SlideShare uma empresa Scribd logo
1 de 18
LIBER: e-Science Workshop
   Rob Grim
   e-Science Coordinator, Tilburg University
   Executive manager Open Data Foundation (ODaF)
   December 5th, Bristol 2011
e-Science, Research Data and Libraries

Overview of this presentation:
1.    Open Data Foundation (ODaF)
2.    e-Science
3.    Research Data Life Cycle: Data Documentation Initiative (DDI 3)
4.    Technology for Statistical Data and Metadata Exchange (SDMX)
5.    Role of Libraries


Main issue of my talk:
•    What kind of problems can be solved with metadata management?
•    How and where can metadata management help libraries to support
     research?
•    What sort of data services could libraries develop?


                          LIBER e-Science Workshop   14-12-2011         2
What is ODaF?
 The Open Data Foundation (ODaF) is a non-profit organization
promoting the adoption of global metadata standards and the development
of open-source solutions for the management and use of statistical data.

 We focus on improving data and metadata accessibility and overall
quality in support of research, policy making, and transparency, in the
fields of Social, Behavioral and Economic sciences.

ODaF is heavily involved in developing and promoting SDMX and DDI 3
Why ODaF?
 The Open Data Foundation (ODaF) was established to fill a gap in the
area of statistical data and metadata management in Social, Behavioral
and Economic sciences (SBE).

    The adoption of metadata specifications (DC, DDI, SDMX, ISO/IEC
     11179, ISO19115) has been impaired by the LACK OF TOOLS and agreed
     guidelines for their use.


 Building such tools requires the coordination of strong information
technology and cross-domain expertise that is NOT typically a function of
these agencies. This is not by lack of interest: it is simply not their
mandate, mission or responsibility.
What does ODaF do?
1. Support and coordinate the development of open-source
   tools for management of statistical data and metadata
2. Provide technical assistance to agencies for the adoption of
   metadata specifications, best practices in data
   management, and capacity building
3. Provide access to public metadata collections and registries
4. Promote international cooperation and address global issues
5. Develop training resources and reference materials
6. Provide web-based facilities to foster the dialog between
   various communities
Adopters/Interest in SDMX
  1. European Central Bank (ECB)
  2. International Monetary Fund (IMF)
  3. United Nations (MDG, WHO, UNESCO)
  4. World Bank (WB)
  5. UNESCO (Education)
  6. > 100 National Statistical Offices (NSO’s)

Adopters/Interest in DDI3
  1. Australian Bureau of Statistics
  2. CESSDA partners
  3. OECD
  4. Research Data Centers (CentERdata)
e-Science and Research Data

1. e-Science is about
      Digital Curation
                                               Machine actionable!
      Automated Capture
      Tools Development
2. Three characteristics of the “Digital Revolution”:
      More Data
      Data Sharing
      Data Life Cycle
3. Metadata management is a critical issue to all of these!




                          LIBER e-Science Workshop   14-12-2011      7
DDI 3 Lifecycle Model




                 LIBER e-Science Workshop   14-12-2011 8
Structure of the General Statistical Business
Process Model (GSBPM)

  Process
  Phases

  Sub-
  processes
  (Descriptions)




Source: Steven Vale, UNECE, 2010
DDI 3 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


                          LIBER e-Science Workshop
DDI 3 Perspective

                                Media/Press
               General Public                    Academic


   Policy Makers
                                                                Government



Sponsors
                                                                          Business




             Producers                                      Users


                                Archivists
                                              Source: Pascal Heus, ODaF
DDI 3 Technical Overview
    • DDI 3 is composed of several schemas
        • Use only what you need!
        • Schemas represent modules, sub-modules
          (substitutions), reusable, external schemas
•     archive                            •   instance
•     comparative                        •   logicalproduct
•     conceptualcomponent                •   ncube_recordlayout
•     datacollection                     •   physicaldataproduct
•     dataset                            •   physicalinstance
•     dcelements                         •   proprietary_record_layout (beta)
•     DDIprofile                         •   reusable
•     ddi-xhtml11                        •   simpledc20021212
•     ddi-xhtml11-model-1                •   studyunit
•     ddi-xhtml11-modules-1              •   tabular_ncube_recordlayout
•     group                              •   xml
•     inline_ncube_recordlayout          •   set of xml schemas to support xhtml



