Upload
winter-myers
View
22
Download
0
Tags:
Embed Size (px)
DESCRIPTION
Workshop on Metadata Standards and Best Practices November 19-20 th , 2007 Session 1 Leveraging Metadata Standards in RDC. Pascal Heus Open Data Foundation [email protected] http://www.opendatafoundation.org. Outline. PART 1: General issues & ODaF - PowerPoint PPT Presentation
Citation preview
Workshop on Metadata Standards and Best PracticesNovember 19-20th, 2007
Session 1Leveraging Metadata Standards in RDC
Pascal Heus
Open Data Foundation
http://www.opendatafoundation.org
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Outline
• PART 1: General issues & ODaF– Needs and challenges in statistical data and
metadata management– Metadata and XML solutions– Selecting specifications– Need for tools– Open Data Foundation
• PART 2: RDC Specific issues– Metadata in RDCs– Solutions and benefits– Tools and ongoing initiatives
• Conclusions / Q&A
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
What is Metadata?
• Common definition: Data about Data
Unlabeled stuff Labeled stuff
The bean example is taken from: A Manager’sIntroduction to Adobe eXtensible Metadata Platform, http://www.adobe.com/products/xmp/pdfs/whitepaper.pdf
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Managing data and metadata is challenging!
We are in charge of the data. We support our users but also need to protect our respondents!
We want easy access to high quality and well documented data!
We need to collect the information from the producers, preserve it, and provide access to our users!
Producers
Librarians
Users
General Public
Policy Makers
Sponsors
Media/Press
Academic
Business
Government
We have an information
management problem
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
XML to the rescue!
• XML is driving today’s web service oriented architecture of the Internet and Intranets
• Using XML, we can capture, structure, transform, discover, exchange, query, edit and secure metadata and data
• XML is platform & language independent and can be used by everyone
• XML is both machine and human readable• XML is non-proprietary, public domain and
many open tools exist• Domain specific standards are available!
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
XML Technical Overview
StructureDTD
XSchema
TransformXSL, XSLT
XSL-FO
DiscoverRegistriesDatabases
ExchangeWeb Services
SOAPREST
SearchXPath
XQuery
ManageSoftwareXForms
CaptureXML
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
XML Solutions
Producers
Librarians
Users
General Public
Policy Makers
Media/Press
Academic
Business
Government
Sponsors
XML Specs
Use our specifications and your will be happy! It will harmonize everything.
Great, I can provide public metadata!
Well documented data, here we come!
Now we can talk to each other!
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Let’s use XML, but….
Producers
Librarians
Users
XML Specs
Which specifications should we adopt?
How do we do this? Where are the tools and guidelines?
?Open Data Foundation
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Open Data Foundation (ODaF)
• US Based non-profit organization, established 2006
• Directors, advisors and managers from statistical and ICT communities
• Project oriented• Mission
– Focus on socio-economic data– Adoption of global metadata standards – Coordinated development of open-source tools– Capacity building– Improving data and metadata accessibility and
overall quality – Operate at the global level
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Selecting XML specifications
• A single specification is not enough!– XML specifications commonly focus on a specific
area of knowledge and/or set of functionalities– Cannot answer the needs of all actors
• XML mappings between specifications are possible– Information can be converted from one domain to
another and be carried across communities
• Which ones should we use?– Fit for purpose– Widely accepted and supported– Can be mapped to a cross-domain family
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
A suggested set for socio-economic data
• Statistical Data and Metadata Exchange (SDMX)– Macrodata, time series, indicators, registries– http://www.sdmx.org
• Data Documentation Initiative (DDI)– Microdata (surveys, studies)– http://www.ddialliance.org
• ISO 11179– Semantic modeling, concepts, registries– http://metadata-standards.org/11179/
• ISO 19115– Geography– http://www.isotc211.org/
• Dublin Core– Resources (documentation, images, multimedia)– http://www.dublincore.org
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
The need for Tools
We produce data not tools! We don’t have the expertise.
