that maps the emotions of the inhabitants of Doetinchem. D-tower measures HAPPINESS,
LOVE, FEAR and HATE daily using different questions." http://www.d-toren.nl/site/
...
Unit one, Historical and cultural approaches to information
Aug 31::
Introduction
Review syllabus: http://beforebefore.net/scima300/f15/
The Processing programming language
***What does it mean when something is historically and culturally specific? Our assignments over the next few weeks will hopefully address this question. Get psyched!
No Class!
Read:
- https://processing.org/overview/
Do:
Install Processing on your computer from the Processing.org site
If you are new to Processing:
Do the following tutorials from the Processing tutorial page and bring to class:
- "Getting Started"
- "Coordinate System and Shapes"
- "Color"
Optional:
- Watch some of the "Hello Processing" tutorial videos with Daniel Shiffman
If you are experienced with Processing:
Do a tutorial on one of the following concepts (assigned to you in class): variables, conditionals, for loops, arrays -- incorporating one of the following: song, dance, sculpture, drawing or storytelling.
Aim for clarity: a novice to programming should be able to get the concept implicitly from your tutorial. This takes time and planning to do well.
zip up, label Hw1_lastname_firstname.zip and bring to class the following week. (note: this is categorized as homework (Hw) rather than an Assignment (A))
Using spreadsheets
Organizing Digital data
Intro to Processing
BEFORE CLASS:
Read:
- 9 Essential Things you Should Know How to Do in a Spreadsheet
- An Introduction to Visualizing Data sections 1 through 5
Assignment Due:
A1a :: Data Selfie ::
1) Collect ALL your digital communications from a 72 hour timeblock (you can do longer if you need more data, but not shorter) and organize them in a spreadsheet. Use a minimum of 12 metadata categories to organize this collection. You are not sharing the content of your collected data, but the metadata, the "data about the data": time, date, location, medium etc. Are they: email, chat, twitter, social network sites, listserves, blogs, text messages and phone/voicemail? What types of relationships (immediate family member, close friend, acquaintance, etc.) are you communicating with? What kinds of conversations and data exchanges did you have; were they executables, coordinating a physical meeting, gossip, intimate or humourous...? Are the messages short or long? Classify the contexts (from bed, campus, class, cafe) and mood. A truly excellent work will conceive of innovative categories for classification and analysis in addition to the ones above. In addition to the above, you will need a "unique identifier" for each row or entry. This is usually a unique number (incrementing by 1) that is assigned to each row. Make the unique identifier the first column on your spreadsheet.
2) Write 1-2 paragraphs on your initial observations about your 72 hour digital communication data. Are there certain patterns that you see? If someone who didn't know you were to read this data, what would they conclude about you?
Put work into a folder called A1a_lastname_firstname and them compress so that your zip file is A1a_lastname_firstname.zip and bring into class. (note: this is categorized as an Assignment (A) rather than an Homework (Hw))
**note: If you are unfamiliar with using spreadsheets please spend some extra time familiarizing yourself with how they work and with the reading above.
IN CLASS:
- Variables
- Review Hw.
- Review A1a. What observations were made?
- Identify variable types for the kinds of data you have. Make notes for how the data could be understood visually
BEFORE CLASS:
Read:
- from Ben Fry, Visualizing Data: The Seven Stages of Visualizing Data (1st chapter)
- and Getting Started with Processing
- Read about GitHub (this is another reference if you need it)
***optional: review this text on variables
Do:
- answer the following questions about your data selfie in a text document: 1) What is the data? 2) What are the relationships between the variables? 3) How is the data organized? / How could it be organized? 4) What needs to be communicated? / what is the most interesting? 5) discuss 3 ways of visualizing your data, and what data from your collection you will use (communication over time, mood and platform, network) 6) if you used a pie, bar, or bubble, what data would you use for each kind of visualization?
- make new sheets (w/in same spreadsheet) with just the data you need for 3 types visualizations (make one location based). Please indicate somewhere what kind of visualization you are envisioning for each sheet. make sure to keep a unique id for each row that is consistent with your original sheet's rows.
- Revise your artistic programming-tutorial-without-code if necessary.
- Register with GitHub, using your cca email. Opt for a free account if prompted.
- put all work in a folder called A1b_lastname_firstname. Zip this up so that the file is A1b_lastname_firstname.zip, and email to prof. In the body of the email, include your github username.
IN CLASS:
- Visualizations
- More programming review - if statements, for loops
- functions in Processing: PImage, loadImage(), image(), getRowCount, getFloat, getString, createWriter() and related, map(),
- Load and Save tables
- look at this code corrected 5:49p 9/21
- Install git
- Introduction to terminal: cd, ls, pwd, mkdir, touch, cp, mv, rm
Visualization studio
BEFORE CLASS:
Read:
- from Ben Fry, Visualizing Data: Mapping
- read Chapter 1, Getting Started with Git, follow instructions and install if you haven't already, also do the section on set-up
- if you've never used the command line before, you may need to read up a bit: Command Line for Mac, or Command Line for Windows
Do:
- A1c :: Finish mapping some data from your digital data selfie. You can use location to show actual location of communication, or have the map be somewhat abstract, representing platform or receiver, for example. The size of the bubbles should represent some aspect of your data, like amount of use. Consider using color as representing some other aspec of your visual, like dominant mood as related to location. Use TSV or CSV files. Submit work via email.
