SlideShare a Scribd company logo
Metadata Evaluation and Guidance for
Curation and Improvement
Sean Gordon
(scgordon@hdfgroup.org)
Ted Habermann
John Kozimor
The HDF Group
1
Terminology
Concept : General term for describing a documentation entity (e.g.
Title, Revision Date, Process Step, Spatial Extent).
Profile: A set of concepts required to support a particular
documentation need or use case for a recommendation.
Recommendation: A set of concepts that a group believes is required
for achieving a documentation goal.
Dialect : A particular form of the documentation language that is
specific to a community (e.g. ISO, DIF, CSDGM, EML, ECHO).
Collection: A group of metadata records, commonly organized by a
data center, organization or project and often stored in a database or
web accessible folder.
Recommendations Analysis Dashboard
3
Documentation
Metadata
data.ucar.edu
• Interactive exploratory metadata concept evaluation tool.
• Enables metadata for a single dialect to be easily evaluated using multiple
recommendations (eg. CSW, DataCite, UMM).
• Designed to run on collections.
• Provides a dashboard interface with 4 different visualizations
• Requires a data sheet, created by HDF metadata team.
Recommendation
Dialect
Comparison
Field
Summary
Concept
Guidance Links
Signature Score
Groups
Recommendation / Dialect Comparison
4
Documentation
Metadata
Sharable Metadata
data.ucar.edu
Identify gaps
between dialects
and
recommendations
Collection Concept Occurrence %
5
Documentation
Metadata
Sharable Metadata
data.ucar.eduIdentify fields that are
missing from dialect,
missing from collection,
complete, or partial
-100% = Concept Not in Dialect
0% = Concept Not in Collection
100% = Concept in All Records
54% = Concept in Some Records
Signature Score Groups
6
Metadata
Sharable Metadata
data.ucar.edu
Identify groups of records that
are missing the same number of
fields (typically the same fields)
Concept Guidance Links
7
Documentation
Metadata
Sharable Metadata
data.ucar.edu
Guidance Documentation
8
Documentation
Metadata
Sharable Metadata
data.ucar.edu
http://wiki.esipfed.org/index.php/Category:Documentation_Connections
Prioritizing Metadata Improvement
1. What recommendations are most important to your organization?
a) DataCite, b) DCAT, c) DIF
2. What recommendation levels are most important to your organization?
- Not all recommendations are required
3. What concepts are missing from the most metadata records?
- Fix the concept missing in 90% of your records before the concept
missing in 7% if they are part of the same profile.
4. What concepts are missing from the multiple recommendations?
- Improve completeness score for multiple recommendations by fixing
1 concept.
http://wiki.esipfed.org/index.php/Documentation_Recommendations
Metadata Improvement Guidance
1. How do I access online guidance for fixing missing concepts?
That’s great, but it doesn’t tell me how I identify which records are missing
concepts…
Which records do I need to improve?
How do I identify which records are missing concepts?
Links to xPaths in
particular dialect
What concepts are missing in a single record?
Future Directions
• Signature Score Sprints
14
Signature Score Sprints
Metadata Improvement Process
1. Prioritize which concepts should be fixed first
2. Identify records with missing concepts
3. Curate the metadata.
Strengths of the workflow
• Easy to read and understand
• Metadata dialect is not limited to one standard
• Community recommendation is not limited to
one dialect
• Use the results with your own system
• Quick to add new recommendations
• Direct quantitative guidance
• Easily accessible guidance documentation
December 14, 2015 AGU 2015 17
Questions?
December 14, 2015 AGU 2015 18
Thank you!

