Title: IZA%20Data%20Service%20Center%20DDI/SDMX%20Workshop%20Wiesbaden,%20Germany,%20June%2018th%202008%20The%20Data%20Documentation%20Initiative%20(DDI)
1IZA Data Service CenterDDI/SDMX
WorkshopWiesbaden, Germany, June 18th 2008The
Data Documentation Initiative (DDI)
- Arofan Gregory / Pascal Heus
- agregory_at_opendatafoundation.org /
pheus_at_opendatafoundation.org - Open Data Foundation
2Content
- Background on metadata and XML
- Metadata and Microdata
- XML and Microdata the DDI
- DDI 2.0
- DDI 3.0
- DDI 2.0 vs 3.0
- Major stakeholders / initiatives
3Metadata / XML
4What is metadata?
- Common definition Data about Data
5What is XML?
- Today's Universal language on the web
- Purpose is to facilitate sharing of structured
information across information systems - XML stands for eXtensible Markup Language
- eXtensibe ? can be customized
- Markup ? tags, marks, attach attributes to things
- Language ? syntax (grammatical rules)
- HTML (HyperText Markup Language) is a markup
language but not extensible! It is also concerned
about presentation, not content. - XML is a text format (not a binary black box)
- XML is a also a collection of technologies (built
on the XML language) - It is platform independent and is understood by
modern programming languages (C, Java, .NET,
pHp, perl, etc.) - It is both machine and human readable
6Simple XML example
Attributes
ltcataloggt ltbook isbn0385504209gt
lttitlegtDa Vinci Codelt/titlegt
ltauthorgtDan Brownlt/authorgt lt/bookgt
ltbook isbn0553294385 pages352gt
lttitlegtI, robotlt/titlegt ltauthorgtIsaac
Asimovlt/authorgt ltlanguagegtEnglishlt/langu
agegt lt/bookgtlt/cataloggt
Elements
Opening and Closing tags
Text content
7XML Technology overview
Document Type Definition (DTD) and XSchema are
use to validate an XML document by defining
namespaces, elements, rules
Specialized software and database systems can be
used to create and edit XML documents. In the
future the XForm standard will be used
XML separates the metadata storage from its
presentation. XML documents can be transformed
into something else, like HTML, PDF, XML, other)
through the use of the eXtensible Stylesheet
Language, XSL Transformations (XSLT) and XSL
Formatting Objects (XSL-FO)
Very much like a database system, XML documents
can be searched and queried through the use of
XPath oe XQuery. There is no need to create
tables, indexes or define relationships
XML metadata or data can be published in smart
catalogs often referred to as registries than can
be used for discovery of information.
XML Documents can be sent like regular files but
are typically exchanged between applications
through Web Services using the SOAP and other
protocols
8What is an XML Schema?
- Exchange / sharing / harmonization implies
agreement on structure - We need a specification that describes the
structure and rules ? Schema - A schema is a set of rules to which an XML
document must conform in order to be considered
'valid' - XML Schema was also designed with the intent that
determination of a document's validity would
produce a collection of information adhering to
specific data types - Similar to relational databases structural
definition - Many schemas exists for different purposes
- Examples
- DDI, SDMX ,Dublin Core, RSS, XHTML, etc.
9Metadata, XML and Microdata
10What is a survey?
- More than just data.
- A complex process to produce data for the purpose
of statistical analysis - Beyond this, a tool to support evidence based
policy making and results monitoring - The data is surrounded by a large body of
documentation - Survey data often come with limited documention
- Note that microdata is intended for experts
- Statisticians / researchers
- Represents a single point in time and space
- Need to be aggregated to produce meaningful
results - It is the beginning of the story
11What is survey metadata?
- Survey documentation can be broken down into
structured metadata and documents - Structured metadata can be captured using XML
- Documents can be described in structured metadata
- Example of metadata
- Survey level Title, country, year, abstract,
sampling, agencies, access policy, etc. - Variable level filename, label, code, questions,
instructions, derivation, etc. - Related materials report, questionnaire, papers,
manuals, scripts/programs, photos - Cross-surveys catalogs, longitudinal, concepts,
comparability, etc.
