Materials and data

Note

The online presentations in HTML can be downloaded in PDF:

• open the presentation,
• press e or the three lines in the left bottom corner, Tools and PDF Export Mode,
• print the result to PDF using your browser.

Monday, 16 Sept.

Introduction to R

• Presentation contents:
  • Functions and data structures
  • Basic workflows (packages, scripts, projects, paths)
  • Reading data into R
• Dataset dartpoints.csv

Data analysis and data viz

• Presentation

Tuesday, 17 Sept.

Linked Open Data & ARIADNE

• Presentation contents:
  • ARIADNE Portal
  • Linked Open Data (LOD)
  • AO-Cat ontology

SPARQL

• Presentation contents:
  • Intro to SPARQL
  • Examples of SPARQL queries on DBpedia, Wikidata and ARIADNE GraphDB
  • SPARQL queries from R using glitter package
• R script wikidata.r with Wikidata exercise
• R script ariadne.r with ARIADNE exercise

Resources

• Article Practices of Linked Open Data in Archaeology and Their Realisation in Wikidata by Sophie C. Schmid, Florian Thiery and Martina Trognitz
• AO-Cat ontology
• Introduction to the Principles of LOD on Programming Historian
• Using SPARQL to access Linked Open Data on Programming Historian

Wednesday, 18 Sept.

Intro to spatial data

• R script with required packages.
• R script with the spatial analysis.

(Data circulated on a USB stick.)

Thursday, 19 Sept.

• Presentation (PPTX) on the point pattern analysis.
• R script with the point pattern analysis.

Note on setwd()

• Blog post by Jenny Bryan why not to hardcode setwd() into your scripts and what is the alternative.
• Also check the Intro to R presentation from Monday, where relative paths and project oriented workflow is explained a bit.

Friday, 20 Sept.

R books

• R for Data Science by Hadley Wickham, Mine Çetinkaya-Rundel and Garrett Grolemund – tidyverse packages, data manipulation, visualization etc.
• Geocomputation with R by Robin Lovelace, Jakub Nowosad, and Jannes Muenchow – sf, terra and other spatial packages.
• Spatial Data Science by Edzer Pebesma and Roger Bivand – includes more advanced topics like point pattern analysis with spatstat etc.
• Data Visualization. A practical introduction by Kieran Healy – gives you all you need to be able to create beautiful plots with ggplot2.

Some more glitter and ARIADNE

• R script with an example query on coins from ARIADNE SPARQL endpoint.