More Related Content

What's hot

Exploration of a Data Landscape using a Collaborative Linked Data Framework.
Exploration of a Data Landscape using a Collaborative Linked Data Framework.Exploration of a Data Landscape using a Collaborative Linked Data Framework.
Exploration of a Data Landscape using a Collaborative Linked Data Framework.
Laurent Alquier
 
Persistent Identifier Services and their Metadata by John Kunze
Persistent Identifier Services and their Metadata by John KunzePersistent Identifier Services and their Metadata by John Kunze
Persistent Identifier Services and their Metadata by John Kunze
datascienceiqss
 
Linked Data for Biopharma
Linked Data for BiopharmaLinked Data for Biopharma
Linked Data for Biopharma
Tom Plasterer
 
Making data sharing count
Making data sharing countMaking data sharing count
Making data sharing count
Krzysztof Gorgolewski
 
Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...
Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...
Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...
EOSC-hub project
 
Caldrone - Specific Needs and Concerns Associated with Data Repositories
Caldrone - Specific Needs and Concerns Associated with Data RepositoriesCaldrone - Specific Needs and Concerns Associated with Data Repositories
Caldrone - Specific Needs and Concerns Associated with Data Repositories
National Information Standards Organization (NISO)
 
OAI Metadata: Why and How
OAI Metadata: Why and HowOAI Metadata: Why and How
OAI Metadata: Why and How
Jenn Riley
 
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...
Tom Plasterer
 
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...
Tom Plasterer
 
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
National Information Standards Organization (NISO)
 
Data Management for Graduate Students
Data Management for Graduate StudentsData Management for Graduate Students
Data Management for Graduate Students
Rebekah Cummings
 
Dataset description using the W3C HCLS standard
Dataset description using the W3C HCLS standardDataset description using the W3C HCLS standard
Dataset description using the W3C HCLS standard
mhaendel
 
Research Network
Research NetworkResearch Network
Research Network
ntunmg
 
Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"
Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"
Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"
National Information Standards Organization (NISO)
 
Creating impact with accessible data in agriculture and nutrition: sharing da...
Creating impact with accessible data in agriculture and nutrition: sharing da...Creating impact with accessible data in agriculture and nutrition: sharing da...
Creating impact with accessible data in agriculture and nutrition: sharing da...
godanSec
 
TAIR ICAR 2010 Presentation
TAIR ICAR 2010 PresentationTAIR ICAR 2010 Presentation
TAIR ICAR 2010 Presentation
Phoenix Bioinformatics
 
Rachael Lammey: CrossCheck from those in the know #crossref15
Rachael Lammey: CrossCheck from those in the know #crossref15Rachael Lammey: CrossCheck from those in the know #crossref15
Rachael Lammey: CrossCheck from those in the know #crossref15
Crossref
 
Wilcox - Open Source Repositories and the Future of Fedora
Wilcox - Open Source Repositories and the Future of FedoraWilcox - Open Source Repositories and the Future of Fedora
Wilcox - Open Source Repositories and the Future of Fedora
National Information Standards Organization (NISO)
 
FAIR Data Knowledge Graphs–from Theory to Practice
FAIR Data Knowledge Graphs–from Theory to PracticeFAIR Data Knowledge Graphs–from Theory to Practice
FAIR Data Knowledge Graphs–from Theory to Practice
Tom Plasterer
 
Dspace Webinar
Dspace WebinarDspace Webinar
Dspace Webinar
Gavin Henrick
 

What's hot (20)

Exploration of a Data Landscape using a Collaborative Linked Data Framework.
Exploration of a Data Landscape using a Collaborative Linked Data Framework.Exploration of a Data Landscape using a Collaborative Linked Data Framework.
Exploration of a Data Landscape using a Collaborative Linked Data Framework.
 
Persistent Identifier Services and their Metadata by John Kunze
Persistent Identifier Services and their Metadata by John KunzePersistent Identifier Services and their Metadata by John Kunze
Persistent Identifier Services and their Metadata by John Kunze
 
Linked Data for Biopharma
Linked Data for BiopharmaLinked Data for Biopharma
Linked Data for Biopharma
 
Making data sharing count
Making data sharing countMaking data sharing count
Making data sharing count
 
Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...
Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...
Updates on the FAIR Data Maturity Model RDA Working Group & the DG RTD FAIR i...
 
