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Sytze Van Herck edited this page Jan 27, 2023 · 32 revisions

CSV on the Web (CoW) was developed for researchers, and in particular for historians. The goal of the tool is to encourage researchers to change their working practices. Instead of compiling only tabular data, CoW now allows anyone to transition to Linked Data.

The introduction defines Linked Data, explains the concept of FAIR data, and the process of creating Linked Data. Adapting the Metadata explains how to change the result of CoWs conversion. This section breaks down the components of the JSON schema file. Enriching the Data discusses virtual columns and how to add provenance to your data. The Tutorial on Death Duty Data from 1921 that can be linked to Civil Registry Data provides an in-depth practical example of the entire proces. The Additional Features are for advanced uses of CoW. Finally, the FAQ section includes how to deal with common error messages. A complete overview of the contents can be found below.

Examples

The examples in Adapting the Metadata and Enriching the Data are based on the following two columns by four rows dataset buurt.csv:

properties_name_in_uri |  Dienstboden
---------------------------------------
buurt-a                |  1,5
buurt-b                |  2,32
buurt-c                |  1,96
buurt-d                |  1,37

Where 'properties_name_in_uri' contains names of neighbourhoods in Amsterdam in the 19th century and 'Dienstboden' refers to the number of maids within a neighbourhood.

Occasionally, we use another example file:

personID | surname | male | occupation
------------------------------------------
012      | Fumes   | 0    | chimney sweep
013      | Careful | 1    | nurse
017      | Bushman | 1    | shrubber
019      | Oak     | 0    | woodturner

Contents

Introduction

  1. Adapting the Metadata
  2. Enriching the Data
  3. Additional Features
  4. Tutorial
    • Linking 1921 Death Duty Data to Civil Registry Data
  5. FAQ

Next: Introduction

Notice

Anyone who works with data can run CoW and create Linked Data. This wiki is a good place to start, but we also recommend some training. Aside from the step-by-step tutorial you can study at your own pace, we offer workshops from time to time.

The wiki is still being expanded on, so please leave your thoughts and comments as issues.