12Importance of survey metadata
- Data Quality
- Usefulness accessibility coherence
completeness relevance timeliness - Undocumented data is useless
- Partially documented data is risky (misuse)
- Data discovery and access
- Preservation
- Replication standard (Gary King)
- Information exchange
- Reduce need to access sensitive data
- Maintain coherence / linkages across the complete
life cycle (from respondent to policy maker) - Reuse
13The Data Documentation Initiative
- The Data Documentation Initiative is an XML
specification to capture structured metadata
about microdata (broad sense) - First generation DDI 1.02.1 (2000-2008)
- focus on single archived instance
- Second generation DDI 3.0 (2008)
- focus on life cycle
- go beyond the single survey concept
- mutli-purpose
14DDI Timeline / Status
- Pre-DDI 1.0
- 70s / 80s OSIRIS Codebook
- 1993 IASSIST Codebook Action Group
- 1996 SGML DTD
- 1997 DDI XML
- 1999 Draft DDI DTD
- 2000 DDI 1.0
- Simple survey
- Archival data formats
- Microdata only
- 2003 DDI 2.0
- Aggregate data (based on matrix structure)
- Added geographic material to aid geographic
search systems and GIS users - 2003 - Establishment of DDI Alliance
- 2004 Acceptance of a new DDI paradigm
- Lifecycle model
- Shift from the codebook centric / variable
centric model to capturing the lifecycle of data - Agreement on expanded areas of coverage
- 2005
- Presentation of schema structure
- Focus on points of metadata creation and reuse
- 2006
- Presentation of first complete 3.0 model
- Internal and public review
- 2007
- Vote to move to Candidate Version (CR)
- Establishment of a set of use cases to test
application and implementation - October 3.0 CR2
- 2008
- February 3.0 CR3
- March 3.0 CR3 update
- April 3.0 CR3 final
- April 28th 3.0 Approved by DDI Alliance
- May 21st DDI 3.0 Officially announced
- Initial presentations at IASSIST 2008
- 2009
- DDI 3.1 and beyond
15DDI 1/2.x
16The archive perspective
- Focus on preservation of a survey
- Often see survey as collection of data files
accompanied by documentation - Code book centric
- report, questionnaire, methodologies, scripts,
etc. - Result in a static event the archive
- Maintained by a single agency
- Is typically documentation after the facts
- This is the initial DDI perspective (DDI 2.0)
17DDI 2.0 Technical Overview
- Based on a single structure (DTD)
- 1 codeBook, 5 sections
- docDscr describes the DDI document
- The preparation of the metadata
- stdyDscr describes the study
- Title, abstract, methodologies, agencies, access
policy - fileDscr describes each file in the dataset
- dataDscr describes the data in the files
- Variables (name, code, )
- Variable groups
- Cubes
- othMat other related materials
- Basic document citation
18Characteristics of DDI 1.0/2.0
- Focuses on the static object of a codebook
- Designed for limited uses
- End user data discovery via the variable or high
level study identification (bibliographic) - Only heavily structured content relates to
information used to drive statistical analysis - Coverage is focused on single study, single data
file, simple survey and aggregate data files - Variable contains majority of information
(question, categories, data typing, physical
storage information, statistics)
19Impact of these limitations
- Treated as an add on to the data collection
process - Focus is on the data end product and end users
(static) - Limited tools for creation or exploitation
- The Variable must exist before metadata can be
created - Producers hesitant to take up DDI creation
because it is a cost and does not support their
development or collection process
20DDI 1/2.x Tools
- Nesstar
- Nesstar Publisher, Nesstar Server
- IHSN
- Microdata Management Toolkit
- NADA (online catalog for national data archive)
- Archivist / Reviewer Guidelines
- Other tools
- SDA, Harvard/MIT Virtual Data Center (Dataverse)
- UKDA DExT, ODaF DeXtris
- http//tools.ddialliance.org
21DDI 2.0 perspective
DDI 2 Survey
DDI 2 Survey
DDI 2 Survey
DDI 2 Survey
DDI 2 Survey
DDI 2 Survey
DDI 2 Survey
22DDI 3.0
23When to capture metadata?
- Metadata must be captured at the time the event
occurs! - Documenting after the facts leads to considerable
loss of information - Multiple contributors are typically involved in
this process (not only the archivist) - This is true for producers and researchers
24DDI 3.0 and the Survey Life Cycle
- A survey is not a static process It dynamically
evolved across time and involves many
agencies/individuals - DDI 2.x is about archiving, DDI 3.0 across the
entire life cycle - 3.0 focus on metadata reuse (minimizes
redundancies/discrepancies, support comparison) - Also supports multilingual, grouping, geography,
and others - 3.0 is extensible
25Requirements for 3.0
- Improve and expand the machine-actionable aspects
of the DDI to support programming and software
systems - Support CAI instruments through expanded
description of the questionnaire (content and
question flow) - Support the description of data series
(longitudinal surveys, panel studies, recurring
waves, etc.) - Support comparison, in particular comparison by
design but also comparison-after-the fact
(harmonization) - Improve support for describing complex data files
(record and file linkages) - Provide improved support for geographic content
to facilitate linking to geographic files (shape
files, boundary files, etc.)
26Approach
- Shift from the codebook centric model of early
versions of DDI to a lifecycle model, providing
metadata support from data study conception
through analysis and repurposing of data - Shift from an XML Data Type Definition (DTD) to
an XML Schema model to support the lifecycle
model, reuse of content and increased controls to
support programming needs - Redefine a single DDI instance to include a
simple instance similar to DDI 1/2 which
covered a single study and complex instances
covering groups of related studies. Allow a
single study description to contain multiple data
products (for example, a microdata file and
aggregate products created from the same data
collection). - Incorporate the requested functionality in the
first published edition
27Designing to support registries
- Resource package
- structure to publish non-study-specific materials
for reuse - Extracting specified types of information in to
schemes - Universe, Concept, Category, Code, Question,
Instrument, Variable, etc. - Allowing for either internal or external
references - Can include other schemes by reference and select
only desired items - Providing Comparison Mapping
- Target can be external harmonized structure
28Technical Overview
- DDI 3 is composed of several schemas
- Use only what you need!