Caldrone - Specific Needs and Concerns Associated with Data Repositories
Caldrone - Specific Needs and Concerns Associated with Data RepositoriesCaldrone - Specific Needs and Concerns Associated with Data Repositories
Caldrone - Specific Needs and Concerns Associated with Data Repositories
 
OAI Metadata: Why and How
OAI Metadata: Why and HowOAI Metadata: Why and How
OAI Metadata: Why and How
 
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...
 
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...
 
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
 
Data Management for Graduate Students
Data Management for Graduate StudentsData Management for Graduate Students
Data Management for Graduate Students
 
Dataset description using the W3C HCLS standard
Dataset description using the W3C HCLS standardDataset description using the W3C HCLS standard
Dataset description using the W3C HCLS standard
 
Research Network
Research NetworkResearch Network
Research Network
 
Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"
Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"
Funk and Beck "Driving Use: Identifiers and Enhanced Metadata"
 
Creating impact with accessible data in agriculture and nutrition: sharing da...
Creating impact with accessible data in agriculture and nutrition: sharing da...Creating impact with accessible data in agriculture and nutrition: sharing da...
Creating impact with accessible data in agriculture and nutrition: sharing da...
 
TAIR ICAR 2010 Presentation
TAIR ICAR 2010 PresentationTAIR ICAR 2010 Presentation
TAIR ICAR 2010 Presentation
 
Rachael Lammey: CrossCheck from those in the know #crossref15
Rachael Lammey: CrossCheck from those in the know #crossref15Rachael Lammey: CrossCheck from those in the know #crossref15
Rachael Lammey: CrossCheck from those in the know #crossref15
 
Wilcox - Open Source Repositories and the Future of Fedora
Wilcox - Open Source Repositories and the Future of FedoraWilcox - Open Source Repositories and the Future of Fedora
Wilcox - Open Source Repositories and the Future of Fedora
 
FAIR Data Knowledge Graphs–from Theory to Practice
FAIR Data Knowledge Graphs–from Theory to PracticeFAIR Data Knowledge Graphs–from Theory to Practice
FAIR Data Knowledge Graphs–from Theory to Practice
 
Dspace Webinar
Dspace WebinarDspace Webinar
Dspace Webinar
 

Viewers also liked

Progetto Quella finito
Progetto Quella finitoProgetto Quella finito
Progetto Quella finito
Roberto Paradiso
 
TuckerFinalPaper
TuckerFinalPaperTuckerFinalPaper
TuckerFinalPaper
Carly Tucker
 
Elka for new yaer
Elka for new yaerElka for new yaer
Elka for new yaer
DESIGN_STUDIO9
 
Ibm Power System S812 LC
Ibm Power System S812 LCIbm Power System S812 LC
Ibm Power System S812 LC
Diego Alberto Tamayo
 
Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988
Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988
Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988
Natalia Araújo Storck
 
Case Study - Currency from the Cloud: Security & Compliance for Payment Provider
Case Study - Currency from the Cloud: Security & Compliance for Payment ProviderCase Study - Currency from the Cloud: Security & Compliance for Payment Provider
Case Study - Currency from the Cloud: Security & Compliance for Payment Provider
Armor
 
Migrating from Magento 1 to Magento 2
Migrating from Magento 1 to Magento 2Migrating from Magento 1 to Magento 2
Migrating from Magento 1 to Magento 2
Matthias Glitzner-Zeis
 
evergreen-press-kit1
evergreen-press-kit1evergreen-press-kit1
evergreen-press-kit1
Claire Johnson
 

Viewers also liked (8)

Progetto Quella finito
Progetto Quella finitoProgetto Quella finito
Progetto Quella finito
 
TuckerFinalPaper
TuckerFinalPaperTuckerFinalPaper
TuckerFinalPaper
 
Elka for new yaer
Elka for new yaerElka for new yaer
Elka for new yaer
 
Ibm Power System S812 LC
Ibm Power System S812 LCIbm Power System S812 LC
Ibm Power System S812 LC
 
Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988
Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988
Desenvolvimento econômico meio_ambiente_e_constituição_federal_de_1988
 