We use data and software but we don’t build tools! We don’t have the expertise
We preserve and disseminate data not software! We don’t have the expertise
Producers
Librarians
Users
XML Specs
We set specifications and standards. Tools are not our mandate
Open Data Foundation
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Open Data Foundation
The need for Tools
Mandated to develop toolsProvide cross-domain expertise in ICT and statistics
Provide umbrella for coordinated developmentEnsure inter-operability
Outline harmonized architecture and environmentPromote open source / maximize reusability
Foster global registriesResources/Fund raising
…
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
ODaF Vision
• Promote and facilitate the production and use of “open data”– Public metadata, high quality, fully documented, respondent
protected, easy to find, accessible in accordance to statistical principles and legislations
• Foster a global harmonized framework– Facilitate the flow of data and metadata– Promotes dialog between all stakeholders
Unlock the Data!
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Some Projects & Ideas
• Guidelines for an harmonized architecture and development environment
• Roadmap for tools development• XML mappings• Facility to host development of open source
projects (GForge)• Provide hosting services for agencies• Implement registries / catalogs• Produce training and reference material• Technical support & capacity building• Advocacy
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
ODaF partners / clients
• Statistical agencies / producers• Data Archives• Academic & Research communities• Standard settings agencies & consortiums• Governmental organizations• International organizations• Open source community• Software developers• IT Vendors
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Growing solutions in a complex environment
USEPRODUCTION
PRESERVATION
ANALYSIS
DISCOVERY
DISSEMINATION
QUALITY
SECURITY
SPSS
Excel
SDDS
GDDS
Toolkit
Blaise
CSPro
SAS METADATAStata
DQAF
Access
Privacy Disclosure
Legal
ISO 11179
TECHNOLOGY
Accessibility
DDI
ISO 19115
SDMX
DCMIRegistries
XML
WebDatabases
XML-DB
Infrastructure
XSLTXPath SOAP
Programming
GIS
Warehouse
What are we concerned with?
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Growing solutions in a complex environment
USEPRODUCTION
PRESERVATION
ANALYSIS
DISCOVERY
DISSEMINATION
QUALITY
SECURITY
SPSS
Excel
SDDS
GDDS
Toolkit
Blaise
CSPro
SAS METADATAStata
DQAF
Access
Privacy Disclosure
Legal
ISO 11179
TECHNOLOGY
Accessibility
DDI
ISO 19115
SDMX
DCMIRegistries
XML
WebDatabases
XML-DB
Infrastructure
XSLTXPath SOAP
Programming
GIS
Warehouse
CHALLENGEWe need a set of tools that work
together in an harmonized framework. This requires
coordinated efforts and expertise from the various communities
OPEN DATA FOUNDATION• Provide cross-domain & IT expertise• Coordinate and support development• Knowledge sharing• Capacity Building• Provide global vision and guidance
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Challenges
• The technology is available today• The right people are available today• The need and the will are there• The real challenges are:
– Tools availability– Awareness / Understanding of technology– Change management– Coordination & Guidance– Focused resources and funding– Institutional commitment
• Learn for the past for a better future• It’s not about data, it’s about people
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Summary
• Managing data and metadata is challenging– Solutions exist to make it easier and provide
better information to unlock the data
• Adopt a set of specifications that answer your requirements and can connect across domains– DDI, SDMX, ISO 11179, Dublin Core, ISO 19115
• Promote the use and development of open tools, do not work in isolation, get the appropriate expertise– Open Data Foundation
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
PART 2
• RDC metadata perspective• List of stakeholders / initiatives • Benefits of adopting metadata• Challenges• Tools demo (IHSN Toolkit)
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
RDC Objectives
• Provide a secure environment for the researcher to perform the in depth analysis of sensitive/confidential data in a cost effective way
• Facilitate the capture, sharing and dissemination of research knowledge
• Provide feedback to the producer on data usage and quality
• Exchange information with other RDC’s / agencies / public
• Overall: benefit all stakeholders: producers, librarians, researcher, general public, etc.
