TabLinker, introduced in an earlier post, is a spreadsheet to RDF converter. It takes Excel/CSV files as input, and produces enriched RDF graphs with cell contents, properties and annotations using the DataCube and Open Annotation vocabularies.
TabLinker interprets spreadsheets based on hand-made markup using a small set of predefined styles (e.g. it needs to know what the header cells are). Work package 6 is currently investigating whether and how we can perform this step automatically.
- Raw, model-agnostic conversion from spreadsheets to RDF
- Interactive spreadsheet marking within Excel
- Automatic annotation recognition and export with OA
- Round-trip conversion: revive the original spreadsheet files from the produced RDF (UnTabLinker)
In Data2Semantics, we have used TabLinker to publish linked socio-historical data, converting the historical Dutch censuses (1795-1971) to RDF (see slides).
Social historians are actively doing research using these datasets, producing rich annotations that correct or reinterpret data; these annotations are very useful when checking dataset quality and consistency (see model). Published RDF is ready-to-query and visualze via SPARQL queries.