaboration on statistical information management in Asia and the Pacific 20-22 June 2011 Swissotel Nailert Park, Bangkok Tuesday, 21 June 2011 Session 3: Emerging generic business process models and common frameworks and terminology – A basis for practical cooperation? Integrating statistical information systems: The Statistical Data and Metadata eXchange Standard (SDMX) Brian Studman Australian Bureau of Statistics [email protected] Session Overview •SDMX – Background –History – What can it represent – SDMX & Other Standards (particularly DDI) • ABS & SDMX: Integration via IMTP (ABS major business programme) • Using SDMX in the context of GSBPM • Examples of Use: ABS main projects that utilise SDMX • A quick preview of GSIM v 0.1 (if we have time) 1 SDMX • Origins – Bank for International Settlements, European Central Bank, Eurostat, IMF, UN, OECD, and the World Bank (SDMX Consortium) • Format for statistical returns for aggregated data • Version 2.1 (April 2011 public comment) • http://sdmx.org/ (best starting place) • SDMX comes from the international agencies (OECD, IMF, Eurostat, UNSD, World Bank, ECB, BIS) – they get aggregate statistical tables from many countries regularly over time – they wanted to automate and manage the process • they need standard agreed definitions and classifications, standard agreed table structures, standard agreed formats for both data and metadata – They commissioned
    [Show full text]
  • Joint Adb – Unescap Sdmx Capacity Building Initiative Sdmx Starter Kit for National Statistical Agencies
    JOINT ADB – UNESCAP SDMX CAPACITY BUILDING INITIATIVE SDMX STARTER KIT FOR NATIONAL STATISTICAL AGENCIES Version: 5 October 2014 1 FOREWORD The aim of the Starter Kit is to provide a resource for national statistical agencies in countries in the Asia and Pacific region contemplating the implementation of the Statistical Data and Metadata Exchange (SDMX) technical standards and content-oriented guidelines for the exchange of aggregate data and their related methodological information (metadata). It outlines a structured process for the implementation of SDMX by agencies that have little knowledge about SDMX and how they would go about the implementation of the standards and guidelines. In order to avoid duplicating the work of the SDMX sponsoring agencies the Kit makes extensive use of links to existing SDMX background documents and artifacts that have been developed at the global level. The Starter Kit was developed under the auspices of the joint 2014 Asian Development Bank– United Nations Economic and Social Commission for Asia and the Pacific SDMX initiative to improve the efficiency of data and metadata exchange between national statistical agencies in the Asia and Pacific region and international organizations through the ongoing use of SDMX standards. The aim of the joint initiative is to build the capacity of countries in the region to apply SDMX standards through mapping national concepts to specific identified SDMX Data Structure Definitions (DSDs) and Metadata Structure Definitions (MSDs). The initiative also aims at enabling national agencies to determine which, of a range of available tools for SDMX implementation, best meets the needs of the organisation. The basic premise of the Kit is that SDMX implementation must be seen in the context of a wide range of corporate institutional, infrastructure and statistical initiatives currently underway in almost all statistical agencies around the globe to improve the quality and relevance of the service they provide to government and non-government users of their outputs.
    [Show full text]
  • Central Banks' Use of the SDMX Standard
    Irving Fisher Committee on Central Bank Statistics IFC Report No 4 Central banks’ use of the SDMX standard 2015 Survey, conducted by the SDMX Global Conference Organising Committee (this report includes only the central bank responses) March 2016 1 Contributors to the IFC report Bank for International Settlements (BIS) Heinrich Ehrmann Bruno Tissot (IFC Secretariat) Central Bank of the Republic of Turkey (CBRT) Erdem Başer Timur Hülagü This publication is available on the BIS website (www.bis.org). © Bank for International Settlements 2016. All rights reserved. Brief excerpts may be reproduced or translated provided the source is stated. ISSN 1991-7511 (online) ISBN 978-92-9197-480-1 (online) 1 The views expressed in this document reflect those of the contributors and are not necessarily the views of the institutions they represent. Contents 1. Executive summary .......................................................................................................................... 1 2. Background: SDMX ......................................................................................................................... 3 3. Survey findings .................................................................................................................................. 5 Annex A: List of participating central banks and respondents ........................................... 12 Annex B: IFC Questionnaire on central banks’ use of SDMX standard ............................ 14 Annex C: SDMX Roadmap 2020 .....................................................................................................