Case Study - Currency from the Cloud: Security & Compliance for Payment Provider
Case Study - Currency from the Cloud: Security & Compliance for Payment ProviderCase Study - Currency from the Cloud: Security & Compliance for Payment Provider
Case Study - Currency from the Cloud: Security & Compliance for Payment Provider
 
Migrating from Magento 1 to Magento 2
Migrating from Magento 1 to Magento 2Migrating from Magento 1 to Magento 2
Migrating from Magento 1 to Magento 2
 
evergreen-press-kit1
evergreen-press-kit1evergreen-press-kit1
evergreen-press-kit1
 

Similar to Recommendations Analysis Dashboard

IWMW 2002: The Value of Metadata and How to Realise It
IWMW 2002: The Value of Metadata and How to Realise ItIWMW 2002: The Value of Metadata and How to Realise It
IWMW 2002: The Value of Metadata and How to Realise It
IWMW
 
A Data Citation Roadmap for Scholarly Data Repositories
A Data Citation Roadmap for Scholarly Data RepositoriesA Data Citation Roadmap for Scholarly Data Repositories
A Data Citation Roadmap for Scholarly Data Repositories
LIBER Europe
 
Wheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSSWheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSS
CIARD Movement
 
Tec2010 Buckley Share
Tec2010 Buckley ShareTec2010 Buckley Share
Tec2010 Buckley Share
Christian Buckley
 
LOR Characteristics and Considerations
LOR Characteristics and ConsiderationsLOR Characteristics and Considerations
LOR Characteristics and Considerations
Scott Leslie
 
Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...
Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...
Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...
Jenn Riley
 
Metadata Management In A Social Media World, Spsbos, 2 2010
Metadata Management In A Social Media World, Spsbos, 2 2010Metadata Management In A Social Media World, Spsbos, 2 2010
Metadata Management In A Social Media World, Spsbos, 2 2010
Christian Buckley
 
eROSA Stakeholder WS1: Data discovery through federated dataset catalogues
eROSA Stakeholder WS1: Data discovery through federated dataset catalogueseROSA Stakeholder WS1: Data discovery through federated dataset catalogues
eROSA Stakeholder WS1: Data discovery through federated dataset catalogues
e-ROSA
 
Knowledge management and sharepoint
Knowledge management and sharepointKnowledge management and sharepoint
Knowledge management and sharepoint
Willem Burger
 
11 Strategic Considerations for SharePoint Migrations
11 Strategic Considerations for SharePoint Migrations11 Strategic Considerations for SharePoint Migrations
11 Strategic Considerations for SharePoint Migrations
Christian Buckley
 
Data discovery through federated dataset catalogs
Data discovery through federated dataset catalogsData discovery through federated dataset catalogs
Data discovery through federated dataset catalogs
Valeria Pesce
 
Data Management Planning for researchers
Data Management Planning for researchersData Management Planning for researchers
Data Management Planning for researchers
Sarah Jones
 
Assessment of Metadata Remediation Efforts
Assessment of Metadata Remediation EffortsAssessment of Metadata Remediation Efforts
Assessment of Metadata Remediation Efforts
Jenn Riley
 
chapter 1-Overview of Information Retrieval.ppt
chapter 1-Overview of Information Retrieval.pptchapter 1-Overview of Information Retrieval.ppt
chapter 1-Overview of Information Retrieval.ppt
SamuelKetema1
 
Missing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscapMissing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscap
Stuart Weibel
 
Deploying Viva Topics
Deploying Viva TopicsDeploying Viva Topics
Deploying Viva Topics
Drew Madelung
 
How your metadata strategy impacts everything you do
How your metadata strategy impacts everything you doHow your metadata strategy impacts everything you do
How your metadata strategy impacts everything you do
Christian Buckley
 
Looking Under the Hood: How Your Metadata Strategy Impacts Everything You Do
Looking Under the Hood: How Your Metadata Strategy Impacts Everything You DoLooking Under the Hood: How Your Metadata Strategy Impacts Everything You Do
Looking Under the Hood: How Your Metadata Strategy Impacts Everything You Do
Christian Buckley
 