- Schemas represent modules, sub-modules
(substitutions), reusable, external schemas
- archive
- comparative
- conceptualcomponent
- datacollection
- dataset
- dcelements
- DDIprofile
- ddi-xhtml11
- ddi-xhtml11-model-1
- ddi-xhtml11-modules-1
- group
- inline_ncube_recordlayout
- instance
- logicalproduct
- ncube_recordlayout
- physicaldataproduct
- physicalinstance
- proprietary_record_layout (beta)
- reusable
- simpledc20021212
- studyunit
- tabular_ncube_recordlayout
- xml
- set of xml schemas to support xhtml
29Technical Overview
- Any element that can be referenced is globally
uniquely identified - Maintainable (by an agency)
- Versionable (can change across time)
- Identifiable (within a maintainable scheme)
- Modules
- Reflect closely related sets of information
similar to the sections of DDI 1/2. DTD - Modules can be held as separate XML instances and
be included in a large instance by either
inclusion or reference - All modules are maintainable (but not all
maintainables are modules)
30 Technical Overview Maintainable Schemes
(thats with an e not an a)
- Category Scheme
- Code Scheme
- Concept Scheme
- Control Construct Scheme
- GeographicStructureScheme
- GeographicLocationScheme
- InterviewerInstructionScheme
- Question Scheme
- NCubeScheme
- Organization Scheme
- Physical Structure Scheme
- Record Layout Scheme
- Universe Scheme
- Variable Scheme
- Packages of reusable metadata maintained by a
single agency
31DDI 3.0 Use Cases
- Study design/survey instrumentation
- Questionnaire generation/data collection and
procesing - Data recoding, aggregation and other processing
- Data dissemination/discovery
- Archival ingestion/metadata value-add
- Question/concept/variable banks
- DDI for use within a research project
- Capture of metadata regarding data use
- Metadata mining for comparison, etc.
- Generating instruction packages/presentations
32Study Design/Survey Instrumentation
- This use case concerns how DDI 3.0 can support
the design of studies and survey instrumentation - Without benefit of a question or concept bank
33- Types of Metadata
- Concepts (conceptual module)
- Universe (conceptual module)
- Questions (datacollection module)
- Flow Logic (datacollection module)
ltDDI 3.0gt Concepts Universes
ltDDI 3.0gt Concepts Universes
Final
Drafting/ Review/ Revision
ltDDI 3.0gt Questions Flow Logic
ltDDI 3.0gt Concepts Universes Questions Flow Logic
As the survey instrument is tested, all
revisions and history can be tracked and
preserved. This would include question
translation and internationalization.
Final
Drafting/ Testing/ Revision
34Questionnaire Generation, Data Collection, and
Processing
- This use case concerns how DDI 3.0 can support
the creation of various types of
questionnaires/CAI, and the collection and
processing of raw data into microdata.
35- Types of Metadata
- Concepts (conceptual module)
- Universe (conceptual module)
- Questions (datacollection module)
- Flow Logic (datacollection module)
- Variables (logicalproduct module)
- Categories/Codes (logicalproduct module)
- Coding (datacollection module)
Paper Questionnaire
ltDDI 3.0gt Concepts Universes Questions Flow Logic
Online Survey Instrument
CAI Instrument
Final
Raw Data
Microdata
DDI captures the content XML allows for each
application to do its own presentation
ltDDI 3.0gt Concepts Universes Questions Flow Logic
ltDDI 3.0gt Variables Coding
ltDDI 3.0gt Categories Codes Physical Data
Product Physical Data Instance
36Data Recoding, Aggregation, etc.
- This use case concerns how DDI 3.0 can describe
recodes, aggregation, and similar types of data
processing.
37- Initial microdata has
- Concepts (conceptual module)
- Universes (conceptual module)
- Questions (datacollection module)
- Flow Logic (datacollection module)
- Variables (logicalproduct module)
- Coding (datacollection module)
- Categories (logicalproduct module)
- Codes (logicalproduct module)
- Physical Data Product
- Physical Data Instance
- Recode adds
- More codings (datacollection module)
- New variables
- New categories
- New codes
- NCubes (for aggregation)
Could be a recode, an aggregation, or other
process.
Microdata/ Aggregates
Microdata
ltDDI 3.0gt Conceptual Datacollection Variables Cate
gories Codes
ltDDI 3.0gt Codings Variables (new) Categories
(new) Codes (new) NCubes
38Data Dissemination/Data Discovery
- This use case concerns how DDI 3.0 can support
the discovery and dissemination of data.
39ltDDI 3.0gt Can add archival events meta-data
Rich metadata supports auto-generation of
websites and other delivery formats
Codebooks
ltDDI 3.0gt Full meta- data set
Websites
Databases, repositories
Research Data Centers
Microdata/ Aggregates
Data-Specific Info Access Systems
Registries Catalogues Question/Concept/ Variable
Banks
40Archival Ingestion and Metadata Value-Add
- This use case concerns how DDI 3.0 can support
the ingest and migration functions of data
archives and data libraries.
41Supports automation of processing if good DDI
metadata is captured upstream
Provides a neutral format for data migration as
analysis packages are versioned
ltDDI 3.0gt Full meta- data set (?)
Data Archive Data Library
Ingest Processing
Microdata/ Aggregates
ltDDI 3.0gt Full or additional metadata Archival
events
Provides good format foundation for
value- added metadata by archive
42Question/Concept/Variable Banks
- This use case describes how DDI 3.0 can support
question, concept, and variable banks. These are
often termed registries or metadata
repositories because they contain only metadata
links to the data are optional, but provide
implied comparability. The focus is metadata
reuse.
43Because DDI has links, each type of bank
functions in a modular, complementary way.
Question Bank
ltDDI 3.0gt Questions Flow Logic Codings
ltDDI 3.0gt Questions Flow Logic Codings
Users and Applications
Variable Bank
ltDDI 3.0gt Variables Categories Codes
ltDDI 3.0gt Variables Categories Codes
Users and Applications
ltDDI 3.0gt Concepts
ltDDI 3.0gt Concepts
Users and Applications
Concept Bank
Supports but does not require ISO 11179
44DDI For Use within a Research Project
- This use case concerns how DDI 3.0 can support
various functions within a research project, from
the conception of the study through collection
and publication of the resulting data.