    [Show full text]
  • Implementor's Guide for Sdmx Format Standards (Version
    STATISTICAL DATA AND METADATA EXCHANGE INITIATIVE IMPLEMENTOR’S GUIDE FOR SDMX FORMAT STANDARDS (VERSION 1.0) STATISTICAL DATA AND METADATA EXCHANGE INITIATIVE 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Initial Release September 2004 26 First Revision December 2004 27 © SDMX 2004 28 http://www.sdmx.org/ 29 30 31 32 33 3 STATISTICAL DATA AND METADATA EXCHANGE INITIATIVE 34 1 INTRODUCTION ............................................................................................................................ 5 35 2 SDMX INFORMATION MODEL FOR FORMAT IMPLEMENTORS .............................................. 5 36 2.1 Introduction...................................................................................................................................................5 37 2.2 Fundamental Parts of the Information Model .................................................................................6 38 2.3 Data Set.....................................................................................................................................................6 39 2.4 Attachment Levels and Data Formats....................................................................................................8 40 2.5 Concepts, Definitions, Properties and Rules.......................................................................................9 41 3 SDMX-ML AND SDMX-EDI: COMPARISON OF EXPRESSIVE CAPABILITIES AND 42 FUNCTION .........................................................................................................................................
    [Show full text]
  • SDMX 2.1 User Guide Aims at Providing Guidance to Users of the Version 2.1 of the Technical Specification, Released in April 2011
    EUROSTAT – SDMX Training – March 2015 UNDERSTANDING SDMX Introduction to a training course March 2015 1 | P a g e EUROSTAT – SDMX Training – March 2015 Table of Contents 1 SDMX in short ................................................................................................. 3 2 Why should you be interested in SDMX? ........................................................... 4 3 Background: origin and purpose of SDMX .......................................................... 5 4 The existing versions of SDMX .......................................................................... 8 5 The SDMX information model .......................................................................... 9 6 Uptake of SDMX within Domains .................................................................... 10 7 How to know more: SDMX Tutorials ............................................................... 12 8 How to know more: the SDMX User Guide ...................................................... 12 Marco Pellegrino (Eurostat) March 2015 2 | P a g e EUROSTAT – SDMX Training – March 2015 What is SDMX This document provides some background information on the SDMX Initiative, the issues which SDMX addresses and the areas in which SDMX is playing a role today. It also provides a description of a training course on the Basics of SDMX, scheduled for GCC-Stat. 1 SDMX in short SDMX provides support for things that are important to statisticians and are often difficult for them to achieve, and it enables tools to be developed to provide support for these things. It does this by providing standard, well-designed formats for holding all of the elements involved in the statistical process and linking them all together in a clear model. The result is an approach that maximises the amount of metadata and statistical context information that can be passed through to statistical clients, maximises the possibility of relating statistics from similar or different sources, and allows for the automation of processes that are often difficult and costly to manage otherwise.
    [Show full text]
  • SDMX Roadmap 2021-2025
    SDMX Roadmap 2021-2025 Executive Summary The Statistical Data and Metadata eXchange (SDMX) is a standard developed to facilitate the exchange of data and metadata in the international statistical community. It is widely used by international organizations, national statistical offices, and other data producing agencies. The development of SDMX is guided by a roadmap that sets forth the objectives for a span of five years. The SDMX Roadmap 2021-2025 (“the Roadmap”) provides a strategic plan for the continuous development of SDMX over the next five years. The Roadmap has two main drivers: addressing a broadening set of needs and improving the usability of the standard. These two drivers come together under the umbrella of the SDMX 3.0 project. The new roadmap continues to group the objectives into four pillars: (i) Implementation, (ii) Simplification, (iii) Modernisation and (iv) Communication. The Roadmap aims to strengthen the implementation of SDMX. SDMX will be expanded to new statistical domains. Existing SDMX packages will be upgraded based on updates of international classification standards. The adoption of established global code-lists and data structure definitions (DSDs) will be encouraged. Finally, SDMX tools will be finalized to facilitate the exchange of referential metadata. Simplification will be required to facilitate the use of SDMX. Main directions of work will be to simplify referential metadata exchange mechanisms, explore links between SDMX and other standards, and develop tools that simplify the complexities of SDMX for novice users. SDMX will be leveraged to modernise statistical processes and IT infrastructure. The development of SDMX 3.0 will incorporate modern features of data management.