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
RDC metadata
• Simple access to data file and codebook is insufficient. Researcher need high quality comprehensive metadata and a collaborative environment to promote dynamic research
• Traditionally, survey metadata has focused on archiving/preservation (current DDI 1/2.x)
• This however insufficient and should extended into both the survey production process and the secondary use of the data
• New DDI 3.0 meets such requirements• RDC ideal environment for capture of
researcher metadata
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
DDI 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 extends to life cycle• 3.0 is a modular framework available for multiple purposes (use cases)• Metadata is key to comprehensive capture of knowledge
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
RDC issues
• Without producer metadata– researchers can’t work discover data or perform efficient
work
• Without researcher metadata– producer don’t know about data usage and quality issues– Other researcher are not aware of what has been done
• Without standards– Information can’t be properly managed and exchanged
between agencies or with the public
• Without tools:– Can’t capture and preserve/share knowledge
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
When to capture metadata?
• Metadata must be captured at the time the event occurs!• Documenting after the facts leads to considerable loss of
information• This is true for producers and researchers
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
RDCRDC
RDC
Data
RDC Metadata Framework
Producers
Researcher
Producer/ArchiveMetadata
ResearchMetadata
Research Output
Public Usemetadata
External users
1. Producer provide data & basic docs
2. Need to enhance existing metadata
3. Start capturing researcher metadata
4. Knowledge grows and gets reused
5. Provides usage and quality feedback to producer / RDC6. Repeat across surveys/topics
7. Metadata facilitates output
8. Public metadata facilitates data discovery / fosters global knowledge
9. Metadata exchange between agencies
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Metadata Components
• Producer metadata:– Codebook, questionnaires, reports, methodologies,
processing, scripts, quality, admin, etc.
• Research metadata– Recodes, analysis, table, scripts, papers, references, logs,
quality, usage– Activities, discussions, knowledge base
• Outputs– Papers, presentations, tables
• Public metadata– Metadata stripped out of sensitive information (summary
statistics, sensitive variables, etc.)
• Metadata capture can be manual, semi-automated, automated
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
RDC Solutions
• Metadata management– Adopt standards and provide researcher with
comprehensive metadata– Use related tools to capture research process– Metadata mining and reporting utilities
• Collaborative environment– Used web technologies to foster a dynamic research
environment
• Connected and Remote enclaves– Connect RDCs through secure networks– Consider virtual data enclave or batch analysis
• Data disclosure– Protect respondent through sound data disclosure
techniques (using metadata as well)
• Train producers/researchers (methods and data)
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Solution Examples
• Simple solutions: use good practices– File and variable naming conventions, sound
statistical methods– Comment source code– Document the work
• Metadata solutions:– DDI tools, citation database, source code level
metadata capture, variable recodes, table disclosure, data quality feedback, comparability
• Web based collaboration environment– Wiki, blogs, discussion groups, events/todo
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Benefits (1)
• Comprehensive data documentation– Through good metadata practices,
comprehensive documentation is available to the researchers
• Preservation, integration and sharing of knowledge– Research process is captured and preserved in
harmonized formats– Research knowledge becomes integrant part of
the survey and available to all – Reduce duplication of efforts and facilitates reuse– Producer gets feedback from the data users
(usage, quality issues)
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Benefits (2)
• Research outputs and dissemination– Facilitate production of research outputs– Facilitate dissemination and fosters broader
visibility of research outputs
• Exchange of information– Metadata exchange between RDC, producers,
librarians– Importance of public metadata for sensitive
datasets– Facilitate data discovery (inside and outside
RDC)
• Advanced metadata mining / comparability
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
Answering the tools challenge
• Metadata standards are available but there is a lack of tools for metadata management
• Several efforts are ongoing– DDI Alliance, International Household Survey
Network, UK Data archive, NORC Data Enclave, Canada RDC, Open Data Foundation
– DDI Foundation Tools Program, UK DExT, Canada RDC, EU Framework 7
• Joint efforts will minimize costs, maximize reusability and foster tool harmonization / interoperability
• Open source model: availability & sustainability
http://www.opendatafoundation.org Open Data Foundation – IZA 2007/11
RDC challenges
• Adopting good metadata management framework takes effort– Survey metadata must first be compiled– ICT capacity building and tools development– Producer and researchers need to be trained
• Not only a technological challenge – change management, training
• Leads to better research, shared knowledge, better user/producer dialog, improved data quality
• Meets the mandate of RDC