Describing Statistical registers in SDMX and DDI: A Comparison Arofan Gregory Metadata Technology Eurostat, June 4-6, 2013 Luxembourg.

Slides:



Advertisements
Similar presentations
Status on the Mapping of Metadata Standards
Advertisements

SDMX Data Structure Definition for BPM6 and EBOPS Working Party on International Trade in Goods and Trade in Services Statistics Paris, France November.
Overview of key concepts and features
NESSTAR - the data archive perspective by Margaret Ward UK Data Archive.
SDMX and DDI: How Do They Fit Together in Practical Terms? Arofan Gregory The Open Data Foundation European DDI User’s Group 2011 Gothenburg, Sweden.
Präsentationstitel IAB-ITM Find the right tags in DDI IASSIST 2009, 27th-30th Mai 2009 IAB-ITM Finding the Right Tags in DDI 3.0: A Beginner's Experience.
Codebook Centric to Life-Cycle Centric In the beginning….
Data Management: Documentation & Metadata Types of Documentation.
Copyright © 2010, SAS Institute Inc. All rights reserved. Define.xml - Tips and Techniques for Creating CRT - DDS Julie Maddox Mark Lambrecht SAS Institute.
ESCWA SDMX Workshop Session: Role in the Statistical Lifecycle and Relationship with DDI (Data Documentation Initiative)
WP.5 - DDI-SDMX Integration
WP.5 - DDI-SDMX Integration E.S.S. cross-cutting project on Information Models and Standards Marco Pellegrino, Denis Grofils Eurostat METIS Work Session6-8.
NSI 1 Collect Process AnalyseDisseminate Survey A Survey B Historically statistical organisations have produced specialised business processes and IT.
Survey Data Management and Combined use of DDI and SDMX DDI and SDMX use case Labor Force Statistics.
Metadata management and statistical business process at Statistics Estonia Work Session on Statistical Metadata (Geneva, Switzerland 8-10 May 2013) Kaja.
SDMX and DDI Working Together Technical Workshop 5-7 June 2013
3 rd Annual European DDI Users Group Meeting, 5-6 December 2011 The Ongoing Work for a Technical Vocabulary of DDI and SDMX Terms Marco Pellegrino Eurostat.
4 April 2007METIS Work Session1 Metadata Standards and Their Support of Data Management Needs Daniel W. Gillman Bureau of Labor Statistics Paul Johanis.
CountryData Technologies for Data Exchange SDMX Information Model: An Introduction.
SDMX Standards Relationships to ISO/IEC 11179/CMR Arofan Gregory Chris Nelson Joint UNECE/Eurostat/OECD workshop on statistical metadata (METIS): Geneva.
Technical Overview of SDMX and DDI : Describing Microdata Arofan Gregory Metadata Technology.
SDMX and DDI working together Technical workshop, Luxembourg, June 2013 Use cases for DDI and SDMX.
5 June 2013 SDMX Technical Working Group Luxembourg 1 5 June 2013 SDMX Technical Working Group Luxembourg 1 WP Item 6 The Expressions Language of Banca.
DDI-RDF Leveraging the DDI Model for the Linked Data Web.
Metadata Models in Survey Computing Some Results of MetaNet – WG 2 METIS 2004, Geneva W. Grossmann University of Vienna.
Eurostat Expression language (EL) in Eurostat SDMX - TWG Luxembourg, 5 Jun 2013 Adam Wroński.
Secure Epidemiology Research Platform (SERPent) Kick Start Meeting - April 15 th, 2010 Pascal Heus
Pilot Census in Poland Some Quality Aspects Geneva, 7-9 July 2010 Janusz Dygaszewicz Central Statistical Office POLAND.
Eurostat 1 7a. Practical use case 1: Pesticides Use Project Blanaru Cristina Eurostat Unit B5: “Central data and metadata services” SDMX Basics course,
Survey Data Management and the Combined Use of DDI and SDMX Arofan Gregory Chris Nelson Metadata Technology Eurostat, June
Eurostat SDMX and Global Standardisation Marco Pellegrino Eurostat, Statistical Office of the European Union Bangkok,
Eurostat 4. SDMX: Main objects for data exchange 1 Raynald Palmieri Eurostat Unit B5: “Central data and metadata services” SDMX Basics course, October.
SDMX IT Tools Introduction
2.An overview of SDMX (What is SDMX? Part I) 1 Edward Cook Eurostat Unit B5: “Central data and metadata services” SDMX Basics course, October 2015.
ONLINE SERVICES FOR ACCESSING PHC MICRODATA POPULATION AND HOUSEHOLD CENSUS QUERY SYSTEM APPLICATION (1992, 2002 and 2011 CENSUSES)
7b. SDMX practical use case: Census Hub
EDIT – Eurostat’s editing tool
1 Joint UNECE/EUROSTAT/OECD METIS Work Session (Geneva, March 2010) The On-Going Review of the SDMX Technical Specifications Marco Pellegrino, Håkan.
Eurostat November 2015 Eurostat Unit B3 – IT and standards for data and metadata exchange Jean-Francois LEBLANC Christian SEBASTIAN SDMX IT Tools SDMX.
3 June 2013 SDMX Technical Working Group Luxembourg 1 WP Item 6 Expressions and Calculations.
DDI and GSIM – Impacts, Context, and Future Possibilities
Julia Powell Coast Survey Development Laboratory
Progress Update MSIS: Bratislava, April 2005
SDMX Information Model
The 6th SDMX Global Conference
Cross-domain concepts
2. An overview of SDMX (What is SDMX? Part I)
2. An overview of SDMX (What is SDMX? Part I)
SDMX Information Model: An Introduction
Developing a Data Model
SDMX in the S-DWH Layered Architecture
August Götzfried Eurostat unit B 4
Prepared by Peter Boško, Luxembourg June 2012
Roxane Silberman, Réseau Quételet
SISAI STATISTICAL INFORMATION SYSTEMS ARCHITECTURE AND INTEGRATION
Metadata use in the Statistical Value Chain
Item 7.3 (b) SDMX for UOE data collection
Annegrete Wulff Statistics Denmark
Work Session on Statistical Metadata (Geneva, Switzerland May 2013)
EDIT data validation system Ewa Stacewicz EUROSTAT VALIDATION TEAM
DDI and GSIM – Impacts, Context, and Future Possibilities
Introduction to reference metadata and quality reporting
CSPA Templates for sharing services
5. SDMX: General input requirements
CSPA Templates for sharing services
SDMX: Frequently Asked Questions
Palestinian Central Bureau of Statistics
SDMX Converter Abdulla Gozalov, UNSD.
Presentation transcript:

Describing Statistical registers in SDMX and DDI: A Comparison Arofan Gregory Metadata Technology Eurostat, June 4-6, 2013 Luxembourg

Overview Introduction Technical Approach The SDMX Example The DDI Example Comparison Conclusions

Introduction A document is currently being prepared by Eurostat showing how statistical registers can be marked up in SDMX and also in DDI – This is a practical work, designed to illustrate what each approach looks like – The registers used are the Banca d’Italia Debt Securities Register and the EuroGroup Register (EGR) at Eurostat

Technical Approach A proposal was made about how DDI and SDMX could be used to describe the same data so that the different formats could be transformed losslessly from SDMX to DDI and back – This came out of the UN/ECE SDMX-DDI Dialogue effort This approach uses a specific style of SDMX modelling It also uses a proposed subset of the overall elements of DDI

Technical Approach (Continued) The Banca d’Italia and Eurostat are both able to express their register data using SDMX Other registers have been documented with DDI The approach used here emphasized the interchange between the standards – This may not be as optimized a use of SDMX as that of the Banca d’Italia – It also differs from work within Eurostat modelling the EGR data with SDMX

The SDMX Example The EGR data set is a series of transaction which occur irregularly over time There is a large set of attributes which make up the data which is required to be reported – About the financial institution – About the debt products being registered At any point in time, the existing register can be understood as a rectangular data set

The SDMX Example (Continued) Columns are SDMX measures in a “measure dimension” Rows are individual transactions (product registrations)

Dimensions The approach to dimensionalizing the table is: – The first column in the table identifies transactions (it has an “Indentity” type) – The Measures are a measure dimension – Time would be added as a dimension The fact that some of the attributes could also be defined as dimensions in SDMX is ignored (this is a poor optimization) – All attributes in the register are defined as measures This approach will work for almost any rectangular data file

Supplemental Metadata There is some additional metadata we may wish to have about any given register This can be expressed as SDMX Reference Metadata

The Whole Package To fully describe the registers, we would use – An SDMX DSD – An SDMX Reference Metadata Structure – An SDMX DataSet – A SDMX Reference Metadata Report

The DDI Example The DDI example does not provide a dimensionalized description of the register data – It uses the standard description for describing unit-record data – This looks a lot like the SDMX dimensionalized description – The first column has a transaction identifier (each row is a case) – The columns are the “variables” in the data set As for SDMX, the codelists (in DDI, “Codes” and “Categories”) are described The dataset is not encoded in XML, but is an ASCII file

The DDI Example (Continued) If there was additional information which needed to be exchanged, this would be contained inside the same DDI XML document, using the explicit fields for describing it (methodology, processing information, etc.)

The DDI Package A DDI XML instance with all the metadata An ASCII file

Comparison and Consideration Both techniques – SDMX and DDI – provide an interchangeable way of using the standards to describe the data This is a very typical use of DDI – the register data is just another microdata set This is an expected use of SDMX – the register is seen as a dimensionalized data set – It is a deeply cross-sectional one

Comparison and Consideration (Cont.) A decision to use one technique or the other would be driven by: – What standard an organization uses – What tools provide needed functionality on the data

Comparison and Consideration (Cont.) Using this approach, the data is the same whether it is in SDMX or DDI – There are some conventions about transforming identifiers This approach could apply to any “microdata” set for interchange between DDI and SDMX “Microdata” being understood as any set of unit records with a set of attributes attached – But only a single record structure is allowed within the file

Conclusions It is possible to describe register data with both SDMX and DDI The preference for one approach over the other is not based on the merits of the standards themselves, but on other considerations – Tools and needed functionality – Organizational competencies