                                     Source: Arofan Gregory/Wendy Thomas
Data Set Structure:Concepts
          Stock/Flow
Country
              Unit Multiplier
                      Unit
                                           Time/Frequency


             Computers need structure of data
             •Concepts
             •Code lists
            Topicvalues
             •Data
             •How these fit together
Data Makes Sense
          Q,ZA,B,1,1999-06-30=16547

                   Quarterly, South Africa,
                   Bank Loans, Stocks,
                   for 30 June 1999

           16457
Libraries and Research Data Involvement



   Four key areas of activity:


   1. Data Availability
   2. Data Discovery Services
   3. Access and Accessibility
   4. Delivery Services


                LIBER e-Science Workshop   14-12-2011   37
Data Availability     Data Discovery         Access and             Delivery
                                             Accessibility



Registries            Research data          Metadata               Enhanced
                      portals                management tools       Publications
                                             (distributed access,
                                             secured access to
                                             data structures)
Data Archiving        Subject repositories   Research Data          Data Publications
(Repositories)                               Warehousing            and Data Journals


Collection building   Resource               Data Curation          Supplementary
(application of       Aggregation                                   materials
ontologies) +         (Disciplinary)
                                                                    “Dark Archive
                                                                    Materials”
Locally produced or   Metadata                  Data Security and     Data Dissemination
reused research        Mining                   Data Privacy
data                  (“mash ups”)              Digital Rights
                                                Management (DRM)
                              LIBER e-Science Workshop     14-12-2011              38
Library and IT Services,Tilburg University


1. Research data services: registering, archiving, accessibility
2. Link publications, research data and supplementary materials
3. Data discovery services: subject portals European Values Study
4. Lobby to value research data as scientific output
5. Lobby for a generally adopted research data policy




                        LIBER e-Science Workshop   14-12-2011       39
Disclaimer




    “No one, including NSF is quite sure what is
    meant by DATA MANAGEMENT Or PLAN.”

       Christine Borgman (DCC, Chicago, 2010)

    Thanks for your attention!

Mais conteúdo relacionado

Mais procurados

Bridging research and collections
Bridging research and collectionsBridging research and collections
Bridging research and collectionsvty
 
Metadata for digital long-term preservation
Metadata for digital long-term preservationMetadata for digital long-term preservation
Metadata for digital long-term preservationMichael Day
 
Introduction to DataCite and its Infrastructure for new Members
Introduction to DataCite and its Infrastructure for new MembersIntroduction to DataCite and its Infrastructure for new Members
Introduction to DataCite and its Infrastructure for new MembersFrauke Ziedorn
 
Preservation metadata
Preservation metadataPreservation metadata
Preservation metadataMichael Day
 
Where is the opportunity for libraries in the collaborative data infrastructure?
Where is the opportunity for libraries in the collaborative data infrastructure?Where is the opportunity for libraries in the collaborative data infrastructure?
Where is the opportunity for libraries in the collaborative data infrastructure?LIBER Europe
 
Research data management & planning: an introduction
Research data management & planning: an introductionResearch data management & planning: an introduction
Research data management & planning: an introductionMaggie Neilson
 
Repository Federation: Towards Data Interoperability
Repository Federation: Towards Data InteroperabilityRepository Federation: Towards Data Interoperability
Repository Federation: Towards Data InteroperabilityRobert H. McDonald
 
Providing support and services for researchers in good data governance
Providing support and services for researchers in good data governanceProviding support and services for researchers in good data governance
Providing support and services for researchers in good data governanceRobin Rice
 
