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Workshop on Metadata Standards and Best Practices November 19-20 th, 2007 Session 1 Leveraging Metadata Standards in RDC Pascal Heus Open Data Foundation.

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Presentation on theme: "Workshop on Metadata Standards and Best Practices November 19-20 th, 2007 Session 1 Leveraging Metadata Standards in RDC Pascal Heus Open Data Foundation."— Presentation transcript:

1 Workshop on Metadata Standards and Best Practices November th, 2007 Session 1 Leveraging Metadata Standards in RDC Pascal Heus Open Data Foundation

2 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

3 Data Foundation – IZA 2007/11 What is Metadata? Common definition: Data about Data Unlabeled stuffLabeled stuff The bean example is taken from: A Managers Introduction to Adobe eXtensible Metadata Platform,

4 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

5 Data Foundation – IZA 2007/11 XML to the rescue! XML is driving todays 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!

6 Data Foundation – IZA 2007/11 XML Technical Overview Capture XML Structure DTD XSchema Transform XSL, XSLT XSL-FO Discover Registries Databases Exchange Web Services SOAP REST Search XPath XQuery Manage Software XForms

7 Data Foundation – IZA 2007/11 XML Solutions Producers Librarians Users General Public Policy Makers Media/PressAcademicBusinessGovernment 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!

8 Data Foundation – IZA 2007/11 Lets 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

9 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

10 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

11 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 –Semantic modeling, concepts, registries –http://metadata-standards.org/11179/ ISO –Geography –http://www.isotc211.org/ Dublin Core –Resources (documentation, images, multimedia) –http://www.dublincore.org

12 Data Foundation – IZA 2007/11 The need for Tools We produce data not tools! We dont have the expertise. We use data and software but we dont build tools! We dont have the expertise We preserve and disseminate data not software! We dont have the expertise Producers Librarians Users XML Specs We set specifications and standards. Tools are not our mandate Open Data Foundation

13 Data Foundation – IZA 2007/11 Open Data Foundation The need for Tools Mandated to develop tools Provide cross-domain expertise in ICT and statistics Provide umbrella for coordinated development Ensure inter-operability Outline harmonized architecture and environment Promote open source / maximize reusability Foster global registries Resources/Fund raising …

14 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!

15 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

16 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

17 Data Foundation – IZA 2007/11 Growing solutions in a complex environment USE PRODUCTION PRESERVATION ANALYSIS DISCOVERY DISSEMINATION QUALITY SECURITY SPSS Excel SDDS GDDS Toolkit Blaise CSPro SAS METADATA Stata DQAF Access Privacy Disclosure Legal ISO TECHNOLOGY Accessibility DDI ISO SDMX DCMI Registries XML Web Databases XML-DB Infrastructure XSLT XPath SOAP Programming GIS Warehouse What are we concerned with?

18 Data Foundation – IZA 2007/11 Growing solutions in a complex environment USE PRODUCTION PRESERVATION ANALYSIS DISCOVERY DISSEMINATION QUALITY SECURITY SPSS Excel SDDS GDDS Toolkit Blaise CSPro SAS METADATA Stata DQAF Access Privacy Disclosure Legal ISO TECHNOLOGY Accessibility DDI ISO SDMX DCMI Registries XML Web Databases XML-DB Infrastructure XSLT XPath SOAP Programming GIS Warehouse CHALLENGE We 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

19 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 Its not about data, its about people

20 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 Promote the use and development of open tools, do not work in isolation, get the appropriate expertise –Open Data Foundation

21 PART 2: Metadata & RDCs

22 Data Foundation – IZA 2007/11 PART 2 RDC metadata perspective List of stakeholders / initiatives Benefits of adopting metadata Challenges Tools demo (IHSN Toolkit)

23 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 RDCs / agencies / public Overall: benefit all stakeholders: producers, librarians, researcher, general public, etc.

24 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

25 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

26 Data Foundation – IZA 2007/11 RDC issues Without producer metadata –researchers cant work discover data or perform efficient work Without researcher metadata –producer dont know about data usage and quality issues –Other researcher are not aware of what has been done Without standards –Information cant be properly managed and exchanged between agencies or with the public Without tools: –Cant capture and preserve/share knowledge

27 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

28 Data Foundation – IZA 2007/11 RDC Data RDC Metadata Framework Producers Researcher Producer/Archive Metadata Research Metadata Research Output Public Use metadata 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 / RDC 6. Repeat across surveys/topics 7. Metadata facilitates output 8. Public metadata facilitates data discovery / fosters global knowledge 9. Metadata exchange between agencies

29 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

30 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)

31 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

32 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)

33 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

34 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

35 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

36 Data Foundation – IZA 2007/11 IHSN Toolkit Quick Demo Generate HTML based CD-ROM Import metadata and prepare CD-ROM Import data and compile metadata 1 2 3


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