45Prinicpal Investigator
Research Staff
Collaborators
ltDDI 3.0gt Variables Physical Stores
ltDDI 3.0gt Questions Instrument
ltDDI 3.0gt Concepts Universe Methods Purpose People
/Orgs
ltDDI 3.0gt Funding Revisions
ltDDI 3.0gt Data Collection Data Processing
Data
Archive/ Repository
Submitted Proposal
Publication
Presentations
46Capture of Metadata Regarding Data Use
- This use case concerns how DDI 3.0 can capture
information about how researchers use data, which
can then be added to the overall metadata set
about the data sources they have accessed.
47- Types of Metadata
- Recodes (datacollection module)
- Record subsets (physicalinstance module)
- Variable subsets (logicalproduct module)
- Comparison (comparative module)
Data Sets
ltDDI 3.0gt StudyUnit DataCollection LogicalProduct
PhysicalDataProduct PhysicalInstance
- ltDDI 3.0gt
- Recodes
- Case Selection
- Variable Selection
- Comparison to original study
- Resulting physical file descriptions
Data
Data Analysis
48Metadata Mining for Comparison, etc.
- This use case concerns how collections of DDI 3.0
metadata can act as a resource to be explored,
providing further insight into the comparability
and other features of a collection of data.
49- Types of Metadata
- Universe (comparative module)
- Concept (comparative module)
- Question (datacollection module)
- Variable (logicalproduct module)
Questions
Variable
Concepts
Metadata Repositories/ Registries
Universe
ltDDI 3.0gt Instances
- ltDDI 3.0gt
- Comparison
- Questions
- Categories
- Codes
- Variables
- Universe
- Concepts
- Recodes
- Harmonizations
?
Data Sets
50Generating Instruction Packages/Presentations
- This use case concerns how DDI 3.0 can support
automation around the instruction of students and
others.
51- Types of Metadata
- Individual studies (studyunit module)
- Grouping purpose (group module)
- Linking information (comparative module)
- Processing assistance (group module)
ltDDI 3.0gt StudyUnit 1
ltDDI 3.0gt StudyUnit 2
ltDDI 3.0gt StudyUnit 1 StudyUnit 2 StudyUnit
3 StudyUnit 4 Comparative OtherMaterials
ltDDI 3.0gt StudyUnit 3
ltDDI 3.0gt StudyUnit 4
ltDDI 3.0gt StudyUnit 1 StudyUnit 2 StudyUnit
3 StudyUnit 4
- Topically related studies selected
- Group is made with description of the intended
use for the group - Comparative information is added indicating
matching fields for linking and mapping between
similar variables - Other materials such as SAS/SPSS recode command
are referenced from the group
Instructional Package
52DDI 3.0 Tools
- Under developments
- DDI Foundation Tools Program
- Road Map
- XML Beans, validation,
- DDI DExT, DDI2StatsProgs
- Other tools
- R SPSS Export, Algenta SurveyViz, others
presented at IASSIST - DDI Editing Suite
- Proposed as extension of DDI-FTP
- Plan for generic editor in 6-9 months
- DDI 3.0 related projects / initiatives
- RDC Canada, Germany RDC / EURASI, DANS MIXED, NORC
53DDI 3 Relationship to Other Standards
- SDMX (from microdata to indicators / time series)
- Completely mapping to and from DDI NCubes
- Dublin Core (surveys and documents gets cited)
- Mapping of citation elements
- Option for DC namespace basic entry
- ISO 19115 Geography (microdata gets mapped)
- Search requirements
- Support for GIS users
- METS
- Designed to support profile development
- OAIS (alignment of archiving standards)
- Reference model for the archival lifecycle
- ISO/IEC 11179 (metadata mining through concepts)
- Variable linking representation to concept and
universe - Optional data element construct in
ConceptualComponent that allows for complete
ISO/IEC 11179 structure as a maintained item
54DDI 3.0 perspective
55DDI 2.0 and DDI 3.0
56DDI 2 / DDI 3
- Single survey
- Focus on the archive
- Non-reusable metadata
- Maintained by single agency
- Loose validation
- DTD based
- Sparse documentation
- Designed by archivists
- Some tools are available
- Multiple surveys
- Focus on life cycle
- Highly reusable metadata
- Maintained by many agencies
- Tied validation
- Schema based
- Extensive guide
- Designed by expert groups
- Tools are beginning to emerge
57What 3.0 can do for you
- Manage multi-surveys
- Support multiple contributors
- Support many different perspectives
- Support many different use cases
- Maintain metadata integrity across the life cycle
- Connect to other metadata spaces
- Metadata reuse
- Publication in registries
- Backward compatibility with 2.0
58DDI Community
59DDI Organizations/ Agencies
- DDI Alliance (http//www.ddialliance.org)
- Interuniversity Consortium for Political and
Social Research (ICPSR) (http//icpsr.umich.edu) - International Association for Social Science
Infromation Service Technology (IASSIST)
(http//www.iassistdata.org) - International Household Survey Network (IHSN)
(http//www.surveynetwork.org) - Open Data Foundation (ODaF) (http//www.opendatafo
undation.org) - National Opinion Research Center Data Enclave
(NORC) (http//dataenclave.norc.org) - Metadata Technology (http//www.metadatatechnology
.com)
60IZA Data Service CenterDDI/SDMX
WorkshopWiesbaden, Germany, June 18th 2008The
Statistical Data and Metadata Exchange Standard
(SDMX) An Introduction
- Arofan Gregory / Pascal Heus
- agregory_at_opendatafoundation.org /
pheus_at_opendatafoundation.org - Open Data Foundation
61Overview of the Session
- SDMX Background and Goals
- SDMX and Data
- SDMX and Metadata
- SDMX and Best Practices The Content-Oriented
Guidelines - The SDMX Information Model
- SDMX and Web Services
- The SDMX Registry
- SDMX Data Services
- Tools and Resources
62SDMX Background and Goals
63What is SDMX?