Applying Digital Library Metadata Standards
Applying Digital Library Metadata StandardsApplying Digital Library Metadata Standards
Applying Digital Library Metadata StandardsJenn Riley
 
Toward universal information access on the digital object cloud
Toward universal information access on the digital object cloudToward universal information access on the digital object cloud
Toward universal information access on the digital object cloudNational Institute of Informatics
 
Linked Open Data for Digital Humanities
Linked Open Data for Digital HumanitiesLinked Open Data for Digital Humanities
Linked Open Data for Digital HumanitiesChristophe Guéret
 
Research data management : Open Research Data pilot, data management (plans),...
Research data management : Open Research Data pilot, data management (plans),...Research data management : Open Research Data pilot, data management (plans),...
Research data management : Open Research Data pilot, data management (plans),...Leon Osinski
 
Building a Data Discovery Network for Sustainability Science
Building a Data Discovery Network for Sustainability ScienceBuilding a Data Discovery Network for Sustainability Science
Building a Data Discovery Network for Sustainability ScienceRobert H. McDonald
 
Data Management Planning at the DCC: a human factor
Data Management Planning at the DCC: a human factorData Management Planning at the DCC: a human factor
Data Management Planning at the DCC: a human factorMartin Donnelly
 
Metadata approaches for digital presentation
Metadata approaches for digital presentationMetadata approaches for digital presentation
Metadata approaches for digital presentationMichael Day
 
Libby Bishop, Ethics Of Data Sharing Ncess Jun 09 Final
Libby Bishop, Ethics Of Data Sharing Ncess Jun 09 FinalLibby Bishop, Ethics Of Data Sharing Ncess Jun 09 Final
Libby Bishop, Ethics Of Data Sharing Ncess Jun 09 Finala.carusi
 

Mais procurados (20)

Trm Vilnius Metadata New
Trm Vilnius Metadata NewTrm Vilnius Metadata New
Trm Vilnius Metadata New
 
Investigation into Private LOCKSS Networks
Investigation into Private LOCKSS NetworksInvestigation into Private LOCKSS Networks
Investigation into Private LOCKSS Networks
 
Bridging research and collections
Bridging research and collectionsBridging research and collections
Bridging research and collections
 
Metadata for digital long-term preservation
Metadata for digital long-term preservationMetadata for digital long-term preservation
Metadata for digital long-term preservation
 
Introduction to DataCite and its Infrastructure for new Members
Introduction to DataCite and its Infrastructure for new MembersIntroduction to DataCite and its Infrastructure for new Members
Introduction to DataCite and its Infrastructure for new Members
 
Preservation metadata
Preservation metadataPreservation metadata
Preservation metadata
 
Working with Global Infrastructure at a National Level
Working with Global Infrastructure at a National LevelWorking with Global Infrastructure at a National Level
Working with Global Infrastructure at a National Level
 
Where is the opportunity for libraries in the collaborative data infrastructure?
Where is the opportunity for libraries in the collaborative data infrastructure?Where is the opportunity for libraries in the collaborative data infrastructure?
Where is the opportunity for libraries in the collaborative data infrastructure?
 
Research data management & planning: an introduction
Research data management & planning: an introductionResearch data management & planning: an introduction
Research data management & planning: an introduction
 
Repository Federation: Towards Data Interoperability
Repository Federation: Towards Data InteroperabilityRepository Federation: Towards Data Interoperability
Repository Federation: Towards Data Interoperability
 
Providing support and services for researchers in good data governance
Providing support and services for researchers in good data governanceProviding support and services for researchers in good data governance
Providing support and services for researchers in good data governance
 
Applying Digital Library Metadata Standards
Applying Digital Library Metadata StandardsApplying Digital Library Metadata Standards
Applying Digital Library Metadata Standards
 
Toward universal information access on the digital object cloud
Toward universal information access on the digital object cloudToward universal information access on the digital object cloud
Toward universal information access on the digital object cloud
 
Linked Open Data for Digital Humanities
Linked Open Data for Digital HumanitiesLinked Open Data for Digital Humanities
Linked Open Data for Digital Humanities
 
Research data management : Open Research Data pilot, data management (plans),...
Research data management : Open Research Data pilot, data management (plans),...Research data management : Open Research Data pilot, data management (plans),...
Research data management : Open Research Data pilot, data management (plans),...
 
