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Struc data Auke Rijpma

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Work Package 4: Structured data from 
 economic and social history Auke Rijpma January 2016
Predecessors • Economic and social historians often work with structured (tabular) data. • Includes large data-projects… • …and many small data sets.
Problems to solve • Finding data in multiples repositories.
Problems to solve • Finding data in multiples repositories. • Harmonisation.
Problems to solve • Finding data in multiples repositories. • Harmonisation. • Linking datasets to answer new questions. • Analysis of multilevel & big data sets. • Isolated and unknown datasets. • Reproducability v. disposable science.
What we propose • Gather and curate important datasets and place them on the Clariah Structured Data Hub. • Use web-based linked data-technology to augment, harmonise, link, and query datasets. • Provide tooling and incentives to upload new datasets. • Uploading and describing your data gives you augmentation, harmonisation, and links to other micro and macro datasets.
Empower Individual Researchers • Augment and link individual datasets according to best practices of the community or against colleagues • Share machine-interpretable code books with fellow researchers • Align codes and identifiers across datasets • Publish standards-compliant, reusable datasets Grow a giant graph of interconnected datasets
Tools to explore, visualise, query, and analyse datasets.
Future CSDH • Upload, describe, and store data. • Augment, harmonise, and link data. • Find, explore, query, visualise, and analyse data. • Share data, queries, and results.
Today’s CSDH • Prototype up and running. • Loosely interconnected parts without a “hood”. • QBer (Rinke Hoekstra): intake, data description, harmonisation, linking. • Dedicated data pipelines. • Triplestore, data-API, queries (Kathrin Dentler). • Grlc (Albert Meronyo): Query-API . • Come see our demos and visit Github repos: https:// github.com/clariah/!
Utrecht 1829 Utrecht 1839 QBer
Triplestore, data-API, queries, queries-API

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CMDI2RDFCMDI2RDF
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2016 05-20-clariah-wp4
2016 05-20-clariah-wp42016 05-20-clariah-wp4
2016 05-20-clariah-wp4
 
2016 05-20-clariah-wp3
2016 05-20-clariah-wp32016 05-20-clariah-wp3
2016 05-20-clariah-wp3
 
2016 05-20-clariah-wp2
2016 05-20-clariah-wp22016 05-20-clariah-wp2
2016 05-20-clariah-wp2
 
2016 05-20-clariah-wp5
2016 05-20-clariah-wp52016 05-20-clariah-wp5
2016 05-20-clariah-wp5
 
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LREC Ton vd Wouden
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Paqu Gertjan van Noord en Jan Odijk
Paqu Gertjan van Noord en Jan OdijkPaqu Gertjan van Noord en Jan Odijk
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Open sonar martinreynaert
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Diachronous conceptuallexicons Marieke van Erp / Piek Vossen
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Corpus studio Erwin Komen
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Athena richard zijdeman
Athena richard zijdemanAthena richard zijdeman
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Struc data aukerijpma
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Anansi jauco noordzij
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Struc data Auke Rijpma

  • 1. Work Package 4: Structured data from 
 economic and social history Auke Rijpma January 2016
  • 2. Predecessors • Economic and social historians often work with structured (tabular) data. • Includes large data-projects… • …and many small data sets.
  • 3. Problems to solve • Finding data in multiples repositories.
  • 4.
  • 5. Problems to solve • Finding data in multiples repositories. • Harmonisation.
  • 6.
  • 7.
  • 8. Problems to solve • Finding data in multiples repositories. • Harmonisation. • Linking datasets to answer new questions. • Analysis of multilevel & big data sets. • Isolated and unknown datasets. • Reproducability v. disposable science.
  • 9.
  • 10. What we propose • Gather and curate important datasets and place them on the Clariah Structured Data Hub. • Use web-based linked data-technology to augment, harmonise, link, and query datasets. • Provide tooling and incentives to upload new datasets. • Uploading and describing your data gives you augmentation, harmonisation, and links to other micro and macro datasets.
  • 11. Empower Individual Researchers • Augment and link individual datasets according to best practices of the community or against colleagues • Share machine-interpretable code books with fellow researchers • Align codes and identifiers across datasets • Publish standards-compliant, reusable datasets Grow a giant graph of interconnected datasets
  • 12. Tools to explore, visualise, query, and analyse datasets.
  • 13. Future CSDH • Upload, describe, and store data. • Augment, harmonise, and link data. • Find, explore, query, visualise, and analyse data. • Share data, queries, and results.
  • 14. Today’s CSDH • Prototype up and running. • Loosely interconnected parts without a “hood”. • QBer (Rinke Hoekstra): intake, data description, harmonisation, linking. • Dedicated data pipelines. • Triplestore, data-API, queries (Kathrin Dentler). • Grlc (Albert Meronyo): Query-API . • Come see our demos and visit Github repos: https:// github.com/clariah/!
  • 15. Utrecht 1829 Utrecht 1839 QBer