- The problem space
- Statistical collection, processing, and exchange
is time-consuming and resource-intensive - Focus on aggregate data (esp. time series)
- Various international and national organisations
have individual approaches for their
constituencies - Uncertainties about how to proceed with new
technologies (XML, web services )
64What is SDMX?
- The Statistical Data and Metadata Exchange
(SDMX) initiative is taking steps to address
these challenges and opportunities that have just
been mentioned - By focusing on business practices in the field
of statistical information - By identifying more efficient processes for
exchange and sharing of data and metadata using
modern technology and open standards
65Who is SDMX?
- SDMX is an initiative made up of seven
international organizations - Bank for International Settlements
- European Central Bank
- Eurostat
- International Monetary Fund
- Organisation for Economic Cooperation and
Development - United Nations
- World Bank
- The initiative was launched in 2002
66 www.z.orgwww.hub.org
180 Countries
Internet, Search, Navigation
www.y.org
www.x.org
67SDMX Products
- Technical standards for the formatting and
exchange of aggregate statistics - SDMX Technical Specifications version 1.0 (now
ISO/TS 17369 SDMX TC 154 WG2) - SDMX Technical Specifications version 2.0 (soon
to be submitted to ISO TC 154 WG2) - Content-Oriented Guidelines (in draft)
- Common Metadata Vocabulary
- Cross-Domain Statistical Concepts
- Statistical Subject-Matter Domains
68Major Features of SDMX
- Structure and formats (XML, EDIFACT) for
aggregate data - Structure and formats (XML) for metadata
- Formal information model (UML) for managing
statistical exchange and sourcing - Web-services guidelines and registry services
specification for use of modern technologies - Content-oriented guidelines to recommend best
practices
69Recent Events
- Jan 2007 Launch meeting at the World Bank for
SDMX 2.0 Technical Specifications - February 2007 Endorsement of SDMX by EUs
Statistical Programme Committee - March 2008 SDMX becomes the preferred standard
for data and metadata of the UN Statistical
Commission - Other standards were mentioned DDI and XBRL
specifically
70Adopters/Interest
- The following are known adopters (or planning to
adopt) - US Federal Reserve Board and Bank of New York
- European Central Bank
- Joint External Debt Hub (WB, IMF, OECD, BIS)
- UN/TRADECOM at UN Statistical Division
- NAAWE (National Accounts from OECD/Eurostat)
- SODI (Eurostat and European Governments)
- Mexican Federal System
- Vietnamese Ministry of Planning and Investment
- Qatar Information Exchange
- IMF (BOP, SNA, SDDS/GDDS)
- Food and Agriculture Organization
- Millenium Development Goals (UN System, others)
- International Labor Organization
- Bank for International Settlements
- OECD
- World Bank
- Marchioness Islands (Spanish/Portugese
Statistical Region) - UNESCO (Education)
71Rate of Adoption
- Between January 2007 and January 2008, adoption
has doubled - We anticipate a similar rate of growth for the
coming year - Tools are becoming available
- UNSC recommendation makes it a safe course to
follow for risk-averse institutions - Training courses are in increasing demand
(Eurostat, Metadata Technology) - Standard data and metadata structures for many
domains are being developed
72SDMX and Data
73SDMX and Data Formats
- SDMX provides a format for describing the
structure of data (structural metadata) - EDIFACT (was GESMES/TS, now SDMX-EDI)
- XML (SDMX-ML)
- SDMX provides formats for transmission and
processing of data - EDIFACT (1 message)
- XML (4 different equivalent flavors for different
functions) - Data is tabulated, aggregate data (eg,
multi-dimensional/OLAP cubes) - Can be any aggregate data!
- Most data formats are derived from the structural
metadata (eg, XML schemas are generated for each
type of structure according to the business
rules)
74Data Set Structure
75First Identify the Concepts
- A statistical concept is a characteristic of a
time series or an observation (MCV) - A concept is a unit of knowledge created by a
unique combination of characteristics (SDMX
Information Model) - Whatever the definition, statistical concepts are
the DNA of the key family - Their usage (type, structure, sequence) define
the structure of the data
76Data Set StructureConcepts
- Computers need structure of data
- Concepts
- Code lists
- Data values
- How these fit together
77Data Set Structure Code Lists
Code Lists
Concepts
78Data Makes Sense
Q,ZA,B,1,1999-06-3016547
Quarterly, South Africa, Bank Loans, Stocks, for
30 June 1999
79Data Set Structure Defining Multi-Dimensional
Structures
- Comprises
- Concepts that identify the observation value
- Concepts that add additional metadata about the
observation value - Concept that is the observation value
- Any of these may be
- coded
- text
- date/time
- number
- etc.
Dimensions
Attributes
Measure
Representation
80Data Set Structure Concept Usage
(Dimension)
(Dimension)
(Attribute)
(Attribute)
(Dimension)
(Dimension)
(Dimension)
(Measure)
81SDMX and Metadata
82SDMX and Metadata
- SDMX provides for several types of metadata
- Structural (describes structures of data sets and
metadata sets and related items) - Provisioning (describes the sourcing of data
between departments and organizations) - Reference metadata all other types of
metadata (footnotes, methodology, quality, etc.