Metadata Quality
Metadata QualityMetadata Quality
Metadata Quality
tbruce
 
Module BookletUnitUnit17 Database Design Concepts.docx
Module BookletUnitUnit17 Database Design Concepts.docxModule BookletUnitUnit17 Database Design Concepts.docx
Module BookletUnitUnit17 Database Design Concepts.docx
gilpinleeanna
 

Similar to Recommendations Analysis Dashboard (20)

IWMW 2002: The Value of Metadata and How to Realise It
IWMW 2002: The Value of Metadata and How to Realise ItIWMW 2002: The Value of Metadata and How to Realise It
IWMW 2002: The Value of Metadata and How to Realise It
 
A Data Citation Roadmap for Scholarly Data Repositories
A Data Citation Roadmap for Scholarly Data RepositoriesA Data Citation Roadmap for Scholarly Data Repositories
A Data Citation Roadmap for Scholarly Data Repositories
 
Wheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSSWheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSS
Wheat Data Interoperability (2) by Esther DZALE YEUMO KABORE and Richard FULSS
 
Tec2010 Buckley Share
Tec2010 Buckley ShareTec2010 Buckley Share
Tec2010 Buckley Share
 
LOR Characteristics and Considerations
LOR Characteristics and ConsiderationsLOR Characteristics and Considerations
LOR Characteristics and Considerations
 
Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...
Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...
Tools and Techniques for Creating, Maintaining, and Distributing Shareable Me...
 
Metadata Management In A Social Media World, Spsbos, 2 2010
Metadata Management In A Social Media World, Spsbos, 2 2010Metadata Management In A Social Media World, Spsbos, 2 2010
Metadata Management In A Social Media World, Spsbos, 2 2010
 
eROSA Stakeholder WS1: Data discovery through federated dataset catalogues
eROSA Stakeholder WS1: Data discovery through federated dataset catalogueseROSA Stakeholder WS1: Data discovery through federated dataset catalogues
eROSA Stakeholder WS1: Data discovery through federated dataset catalogues
 
Knowledge management and sharepoint
Knowledge management and sharepointKnowledge management and sharepoint
Knowledge management and sharepoint
 
11 Strategic Considerations for SharePoint Migrations
11 Strategic Considerations for SharePoint Migrations11 Strategic Considerations for SharePoint Migrations
11 Strategic Considerations for SharePoint Migrations
 
Data discovery through federated dataset catalogs
Data discovery through federated dataset catalogsData discovery through federated dataset catalogs
Data discovery through federated dataset catalogs
 
Data Management Planning for researchers
Data Management Planning for researchersData Management Planning for researchers
Data Management Planning for researchers
 
Assessment of Metadata Remediation Efforts
Assessment of Metadata Remediation EffortsAssessment of Metadata Remediation Efforts
Assessment of Metadata Remediation Efforts
 
chapter 1-Overview of Information Retrieval.ppt
chapter 1-Overview of Information Retrieval.pptchapter 1-Overview of Information Retrieval.ppt
chapter 1-Overview of Information Retrieval.ppt
 
Missing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscapMissing pieces in_the_global_metadata_landscap
Missing pieces in_the_global_metadata_landscap
 
Deploying Viva Topics
Deploying Viva TopicsDeploying Viva Topics
Deploying Viva Topics
 
How your metadata strategy impacts everything you do
How your metadata strategy impacts everything you doHow your metadata strategy impacts everything you do
How your metadata strategy impacts everything you do
 
Looking Under the Hood: How Your Metadata Strategy Impacts Everything You Do
Looking Under the Hood: How Your Metadata Strategy Impacts Everything You DoLooking Under the Hood: How Your Metadata Strategy Impacts Everything You Do
Looking Under the Hood: How Your Metadata Strategy Impacts Everything You Do
 
Metadata Quality
Metadata QualityMetadata Quality
Metadata Quality
 
Module BookletUnitUnit17 Database Design Concepts.docx
Module BookletUnitUnit17 Database Design Concepts.docxModule BookletUnitUnit17 Database Design Concepts.docx
Module BookletUnitUnit17 Database Design Concepts.docx
 

