Work Package 4: Structured data from

economic and social historyAuke 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