After a theoretical introduction on the concepts of reproducible science and the Web of Data, we will present the methodology of scientific notebooks (e.g. Jupyter Notebooks). In this context, we will present a step-by-step approach to the creation of a scientific notebook in history: we will load a dataset from the Open Data of the institute and then apply filters and calculations on the data. A presentation and analysis layer with graphics will complete our research product with enrichments from external data and vocabularies from the Sema (...)

After a theoretical introduction on the concepts of reproducible science and the Web of Data, we will present the methodology of scientific notebooks (e.g. Jupyter Notebooks). In this context, we will present a step-by-step approach to the creation of a scientific notebook in history: we will load a dataset from the Open Data of the institute and then apply filters and calculations on the data. A presentation and analysis layer with graphics will complete our research product with enrichments from external data and vocabularies from the Semantic Web. This will make our output reproducible and documented with text enriched with semantic schemas (schema.org) and disambiguation authorities (GND, dpPedia, Wikidata...), data sources and computer code. The presentation does not require advanced technical knowledge. It is aimed at beginners. The technical demonstration, in the second part, is deliberately simple in content and will be commented on as it goes along.