Recently uploaded

一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
eudsoh
 
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdfOverview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
nhutnguyen355078
 
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
osoyvvf
 
Sample Devops SRE Product Companies .pdf
Sample Devops SRE  Product Companies .pdfSample Devops SRE  Product Companies .pdf
Sample Devops SRE Product Companies .pdf
Vineet
 
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
ytypuem
 
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理 原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
tzu5xla
 
[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024
Vietnam Cotton & Spinning Association
 
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
hqfek
 
Module 1 ppt BIG DATA ANALYTICS NOTES FOR MCA
Module 1 ppt BIG DATA ANALYTICS NOTES FOR MCAModule 1 ppt BIG DATA ANALYTICS NOTES FOR MCA
Module 1 ppt BIG DATA ANALYTICS NOTES FOR MCA
yuvarajkumar334
 
Econ3060_Screen Time and Success_ final_GroupProject.pdf
Econ3060_Screen Time and Success_ final_GroupProject.pdfEcon3060_Screen Time and Success_ final_GroupProject.pdf
Econ3060_Screen Time and Success_ final_GroupProject.pdf
blueshagoo1
 
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
nyvan3
 
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
ihavuls
 
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
ywqeos
 
Cell The Unit of Life for NEET Multiple Choice Questions.docx
Cell The Unit of Life for NEET Multiple Choice Questions.docxCell The Unit of Life for NEET Multiple Choice Questions.docx
Cell The Unit of Life for NEET Multiple Choice Questions.docx
vasanthatpuram
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
jitskeb
 
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
hyfjgavov
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
Timothy Spann
 
Template xxxxxxxx ssssssssssss Sertifikat.pptx
Template xxxxxxxx ssssssssssss Sertifikat.pptxTemplate xxxxxxxx ssssssssssss Sertifikat.pptx
Template xxxxxxxx ssssssssssss Sertifikat.pptx
TeukuEriSyahputra
 
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...
Marlon Dumas
 
ML-PPT-UNIT-2 Generative Classifiers Discriminative Classifiers
ML-PPT-UNIT-2 Generative Classifiers Discriminative ClassifiersML-PPT-UNIT-2 Generative Classifiers Discriminative Classifiers
ML-PPT-UNIT-2 Generative Classifiers Discriminative Classifiers
MastanaihnaiduYasam
 

Recently uploaded (20)

一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
 
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdfOverview IFM June 2024 Consumer Confidence INDEX Report.pdf
Overview IFM June 2024 Consumer Confidence INDEX Report.pdf
 
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
 
Sample Devops SRE Product Companies .pdf
Sample Devops SRE  Product Companies .pdfSample Devops SRE  Product Companies .pdf
Sample Devops SRE Product Companies .pdf
 
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
 
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理 原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
 
[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics May 2024
 
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
一比一原版爱尔兰都柏林大学毕业证(本硕)ucd学位证书如何办理
 
Module 1 ppt BIG DATA ANALYTICS NOTES FOR MCA
Module 1 ppt BIG DATA ANALYTICS NOTES FOR MCAModule 1 ppt BIG DATA ANALYTICS NOTES FOR MCA
Module 1 ppt BIG DATA ANALYTICS NOTES FOR MCA
 
Econ3060_Screen Time and Success_ final_GroupProject.pdf
Econ3060_Screen Time and Success_ final_GroupProject.pdfEcon3060_Screen Time and Success_ final_GroupProject.pdf
Econ3060_Screen Time and Success_ final_GroupProject.pdf
 
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
 
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
原版制作(unimelb毕业证书)墨尔本大学毕业证Offer一模一样
 
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
一比一原版(lbs毕业证书)伦敦商学院毕业证如何办理
 
Cell The Unit of Life for NEET Multiple Choice Questions.docx
Cell The Unit of Life for NEET Multiple Choice Questions.docxCell The Unit of Life for NEET Multiple Choice Questions.docx
Cell The Unit of Life for NEET Multiple Choice Questions.docx
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
 
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
一比一原版兰加拉学院毕业证(Langara毕业证书)学历如何办理
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
 
Template xxxxxxxx ssssssssssss Sertifikat.pptx
Template xxxxxxxx ssssssssssss Sertifikat.pptxTemplate xxxxxxxx ssssssssssss Sertifikat.pptx
Template xxxxxxxx ssssssssssss Sertifikat.pptx
 
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...
 