Building a Data Discovery Network for Sustainability Science
Building a Data Discovery Network for Sustainability ScienceBuilding a Data Discovery Network for Sustainability Science
Building a Data Discovery Network for Sustainability Science
 
Data Management Planning at the DCC: a human factor
Data Management Planning at the DCC: a human factorData Management Planning at the DCC: a human factor
Data Management Planning at the DCC: a human factor
 
Metadata approaches for digital presentation
Metadata approaches for digital presentationMetadata approaches for digital presentation
Metadata approaches for digital presentation
 
Libby Bishop, Ethics Of Data Sharing Ncess Jun 09 Final
Libby Bishop, Ethics Of Data Sharing Ncess Jun 09 FinalLibby Bishop, Ethics Of Data Sharing Ncess Jun 09 Final
Libby Bishop, Ethics Of Data Sharing Ncess Jun 09 Final
 
DMP in 5 minutes
DMP in 5 minutesDMP in 5 minutes
DMP in 5 minutes
 

Semelhante a e-Science, Research Data and Libaries

The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...Projeto RCAAP
 
Research Data Management
Research Data ManagementResearch Data Management
Research Data ManagementJamie Bisset
 
GBIF BIFA mentoring, Day 5a Data management, July 2016
GBIF BIFA mentoring, Day 5a Data management, July 2016GBIF BIFA mentoring, Day 5a Data management, July 2016
GBIF BIFA mentoring, Day 5a Data management, July 2016Dag Endresen
 
Research Data Management: What is it and why is the Library & Archives Servic...
Research Data Management: What is it and why is the Library & Archives Servic...Research Data Management: What is it and why is the Library & Archives Servic...
Research Data Management: What is it and why is the Library & Archives Servic...GarethKnight
 
Metadata in general and Dublin Core in specific; some experiences
Metadata in general and Dublin Core in specific; some experiencesMetadata in general and Dublin Core in specific; some experiences
Metadata in general and Dublin Core in specific; some experiencesKerstin Forsberg
 
Data Literacy: Creating and Managing Reserach Data
Data Literacy: Creating and Managing Reserach DataData Literacy: Creating and Managing Reserach Data
Data Literacy: Creating and Managing Reserach Datacunera
 
Introduction to digital curation
Introduction to digital curationIntroduction to digital curation
Introduction to digital curationMichael Day
 
ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides DuraSpace
 
DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...
DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...
DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...Dr.-Ing. Thomas Hartmann
 
FAIR BioData Management
FAIR BioData ManagementFAIR BioData Management
FAIR BioData ManagementUlrike Wittig
 
Networked Science, And Integrating with Dataverse
Networked Science, And Integrating with DataverseNetworked Science, And Integrating with Dataverse
Networked Science, And Integrating with DataverseAnita de Waard
 
Meeting the NSF DMP Requirement June 13, 2012
Meeting the NSF DMP Requirement June 13, 2012Meeting the NSF DMP Requirement June 13, 2012
Meeting the NSF DMP Requirement June 13, 2012IUPUI
 
Managing data throughout the research lifecycle
Managing data throughout the research lifecycleManaging data throughout the research lifecycle
Managing data throughout the research lifecycleMarieke Guy
 
Introduction to Research Data Management for postgraduate students
Introduction to Research Data Management for postgraduate studentsIntroduction to Research Data Management for postgraduate students
Introduction to Research Data Management for postgraduate studentsMarieke Guy
 
Research Data (and Software) Management at Imperial: (Everything you need to ...
Research Data (and Software) Management at Imperial: (Everything you need to ...Research Data (and Software) Management at Imperial: (Everything you need to ...
Research Data (and Software) Management at Imperial: (Everything you need to ...Sarah Anna Stewart
 
John morrissey c3 dis fair working data.pptx
John morrissey c3 dis fair working data.pptxJohn morrissey c3 dis fair working data.pptx
John morrissey c3 dis fair working data.pptxARDC
 

Semelhante a e-Science, Research Data and Libaries (20)

The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...The state of global research data initiatives: observations from a life on th...
The state of global research data initiatives: observations from a life on th...
 
