06. Data

December 14, 2020

Agenda

1. Updates
2. Data
3. For next time

Meeting notes

Note-taker: Zach

Business

• Workshop ideas & dates
  • Zach - QGIS workshop, what GIS?
    • for first workshop show projects across disciplines. Does not need to be specific to Arch, Classics, charset
  • Kristen - html Workshop
    • Security- community.reclaimhosting.com/installing-free-ssl-certificates/325 http vs https: the “s” means the site is certified as protecting data through encryption.
      • in domain of ones own go to “Let’s Encrypt SSL”
  • Thu - workshop on introduction the digitization of papyri in papyrology
    • OCR optimizing? photo processing steps to optimize? See Tesseract OCR.
    • Talked about ways to make this more of a DS session.
  • Workshops on Zoom. Will be recorded and can be put on Panopto
• Roles for Spring work
• Questions and updates
  • Examples of professional websites: added to Resources for Session 04
    • examples on the DSGF syllabus page.
    • question about why you would share a github profile: sharing code, collaborative writing, data scraping, etc.
    • unsplash.com - photos for everyone.
  • Kristen question: creative commons photos. Some CC request a citation. How do you cite?
    • AM response: Add caption or photo credit in a footer. Unsplash has code for embedding a badge or text to a photo.

  • Metadata and images: Omeka and Scalar show metadata. Scalar especially using javascript and to a lesser extent css. Wax.

  • Accessibility
    • Kristen, site was pinged for text size and photo alt text . Language needs to be declared
    • web accessibility evaluation tool
    • Skip tp main content link should be present.
  • Security - instructions on issuing ssl certificate for your domain

Data

• Data Cleaning with OpenRefine tutorial
• OpenRefine
  • Data cleaning with open refine. See link on DSGF syllabus.
    • Download and play around with it.
• Tidy data
  • specific approach common to people using R. How to turn a dataset into something that is compatible with R’s tools.
  • Data provides. Structure and standardization.
• What is data? Think about how data is defined and managed. Standardization for machine learning vs. digital exhibition vs. spatial analysis.
  • Data is specifically rhetorical. It is not data unless you are looking at it “as data”. Likewise cleaning data requires interpretation and a priori structural ideas.
  • Tabular vs. graph data (hierarchical, rhyzomatic/networked, or polarized)

Resources

• DataBasic
• From Data to Viz
• Rawgraphs

For next time

Friday, January 22

• Choose a date and time for your workshop and write a short description
• Propose a lightning-round topic for the Grad Showcase in February
• Email me and let me know:
  1. How many hours you’d like to work next semester
  2. Your preferences between: running a community of learning, teaching additional workshops, helping develop and run events, supervising undergraduates
• Finish OpenRefine tutorial

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