    [Show full text]
  • Policy-Making for Research Data in Repositories: a Guide
    Policy-making for Research Data in Repositories: A Guide http://www.disc-uk.org/docs/guide.pdf Image © JupiterImages Corporation 2007 May 2009 Version 1.2 by Ann Green Stuart Macdonald Robin Rice DISC-UK DataShare project Data Information Specialists Committee -UK Table of Contents i. Introduction 3 ii. Acknowledgements 4 iii. How to use this guide 4 1. Content Coverage 5 a. Scope: subjects and languages 5 b. Kinds of research data 5 c. Status of the research data 6 d. Versions 7 e. Data file formats 8 f. Volume and size limitations 10 2. Metadata 13 a. Access to metadata 13 b. Reuse of metadata 13 c. Metadata types and sources 13 d. Metadata schemas 16 3. Submission of Data (Ingest) 18 a. Eligible depositors 18 b. Moderation by repository 19 c. Data quality requirements 19 d. Confidentiality and disclosure 20 e. Embargo status 21 f. Rights and ownership 22 4. Access and Reuse of Data 24 a. Access to data objects 24 b. Use and reuse of data objects 27 c. Tracking users and use statistics 29 5. Preservation of Data 30 a. Retention period 30 b. Functional preservation 30 c. File preservation 30 d. Fixity and authenticity 31 6. Withdrawal of Data and Succession Plans 33 7. Next Steps 34 8. References 35 INTRODUCTION The Policy-making for Research Data in Repositories: A Guide is intended to be used as a decision-making and planning tool for institutions with digital repositories in existence or in development that are considering adding research data to their digital collections.
    [Show full text]
  • Information Model for Format Implementers
    SDMX STANDARDS: SECTION 6 SDMX TECHNICAL NOTES VERSION 2.1 April 2011 © SDMX 2011 http://www.sdmx.org/ Contents 1 Purpose and Structure.....................................................................................1 1.1 Purpose..............................................................................................................1 1.2 Structure.............................................................................................................1 2 General Notes on This Document...................................................................1 3 Guide for SDMX Format Standards ................................................................2 3.1 Introduction.........................................................................................................2 3.2 SDMX Information Model for Format Implementers...........................................2 3.2.1 Introduction....................................................................................................2 3.3 SDMX-ML and SDMX-EDI: Comparison of Expressive Capabilities and Function .......................................................................................................................3 3.3.1 Format Optimizations and Differences ..........................................................3 3.3.2 Data Types ....................................................................................................4 3.4 SDMX-ML and SDMX-EDI Best Practices .........................................................6 3.4.1 Reporting and Dissemination
    [Show full text]
  • Annex 1 Technology Architecture 1 Source Layer
    Annex 1 Technology Architecture The Technology Architecture is the combined set of software, hardware and networks able to develop and support IT services. This is a high-level map or plan of the information assets in an organization, including the physical design of the building that holds the hardware. This annex is intended to be an overview of software packages existing on the market or developed on request in NSIs in order to describe the solutions that would meet NSI needs, implement S-DWH concept and provide the necessary functionality for each S-DWH level. 1 Source layer The Source layer is the level in which we locate all the activities related to storing and managing internal or external data sources. Internal data are from direct data capturing carried out by CAWI, CAPI or CATI while external data are from administrative archives, for example from Customs Agencies, Revenue Agencies, Chambers of Commerce, Social Security Institutes. Generally, data from direct surveys are well-structured so they can flow directly into the integration layer. This is because NSIs have full control of their own applications. Differently, data from others institution’s archives must come into the S-DWH with their metadata in order to be read correctly. In the early days extracting data from source systems, transforming and loading the data to the target data warehouse was done by writing complex codes which with the advent of efficient tools was an inefficient way to process large volumes of complex data in a timely manner. Nowadays ETL (Extract, Transform and Load) is essential component used to load data into data warehouses from the external sources.