Intro to RDM
Intro to RDMIntro to RDM
Intro to RDM
 
Research Data Management
Research Data ManagementResearch Data Management
Research Data Management
 
What is-rdm
What is-rdmWhat is-rdm
What is-rdm
 
GBIF BIFA mentoring, Day 5a Data management, July 2016
GBIF BIFA mentoring, Day 5a Data management, July 2016GBIF BIFA mentoring, Day 5a Data management, July 2016
GBIF BIFA mentoring, Day 5a Data management, July 2016
 
Research Data Management: What is it and why is the Library & Archives Servic...
Research Data Management: What is it and why is the Library & Archives Servic...Research Data Management: What is it and why is the Library & Archives Servic...
Research Data Management: What is it and why is the Library & Archives Servic...
 
Research data life cycle
Research data life cycleResearch data life cycle
Research data life cycle
 
Metadata in general and Dublin Core in specific; some experiences
Metadata in general and Dublin Core in specific; some experiencesMetadata in general and Dublin Core in specific; some experiences
Metadata in general and Dublin Core in specific; some experiences
 
Data Literacy: Creating and Managing Reserach Data
Data Literacy: Creating and Managing Reserach DataData Literacy: Creating and Managing Reserach Data
Data Literacy: Creating and Managing Reserach Data
 
Introduction to digital curation
Introduction to digital curationIntroduction to digital curation
Introduction to digital curation
 
ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides ESI Supplemental Webinar 2 - DataONE presentation slides
ESI Supplemental Webinar 2 - DataONE presentation slides
 
DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...
DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...
DC 2012 - Leveraging the DDI Model for Linked Statistical Data in the Social...
 
FAIR BioData Management
FAIR BioData ManagementFAIR BioData Management
FAIR BioData Management
 
Networked Science, And Integrating with Dataverse
Networked Science, And Integrating with DataverseNetworked Science, And Integrating with Dataverse
Networked Science, And Integrating with Dataverse
 
Meeting the NSF DMP Requirement June 13, 2012
Meeting the NSF DMP Requirement June 13, 2012Meeting the NSF DMP Requirement June 13, 2012
Meeting the NSF DMP Requirement June 13, 2012
 
Managing data throughout the research lifecycle
Managing data throughout the research lifecycleManaging data throughout the research lifecycle
Managing data throughout the research lifecycle
 
Introduction to Research Data Management for postgraduate students
Introduction to Research Data Management for postgraduate studentsIntroduction to Research Data Management for postgraduate students
Introduction to Research Data Management for postgraduate students
 
Research Data (and Software) Management at Imperial: (Everything you need to ...
Research Data (and Software) Management at Imperial: (Everything you need to ...Research Data (and Software) Management at Imperial: (Everything you need to ...
Research Data (and Software) Management at Imperial: (Everything you need to ...
 