Can be specified by the user!) - Reference metadata is the most important one it
is what we typically think of as metadata
83SDMX Metadata Sets
- Version 2.0 of the SDMX Technical Specifications
provides XML formats for metadata sets (SDMX-ML) - To describe their structure
- To exchange metadata in XML
- This is based on concepts (similar to the data
formats) - SDMX supports any metadata concepts the users
wishes to report/exchange/process - May be flat lists or hierarchical
- Definitions provided by users, but
recommendations exist for many common concepts - Metadata sets are attached to a formal object in
the information model (an organization, a data
set, a codelist, etc.)
84SDMX and Metadata
- This is a very powerful feature of SDMX
- It can be used to integrate/mimic other metadata
standards! - Provides very good support for standard exchange
of metadata which cannot be anticipated by the
designers of systems/standards - Must be based on common agreements about the
meaning of metadata concepts - Often, concepts are taken from other metadata
models/standards such as DDI, Dublin Core, etc.
85The SDMX Information Model
86The SDMX Information Model
- A formal, documented conceptual model of
statistical exchange, management, and sourcing - Expressed as a UML model
- Used as the basis of all SDMX implementation
- XML
- EDIFACT
- Any other programming language/platform
- Provides consistency between implementations
- Based on analysis of many statistical processing
systems - Describes existing business practices in a
generic way
87Information Model High-Level Schematic
structure and code list maps
Data or Metadata Structure Definition
Category Scheme
Structure Maps
comprises subject or reporting categories
uses specific data/metadata structure
can be linked to categories in multiple category
schemes
conforms to business rules of the data/metadata
flow
Data or Metadata Flow
Data or Metadata Set
Category
can get data/metadata from multiple data/metadata
providers
publishes/reports data/metadata sets
can have child categories
can provide data/metadata for many data/metadata
flows using agreed data/metadata structure
Registration of Data or Metadata Set
Provision Agreement
URL, registration date etc.
Data Provider
registers existence of data and metadata
88SDMX and Best Practices The Content-Oriented
Guidelines
89SDMX Content-Oriented Guidelines
- There is a long history of discussion about what
is best practice in the collection of statistics - SDMX decided to define the technical basis for
statistical exchange, and then engage in this
debate - It makes reaching agreements between
organizations easier! - These documents build on many years of work
defining statistical concepts, terms, and
classifications - Although described as statistical, much of what
is here also applies to social science (and
other) research
90SDMX Content-Oriented Guidelines
- Four main documents
- Overview
- Metadata Common Vocabulary (annex)
- Cross-Domain Concepts (2 annexes)
- Statistical Subject-Matter Domains (annex)
- These will not become ISO specifications, but
will evolve as publications of the SDMX
Initiative - They are now available in their first official
release at www.sdmx.org
91Common Metadata Vocabulary
- A set of terms and definitions for the different
parts of the SDMX technical standards, and many
common concepts used in data and metadata
structures - Does not replace other major vocabularies in this
space (such as the OECD glossary) but references
these other works
92Cross-Domain Concepts
- Includes concepts which are common across many
statistical domains - Names Definitions
- Representations
- Approximately 130 concepts, some with recommended
representations (codelists) - These are concepts which support both data and
metadata structures - Emphasis on quality frameworks for reference
metadata concepts
93Statistical Subject-Matter Domains
- Based on the UN/ECE classification of statistical
activities - Provides a classification system for use in
exchanging statistics across domain boundaries - Provides a breakdown of the various domains
within official statistics
94SDMX and Web Services
95Web-Services Components of SDMX
- Web-Services Guidelines
- Part of the Technical Specifications package
- SDMX Query message
- Part of SDMX-ML
- SDMX Registry Services
- Part of version 2.0 Technical Specifications
- Interfaces are in SDMX-ML
- Document describes implementation rules
96Web Services Guidelines
- Recommends use of WSS 1.1 for web services which
use SOAP, WSDL - Provides standard function names for many typical
web-services functions - Querying for data
- Querying for metadata
- Querying for structural information
97SDMX Query Message
- An XML Query to support two-way web-services
calls using XML messages - Designed to support
- Queries for structural information from online
databases/repositories - Queries for data from online databases
- Queries for metadata from online databases
- Part of SDMX-ML
- Very similar to the SQL query language supported
by all database packages - Specific to SDMX objects
98SDMX Registry Services
- A registry is a common type of technology
- Every Windows machine has a Windows registry to
let applications know what other applications are
on that machine, and where they are located - Web services registries do the same thing on a
network - Functions like a card catalogue in a print
library you can look up resources and find out
how to obtain them - A registry provides a single place on the
Internet where everyone can discover the data,
metadata, and structures that other organizations
use/publish - They do not contain the data and metadata it
just indexes it and links to it
99SDMX Registry Services (cont.)
- SDMX Registry Services are based on generic,
standard web-services registry technology - ISO 15000 ebXML Registry/Repository
- OASIS UDDI Registry (part of .NET, etc.)
- SDMX Registry Services are not generic
- They are specific to SDMX exchanges of data and
metadata, etc. - There is not one central SDMX Registry
- Each domain will have its own registry for its
members - The registries can be linked (federated)
100SDMX Registry/Repository
SDMX Registry Interfaces
Register
Indexes data and metadata
REGISTRY Data Set/Metadata Set
Query
Submit
Describes data and metadata sources and reporting
processes
REPOSITORY Provisioning Metadata
Query
Submit
REPOSITORY Structural Metadata
Describes data and metadata structures
Query
101SDMX Registry/Repository
SDMX Registry Interfaces
Register
Indexes data and metadata
REGISTRY Data Set/Metadata Set
Query
Subscription/Notification Applications can
subscribe to notification of new or changed
objects
Submit
REPOSITORY Provisioning Metadata
Query
Submit
REPOSITORY Structural Metadata
Describes data and metadata structures
Query
102 The Old JEDH Site
BIS
WEBSITE
IMF
OECD
World Bank
(Various Formats)
(3-month production cycle)
103 JEDH with SDMX
Retrieves data from sites
BIS
SDMX Agent
SDMX-ML
SDMX-ML Loaded into JEDH DB
Info about data is registered
IMF
SDMX-ML
Discover data and URLs
SDMX Registry
OECD
SDMX-ML
Data provided in real time to site
World Bank
SDMX-ML
JEDH Site
SDMX-ML
(Debtor database)
104Recent and On-Going Developments
- Many organizations using SDMX have been
implementing web services - There is growing interest in forming a working
group to further extend the specification for use
with web-services technology - Standard error messages
- Expanded function calls
- Standard WSDLs
- If you are interested in this, please tell me!
