This document outlines Work Package 4, which aims to address issues with structured data from economic and social history. It proposes gathering important datasets and placing them on the Clariah Structured Data Hub to allow for augmentation, harmonization, and linking of datasets. This will help researchers find data across repositories, align codes and identifiers, and grow an interconnected network of datasets. Tools will also be provided to explore, visualize, query, and analyze the linked datasets.

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.
• Harmonisation.
• Linking datasets to answer new questions.
• Analysis of multilevel & big data sets.
• Isolated and unknown datasets.
• Reproducability v. disposable science.

5. 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.

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.

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.

15. Today’s CSDH
• Prototype up and running.
• Loosely interconnected parts without a “hood”.
• QBer (intake, data description, harmonisation, linking).
• Dedicated data pipelines.
• Triplestore, data-API, queries.
• Grlc: Query-API.
• Come see our demos!

16. Utrecht 1829 Utrecht 1839
QBer

17. Triplestore, data-API,
queries, queries-API