Introduction to Research Data Management
Introduction to Research Data ManagementIntroduction to Research Data Management
Introduction to Research Data Management
 
John morrissey c3 dis fair working data.pptx
John morrissey c3 dis fair working data.pptxJohn morrissey c3 dis fair working data.pptx
John morrissey c3 dis fair working data.pptx
 

Último

Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxLoriGlavin3
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfLoriGlavin3
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxLoriGlavin3
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxBkGupta21
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfMounikaPolabathina
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 

Último (20)

Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
Moving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdfMoving Beyond Passwords: FIDO Paris Seminar.pdf
Moving Beyond Passwords: FIDO Paris Seminar.pdf
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptxThe Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
The Fit for Passkeys for Employee and Consumer Sign-ins: FIDO Paris Seminar.pptx
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptx
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
What is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdfWhat is DBT - The Ultimate Data Build Tool.pdf
What is DBT - The Ultimate Data Build Tool.pdf
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 

e-Science, Research Data and Libaries

  • 1. LIBER: e-Science Workshop Rob Grim e-Science Coordinator, Tilburg University Executive manager Open Data Foundation (ODaF) December 5th, Bristol 2011
  • 2. e-Science, Research Data and Libraries Overview of this presentation: 1. Open Data Foundation (ODaF) 2. e-Science 3. Research Data Life Cycle: Data Documentation Initiative (DDI 3) 4. Technology for Statistical Data and Metadata Exchange (SDMX) 5. Role of Libraries Main issue of my talk: • What kind of problems can be solved with metadata management? • How and where can metadata management help libraries to support research? • What sort of data services could libraries develop? LIBER e-Science Workshop 14-12-2011 2
  • 3. What is ODaF?  The Open Data Foundation (ODaF) is a non-profit organization promoting the adoption of global metadata standards and the development of open-source solutions for the management and use of statistical data.  We focus on improving data and metadata accessibility and overall quality in support of research, policy making, and transparency, in the fields of Social, Behavioral and Economic sciences. ODaF is heavily involved in developing and promoting SDMX and DDI 3
  • 4. Why ODaF?  The Open Data Foundation (ODaF) was established to fill a gap in the area of statistical data and metadata management in Social, Behavioral and Economic sciences (SBE).  The adoption of metadata specifications (DC, DDI, SDMX, ISO/IEC 11179, ISO19115) has been impaired by the LACK OF TOOLS and agreed guidelines for their use.  Building such tools requires the coordination of strong information technology and cross-domain expertise that is NOT typically a function of these agencies. This is not by lack of interest: it is simply not their mandate, mission or responsibility.
  • 5. What does ODaF do? 1. Support and coordinate the development of open-source tools for management of statistical data and metadata 2. Provide technical assistance to agencies for the adoption of metadata specifications, best practices in data management, and capacity building 3. Provide access to public metadata collections and registries 4. Promote international cooperation and address global issues 5. Develop training resources and reference materials 6. Provide web-based facilities to foster the dialog between various communities
  • 6. Adopters/Interest in SDMX 1. European Central Bank (ECB) 2. International Monetary Fund (IMF) 3. United Nations (MDG, WHO, UNESCO) 4. World Bank (WB) 5. UNESCO (Education) 6. > 100 National Statistical Offices (NSO’s) Adopters/Interest in DDI3 1. Australian Bureau of Statistics 2. CESSDA partners 3. OECD 4. Research Data Centers (CentERdata)
  • 7. e-Science and Research Data 1. e-Science is about  Digital Curation Machine actionable!  Automated Capture  Tools Development 2. Three characteristics of the “Digital Revolution”:  More Data  Data Sharing  Data Life Cycle 3. Metadata management is a critical issue to all of these! LIBER e-Science Workshop 14-12-2011 7
  • 8. DDI 3 Lifecycle Model LIBER e-Science Workshop 14-12-2011 8
  • 9. Structure of the General Statistical Business Process Model (GSBPM) Process Phases Sub- processes (Descriptions) Source: Steven Vale, UNECE, 2010
  • 10. DDI 3 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 LIBER e-Science Workshop
  • 11. DDI 3 Perspective Media/Press General Public Academic Policy Makers Government Sponsors Business Producers Users Archivists Source: Pascal Heus, ODaF
  • 12. DDI 3 Technical Overview • DDI 3 is composed of several schemas • Use only what you need! • Schemas represent modules, sub-modules (substitutions), reusable, external schemas • archive • instance • comparative • logicalproduct • conceptualcomponent • ncube_recordlayout • datacollection • physicaldataproduct • dataset • physicalinstance • dcelements • proprietary_record_layout (beta) • DDIprofile • reusable • ddi-xhtml11 • simpledc20021212 • ddi-xhtml11-model-1 • studyunit • ddi-xhtml11-modules-1 • tabular_ncube_recordlayout • group • xml • inline_ncube_recordlayout • set of xml schemas to support xhtml Source: Arofan Gregory/Wendy Thomas
  • 13. Data Set Structure:Concepts Stock/Flow Country Unit Multiplier Unit Time/Frequency Computers need structure of data •Concepts •Code lists Topicvalues •Data •How these fit together
  • 14. Data Makes Sense Q,ZA,B,1,1999-06-30=16547 Quarterly, South Africa, Bank Loans, Stocks, for 30 June 1999 16457
  • 15. Libraries and Research Data Involvement Four key areas of activity: 1. Data Availability 2. Data Discovery Services 3. Access and Accessibility 4. Delivery Services LIBER e-Science Workshop 14-12-2011 37
  • 16. Data Availability Data Discovery Access and Delivery Accessibility Registries Research data Metadata Enhanced portals management tools Publications (distributed access, secured access to data structures) Data Archiving Subject repositories Research Data Data Publications (Repositories) Warehousing and Data Journals Collection building Resource Data Curation Supplementary (application of Aggregation materials ontologies) + (Disciplinary) “Dark Archive Materials” Locally produced or Metadata Data Security and Data Dissemination reused research Mining Data Privacy data (“mash ups”) Digital Rights Management (DRM) LIBER e-Science Workshop 14-12-2011 38
  • 17. Library and IT Services,Tilburg University 1. Research data services: registering, archiving, accessibility 2. Link publications, research data and supplementary materials 3. Data discovery services: subject portals European Values Study 4. Lobby to value research data as scientific output 5. Lobby for a generally adopted research data policy LIBER e-Science Workshop 14-12-2011 39
  • 18. Disclaimer “No one, including NSF is quite sure what is meant by DATA MANAGEMENT Or PLAN.” Christine Borgman (DCC, Chicago, 2010) Thanks for your attention!

