Data Scopes workshop materials

Tools:

• UNIX Command line tools
  • Windows users: use Git Bash (portable version)
  • Mac users: use Terminal (comes pre-installed) or iTerm2
  • for modelling, selecting, normalizing via command line tools
• OpenRefine
  • for data normalization and exploration
  • also look at customized distributions and extensions for e.g. LOD, RDF, NER, …
• Text Editor:
  • for note taking, inspecting data, …
  • many good options that have syntax highlighting: Atom, Notepad++, Sublime
• Excel, Libre Office Calc, Google Spreadsheet or some other spreadsheet software
  • for spreadsheet analysis
  • pivot table for linking and classifying data through grouping, co-occurrence
• Voyant Tools no installation needed
  • online text analysis tool, note that this requires uploading your data to the web
  • for user-friendly exploration of texts
• [Palladio] (http://hdlab.stanford.edu/palladio-app/) no installation needed
  • online (optionally) historical visualisation tool bij csv/json input
  • for maps (you need to provide coordinates in csv)
  • for networks and some other visualisations

Optional tools

For those who want to work with more advanced tools:

• Anaconda (Python distribution with many packages and easy installer)
  • for more complex filtering, linking, classifying
  • Jupyter notebook (interactive Python environment in the browser)
• Topic modelling:
  • Mallet (command line) of Topic-Modelling-Tool (GUI)
• Natural Language Processing:
  • NLTK or Pattern Python modules for Part-Of-Speech tagging, Named Entity Recognition, Sentiment Analysis
• Structured data handling in Python
  • [pandas] (https://pandas.pydata.org/) many advanced data handling options, with a somewhat quirky api
  • SciPy for even more advanced data handling and processing