The dataLegend ecosystem for historical statistics

Rinke Hoekstra, Albert Meroño-Peñuela*, Auke Rijpma, Richard Zijdeman, Ashkan Ashkpour, Kathrin Dentler, Ivo Zandhuis, Laurens Rietveld

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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The main promise of the digital humanities is the ability to perform scholarly studies at a much broader scale, and in a much more reusable fashion. The key enabler for such studies is the availability of sufficiently well described data. For the field of socio-economic history, data usually comes in a tabular form. Existing efforts to curate and publish datasets take a top-down approach and are focused on large collections, produce scarce metadata, require expertise for effective integration, provide poor user support while producing mappings, and present issues at data access. This paper presents the datalegend platform, which addresses the long tail of research data by catering for the needs of individual scholars. datalegend allows researchers to publish their (small) datasets, link them to existing vocabularies and other datasets, and thereby contribute to a growing collection of interlinked datasets. We present the architecture of datalegend; its core vocabularies and data; and QBer, an interactive, user supportive mapping generator and RDF converter. We evaluate our results by showing how our system facilitates use cases in socio-economic history.

Original languageEnglish
Pages (from-to)49-61
Number of pages13
JournalJournal of Web Semantics
Early online date10 Mar 2018
Publication statusPublished - May 2018


  • Digital humanities
  • Linked data
  • QBer
  • Structured data


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