    [Show full text]
  • PDF Presentation
    Dexterity: Data Exchange Tools and Standards for Social Sciences Louise Corti, Herve L’Hours, Matthew Woollard (UKDA) Arofan Gregory, Pascal Heus (ODaF) I-Pres, 29-30 September 2008, London Introduction to DExT data exchange models and data conversion tools for primary research data two aims: z a standard format for representing richly encoded qualitative data z conversion tools from proprietary statistical software to open formats Project Environment JISC funded funded by JISC (Joint Information Systems Committee) Capital Programme: Repositories and Preservation (Tools and Innovations strand) small budget for one year – proof of concept Project Environment UKDA z the leading UK social science data archive z documenting, preserving and disseminating data for over 40 years z pioneered the archiving and sharing of qualitative data at national level z commitment to open standards and formats z support to DExT project through testing, maintaining and embedding conversion tools and standards 1. DExT: qualitative data data selected were from the social sciences ‘qualitative’ data: annotated and coded text, multimedia, linked sources z in-depth and semi-structured interviews z focus groups, observations, field notes, case study notes z diaries, open-ended survey questions z personal documents and photographs the data formats are typically found across all domains of primary research ESDS Qualidata z national service providing access to and support for a range of social science qualitative datasets z part of the ESRC funded Economic and Social
    [Show full text]
  • (I) Functions of Metadata in Statistical Production
    The SDMX Istat Framework. Prepared by Mauro Bianchi, Dario Camol and Laura Vignola, ISTAT, Italy I. INTRODUCTION ISTAT in the two last years have been involved in several Eurostat SDMX projects the Eurostat SODI project, "Demography Pilot Project" and recently to the "Census Hub Pilot Project". The experience acquired during those projects has brought the development team in building the SDMX Framework. The idea was to create a new environment to manage the entire data flow that conducts to the reporting of data and reference metadata in SDMX format. The SDMX Framework, released as open source package, is composed by building blocks that can be also used separately, so that other statistical agencies can re-use and integrate them in their environments II. ARCHITECTURE A. The data framework The framework is composed by modules and classes that permit the user to create the environment, load data, create SDMX data file in compact and cross sectional format and the corresponding RSS (pull method without a web service) and make available data by a web service. 1.2 Manager The application Manager is a Client-Server application that creates the structure of the database. This structure is “SDMX compliant” that is the tables created inside the database contains as object the elements belong to the information model of SDMX (concepts, descriptors, code lists, key families). These tables are populated using the structure files, containing the Data Structure Definitions and all the information contained in these files are stored in specific tables created in the first loading and updated in every future loading if necessary.
    [Show full text]
  • The SDMX Service Architecture for the Perspective of a National Statistical
    Meeting of the Joint OECD/UNECE Expert Group on Statistical Data and Metadata Exchange 8-9 March Palais des Nations, UNECE, Geneva, Switzerland The SDMX service architecture for the perspective of a National Statistical Institute Prepared by [Francesco Rizzo, ISTAT Italy; Adam Wronski, Eurostat; Bengt-Ake Lindblad, Eurostat] I. Introduction 1. For several years the SDMX Sponsor Organisations have been developing software and tools in order to facilitate the introduction of SDMX in their countries. 2. Eurostat has been discussing the effectiveness of these tools with the Member States (MSs) during task forces meetings and working groups. Many suggestions from the MSs were collected which led in 2009 to an internal project named "SDMX implementation and support for Member States". The aim of that project was to develop a set of software, organized in re-usable building blocks and tools to help MSs in implementing an SDMX service infrastructure for a more efficient participation to some SDMX projects currently running within the European Statistical System (e.g. European Census Hub project). 3. A prototype was presented during the "Statistics, Telematic Networks & EDI" Working Group (STNE) in June 2009. The participants welcomed with enthusiasm the initiative and encouraged Eurostat to proceed forward. 4. The main objectives of the project can be listed as follows: (a) To support for the Census Hub project and other Eurostat projects; (b) To facilitate SDMX implementations within the MSs with a particular attention to the large PC- AXIS community; (c) To stimulate a "SDMX community of developer". 5. The project deliverables consist essentially of: (a) the SDMX NSI Reference infrastructure document.
    [Show full text]