Notas do Editor

  1. Two issues that are key to supporting research are the research data life cycle and the challenges and hindrances for research data sharing. I use the term E-Science interchangeably with E-Research.Two key issues for research data support Jim Gray: e-Science is where IT meets Science
  2. Now lets see how this works….>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>Provide these examples after 3:More data: Metadata content caching is used for optimizing data retrieval queries in wireless networks.Reference: Metadata guided evaluation of resource-constrained queries in content caching based wireless networks.Data sharing: the economic crises over the last decades have been the main stimulator to foster a global infrastructure for the exchange of statistical data and raising awareness for data quality. IMF DQAS. Data life cycle: transparency, science as a social contract but also relevant to verification, replication, documentation and reuse of data.Literatuur: Liu, Zheng, Liu, Wang en Chen. Metadata guided evaluation of resource-constrained queries in content caching based wireless networks. Wireless networks, 17:1833-1850. Springer.
  3. DDI 3 takes the data life cycle as a starting point. --- MOST COMPLEX STANDARD OUT THERE --- 
  4. Do we need such complex standards?
  5. Big Data, Cloud Computingloud? Capture? Curation?Tool developmet
  6. Functional perspective on the services that libraries might be willing to provide.See also: E. Harold (IBM column).
  7. Excluding: Licensed contentStructured dataDiscovery LOD
  8. Mention: projects ODAP, EO, CARDS
  9.  1. Pires, C.M., Information infrastructure(s) for the ERA. 2010: Bonn: Knowledge Exchange Strategy Forum, 8 October 2010.  
  10. Commissie de Ling verlorenkrediet.Escience: where IT meets scienceEscience: curation, capture, toolingDDI 3. SDMX Complex standard . Why use it ?