ML-PPT-UNIT-2 Generative Classifiers Discriminative Classifiers
ML-PPT-UNIT-2 Generative Classifiers Discriminative ClassifiersML-PPT-UNIT-2 Generative Classifiers Discriminative Classifiers
ML-PPT-UNIT-2 Generative Classifiers Discriminative Classifiers
 

Recommendations Analysis Dashboard

  • 1. Metadata Evaluation and Guidance for Curation and Improvement Sean Gordon (scgordon@hdfgroup.org) Ted Habermann John Kozimor The HDF Group 1
  • 2. Terminology Concept : General term for describing a documentation entity (e.g. Title, Revision Date, Process Step, Spatial Extent). Profile: A set of concepts required to support a particular documentation need or use case for a recommendation. Recommendation: A set of concepts that a group believes is required for achieving a documentation goal. Dialect : A particular form of the documentation language that is specific to a community (e.g. ISO, DIF, CSDGM, EML, ECHO). Collection: A group of metadata records, commonly organized by a data center, organization or project and often stored in a database or web accessible folder.
  • 3. Recommendations Analysis Dashboard 3 Documentation Metadata data.ucar.edu • Interactive exploratory metadata concept evaluation tool. • Enables metadata for a single dialect to be easily evaluated using multiple recommendations (eg. CSW, DataCite, UMM). • Designed to run on collections. • Provides a dashboard interface with 4 different visualizations • Requires a data sheet, created by HDF metadata team. Recommendation Dialect Comparison Field Summary Concept Guidance Links Signature Score Groups
  • 4. Recommendation / Dialect Comparison 4 Documentation Metadata Sharable Metadata data.ucar.edu Identify gaps between dialects and recommendations
  • 5. Collection Concept Occurrence % 5 Documentation Metadata Sharable Metadata data.ucar.eduIdentify fields that are missing from dialect, missing from collection, complete, or partial -100% = Concept Not in Dialect 0% = Concept Not in Collection 100% = Concept in All Records 54% = Concept in Some Records
  • 6. Signature Score Groups 6 Metadata Sharable Metadata data.ucar.edu Identify groups of records that are missing the same number of fields (typically the same fields)
  • 9. Prioritizing Metadata Improvement 1. What recommendations are most important to your organization? a) DataCite, b) DCAT, c) DIF 2. What recommendation levels are most important to your organization? - Not all recommendations are required 3. What concepts are missing from the most metadata records? - Fix the concept missing in 90% of your records before the concept missing in 7% if they are part of the same profile. 4. What concepts are missing from the multiple recommendations? - Improve completeness score for multiple recommendations by fixing 1 concept. http://wiki.esipfed.org/index.php/Documentation_Recommendations
  • 10. Metadata Improvement Guidance 1. How do I access online guidance for fixing missing concepts? That’s great, but it doesn’t tell me how I identify which records are missing concepts…
  • 11. Which records do I need to improve?
  • 12. How do I identify which records are missing concepts? Links to xPaths in particular dialect
  • 13. What concepts are missing in a single record?
  • 16. Metadata Improvement Process 1. Prioritize which concepts should be fixed first 2. Identify records with missing concepts 3. Curate the metadata.
  • 17. Strengths of the workflow • Easy to read and understand • Metadata dialect is not limited to one standard • Community recommendation is not limited to one dialect • Use the results with your own system • Quick to add new recommendations • Direct quantitative guidance • Easily accessible guidance documentation December 14, 2015 AGU 2015 17
  • 18. Questions? December 14, 2015 AGU 2015 18 Thank you!