105Tools and Resources
106SDMX Tools
- There are now several sources for SDMX tools
- All are free or open-source
- Eurostat complete package of tools for data,
metadata, and registry services - Metadata Technology Ltd similar package of
tools - Data editors are usually based on Excel
- Some other tools
- Open Data Foundation SDMX Browser for data
visualization - OECD, ECB, and UN/Statistical Division provide
some other tools for specific applications - Integration with PC-Axis has been prototyped, to
be available this summer - DevInfo has SDMX support
- FAME is developing SDMX support
- Commercial vendors provide good support through
web-services functionality - Eg, Oracle 11, .NET, etc.
107Resources
- The SDMX Initiative Site http//www.sdmx.org
- The SDMX Toolkit and Forums
- http//www.metadatatechnology.com
- Various papers and (soon) open-source tools
- http//www.opendatafoundation.org
108IZA Data Service CenterDDI/SDMX
WorkshopWiesbaden, Germany, June 18th
2008SDMX, DDI, and Other Standards
- Arofan Gregory / Pascal Heus
- agregory_at_opendatafoundation.org /
pheus_at_opendatafoundation.org - Open Data Foundation
109Overview of the Session
- DDI/SDMX Philosophy and Timing of Standards
Development - DDI/SDMX Points of Functional Overlap
- DDI/SDMX Direct Mappings
- DDI/SDMX Integration Approaches
- Other Related Standards and On-Going Work
110DDI/SDMX Philosophy and Timing of Development
111Development Philosophies/Timing
- Unlike many standards bodies, both the SDMX
Initiative and the DDI Alliance have attempted to
create standards which do not duplicate existing
efforts - There is an awareness that users need to deal
with several different standards - DDI (3.0) and SDMX were both intentionally
aligned with other, related standards - DDI 1./2. existed before SDMX
- It was largely self-contained
- SDMX was created before DDI 3.0 existed
- Created with an awareness of DDI 1./2.
- DDI 3.0 benefited from having SDMX as a published
specification - Actively aligned with SDMX and many other
standards -
112SDMX Design
- SDMX was intentionally designed to accommodate
integration of standards which are used with the
inputs to aggregate data - This included DDI and XBRL
- Mechanism for integration is generic
- The key point for this integration is the SDMX
Registry - It provides links between aggregate (SDMX) data
sets, and also to source data and metadata
113DDI/SDMX Points of Functional Overlap
114SDMX and DDI as Complementary
- DDI is designed to document micro-data
- 1./2. versions were archival, after-the-fact
documentation - 3.0 version covers entire life cycle, but still
has an after-the fact function - SDMX is designed as a standard for processing and
automation - It is not documentary, but is aimed at automation
of statistical systems and exchanges - These purposes are related, but not duplicative
- SDMX and DDI can both do useful things within a
single system
115Examples
- DDI could be used to document SDMX-based
aggregates more completely for archival purposes - DDI could be used to document the micro-data on
which aggregates are based - As soon as tabulation occurs, SDMX can be used to
describe and format the data - SDMX can describe micro-data, but it is not very
useful - DDI can be used to automate processing of
multi-dimensional data cubes, but it is more
difficult than with SDMX - SDMX can be used to link DDI instances with other
types of standard data and metadata (including
both SDMX and DDI)
116DDI and SDMX
SDMX Aggregated data Indicators, Time
Series Across time Across geography Open
Access Easy to use
DDI Microdata Low level observations Single time
period Single geography Controlled access Expert
Audience
- Microdata data is a important source of
aggregated data - Crucial overlap and mappings exists between both
worlds (but commonly undocumented) - Interoperability provides users with a full
picture of the production process
117Generic Process Example
DDI
Survey/Register
Anonymization, cleaning, recoding, etc.
Tabulation, processing, case selection, etc.
Indicators
Raw Data Set
Micro-Data Set/ Public Use Files
Aggregation, harmonization
Aggregation, harmonization
SDMX
Aggregate Data Set (Lower level)
Aggregate Data Set (Higher Level)
118DDI SDMX?
- When you have data which has been
tabulated/aggregated, it may be useful to have
both SDMX and DDI - SDMX for processing and exchanging the data
- DDI for documenting these processes, in case they
are of interest to researchers - DDI has a much richer descriptive capability for
addressing the exact processes used in
statistical packages - SDMX is easier to process
119DDI/SDMX Direct Mappings
120Direct Mappings DDI SDMX
- IDs and referencing use the same approach
(identifiable versionable - maintainable
structured URN syntax) - Both are organized around schemes
- Reusable packages of data, similar to relational
tables in databases - Both describe multi-dimensional data
- A clean cube in DDI maps directly to/from SDMX
- Both have concepts and codelists
- DDI has much less emphasis on concepts
- SDMX emphasizes concepts because they are needed
for comparison - Both contain mappings (comparison) for codes
and concepts
121Formal Mapping
- There is on-going work to describe a formal
mapping between SDMX and DDI - It will cover these direct correspondences
- They are quite obvious a code maps to a code a
concept to a concept etc. - There are currently no tools, because generic
tools such as XSLT will work for this
transformation - Drafts of this work are expected this summer, as
part of the SDMX submission to ISO for the
version 2.0 Technical Specifications - The direct mappings are the easy part!
122Issues with Direct Mapping
- It is possible to describe everything in the DDI
as an SDMX Metadata Set - This is probably not the best way to use SDMX
with DDI! - It is usually better to select the important
fields, and keep the rest in native DDI format - When you map from DDI to SDMX, you typically will
not carry much of the descriptive metadata,
question text, etc. - Mostly structural (codelists, dimensions,
attributes, concepts) - You must have concepts for SDMX which are not
always present in DDI - Going from SDMX to DDI, it is not always possible
to map all the data - Especially for SDMX Metadata Sets, which may have
user-configured concepts that dont always exist
in DDI - Note that SDMX-DDI mappings refer to all versions
of DDI
123DDI/SDMX Integration Approaches
124Integration Use Cases
- The most important aspect of DDI SDMX
integration is understanding what the use cases
are - This defines what mapping/transformation is
needed - It also defines what links need to be stored
between data and metadata files - There are some common use cases
- DDI used to describe and link microdata inputs to
SDMX aggregates - DDI used to more fully document SDMX aggregates
for dissemination to users - Using the SDMX Registry as a lifecycle management
tool for DDI, SDMX, etc.
125Linking Source Data and Aggregates
- DDI provides a wealth of information about the
micro-data which serves as an input to SDMX
aggregates - It is possible to capture these links in SDMX, at
the cell level or higher, to provide automated
access to source data - An SDMX registry can be used to provide easy
access to these links - The user/collector of aggregate data can access
the rich DDI metadata, and possibly the data (if
they have access rights) - It is possible to automatically generate SDMX
output from the DDI metadata describing
tabulation of micro-data - This may not be useful if the desired SDMX target
is a standard cube structure described by another
organization - It may make transformation to the standard cube
easier, however - The SDMX Registry provides a good tool for
managing links - Links between SDMX and DDI files are stored as
Metadata Reports
126Demo SDMX DDI Source Links
127DDI SDMX for Dissemination
- Typically, the full DDI documentation is not
provided on web-sites which publish
aggregates/indicators - SDMX is becoming a popular dissemination format
for these data - It has been shown to increase the use of data on
the Web - If the DDI documentation is available, this could
also be delivered as additional documentation - Especially useful at study level
- Links could be directly embedded in SDMX data
files as attributes or stored in an SDMX
Registry, or both
128The SDMX Registry for Lifecycle Management
- The SDMX Registry provides a tool for tracking
the sources of data for aggregates - It can also track the transformation of versions
of DDI as the data moves through the lifecycle - There is an SDMX model for processes
- This can be used to describe the DDI lifecycle
model - SDMX Metadata Reports can be used to link DDI
metadata to specific stages of the DDI lifecycle,
and to each other - Applications could query the SDMX Registry to
discover all of the DDI metadata produced
upstream, as micro-data is collected and processed
129Demos
- SDMX Metadata Report used to express DDI metadata
- SDMX Metadata Report used to link DDI instances
130Other Related Standards and On-Going Work
131Many Related Standards
- DDI
- SDMX
- ISO/IEC 11179 concept management and semantic
modelling - ISO 19115 Geographical metadata
- METS packaging/archiving of digital objects
- PREMIS Archival lifecycle metadata
- XBRL business reporting
- Dublin Core citation metadata
- Standard mappings are being defined by people
from many different organizations (see
presentation from METIS 2008 in Luxembourg)
132ISO/IEC 11179
- ISO/IEC 11179 is used to describe the meanings
and representations of terms and concepts - Both SDMX and DDI are aligned with ISO/IEC 11179
- SDMX and DDI concepts can be defined using the
ISO/IEC 11179 attributes - Codelists and categories can be directly mapped
(and other representations) - ISO/IEC 11179 can be implemented with DDI
(directly, for concepts) and/or with SDMX (as a
Metadata Report) - ISO/IEC 11179 has no standard expression in XML
it is just a model
133ISO 19115 Geographical Metadata
- ISO 19115 describes geographies (bounding boxes
for countries, etc.) - DDI uses the ISO 19115 model in its own XML
- It does not use the standard ISO 19115 XML
format, but there is a 1-to-1 mapping - SDMX could model ISO 19115 if desired
- Linking to DDI or ISO 19115 XML is probably more
useful, using the standard SDMX mechanism - Most geographies in SDMX aggregate data sets are
coded, not directly described
134METS
- METS is used to package a set of files which work
together as a digital object - Both DDI and SDMX metadata could be placed inside
a METS wrapper - They would be metadata sections
- The primary use case would be for archiving of a
set of related data and metadata files, possibly
with other related materials such as research
publications
135PREMIS
- PREMIS allows for the capture of administrative
metadata as a collection is placed and managed
within the archive - DDI and SDMX files would be treated like any
other files forming part of the collection - Both may contain metadata which can be extracted
and used to populate PREMIS instances (access
levels, confidentiality, etc.)
136XBRL
- XBRL is used by business to report required
information to national supervisory bodies - This includes banking supervision and other
economic data - XBRL is a source format for some aggregate
statistics - XBRL International and the SDMX Sponsors are
working together to define a cross-walk between
the two standards
137Dublin Core
- Dublin Core is used to capture citation-type
metadata for resources on the Internet and
els