IN CLASS:
- review maps
- continue basic review of programming - arrays (just check out the first 3 sections ), object oriented programming
- studio time to mess with code that demos arrays and classes if you want (download zip file)
- studio time with time and bar graphs, and see: Ch4, Time Series and download this code
- git demo, - practice submitting work to github. upload c4_lastname_firstname.pde to the github repository:
- follow these instructions: https://github.com/SCIMA-300/directions_for_submitting_work/blob/master/DIRECTIONS.md, or add via command line or desktop git
Time
BEFORE CLASS:
Read:
- Ch4, Time Series
- read through the following, https://github.com/SCIMA-300/directions_for_submitting_work/blob/master/DIRECTIONS.md. If you want to deepen your use of git, and collaborate with other students in the class, look at Git Basics
Do:
- this week you have a couple of options. you may continue to develop your map and data visualizations, visualizing new data sets derived from your data selfie, or you may work with new code offered in the reading and here to visualize some data from your data selfie over time. If you are really stuck with the code, please be in touch and we can come up with the right approach for your level. Upload your work into the A1d repository on GitHub here : https://github.com/SCIMA-300with the lastname_firstname naming schema (following the instructions above)
IN CLASS:
- more basic programming review
- review homework, look at examples
- Studio time: Play with sample code of arrays and objects
- Assess where you are in the process visualizing your data selfie in terms of Ben Fry's acquire > parse > filter > mine > represent > refine > interact, and where you need to go next in order to represent some aspect of your data selfie in a meaningful way. Do you need to go back to acquire and generate a wholly new data set? or just back to filter to sift through data you have and represent it in a new way? Or, are you ready to refine your visualization? Decide what is next, define your goal for the next week and then list out the steps to getting there and also identify your biggest challenge. Post this list of steps to the c5 repository on GitHub
- Work on the assignment for Oct 12th.
- more on git and GitHub
- get me your late work by the end of Thursday with no penalty. I will start deducting points beginning at 12a Friday morning.
Oct 09::
- HACKER HOURS! 12-3p in the HYBRID LAB.
- Come get help with assignments, meet programmers at all levels, help others with their code, mess with Git and GitHub!
Oct 12::
BEFORE CLASS:
Read:
- from James Gleick, Information: A History, A Theory, a Flood: Ch7/ Information Theory
- About Git Branching
- Ben Fry, Ch5, Connections and Correlations
Do:
- For your A1e visualization you have 3 options to appraoch your selfie. 1) You can go back to the acquire step (defined by Ben Fry) and use new data from your digital data selfie to make a new visualization (possibly using the connections and correlations code above), or 2) you can filter data you've already been working on to generate a more meaningful visualization, or 3) you may be ready to refine your visualization and add more interaction. Add your work to the A1e repository before class
IN CLASS:
for the first half of class::
- 1) work out any final issues you have with A1-A1e. Refine and add interactivity and/ or movement with whatever code you are working on.
- 2) consider directionality. Using illustrator, pop-ups within Processing, or simple shapes and lines (that draw for a TSV file or not), demonstrate the directions of your messages. Add your work to the c6 github repository, or zip up and email.
for the second half of class::
- 3) start thinking about how to organize your A2 data
Analog/ non-digital communications/ transmissions
BEFORE CLASS:
- Read: Warren Sack, Public Space, Public Discussion and Social Computing
- Review: James Gleick, Information: A History, A Theory, a Flood: Ch7/ Information Theory
Do:
Assignment 2:
- A2a :: Analog Data Selfie ::
- Visualize your analog communications: Document your analog communications for a 24 hour time period. How do you communicate to drivers and bikers when crossing the street on foot, when ordering coffee in a busy shop, or late at night in a rough neighborhood. Consider vocal and non vocal communications. You may use some categories/ metadata that you used for your digital observations, but you will also need to add new ones. Note the difficulty in establishing metadata categories for non-digital communications. Organize your categories in a spreadsheet, TSV, or CSV as in A1, label A2_lastname_firstname and put in GitHub or zip up and email to professor before class.
Analog data
BEFORE CLASS:
Do:
- Consider your A2a analog communication data. You may work in any visual environment you wish to visualize your non-digital communications. How do you understand context, meaning and shared understanding in these communications? In the next few weeks we will work on visualizing and quantifying this data in various ways, but this week you can be creative and think outside of the box in regards to your visualizations. Share all Processing sketches via the A2b github repository, or send sketches, drawings or vector graphics via email.
IN CLASS:
- simple scatterplot (from ch 06 of Ben Fry's Visualizing Data)
- more devloped scatterplot
- look at more examples of object oriented programming
- handout on advanced object oriented programming
Analog data
BEFORE CLASS:
Read:
- Edward Tufte
- Fry, Ch06 from Visualizing Data
Do:
- look at/ mess around with Scatterplot Map code:
- simple scatterplot (from ch 06 of Ben Fry's Visualizing Data)
- more devloped scatterplot
- Work on visualizing your Analog Data Selfie in code. Post work in progress to GitHub or email.
Digital and Analog data selfies combined
BEFORE CLASS:
Read:
- Edward Tufte
- review chapters on git and GitHub above
Do:
- Finish and submit at least two iterations of your Non-digital data selfie by the 16th.
IN CLASS:
- Sketch out a visualization that compares elements of your digital and non-digital data selfies.
- GitHub tutorial - please bring laptops to class. Update:: GitHub tutorial will happen next week
Digital and Analog data selfies combined
BEFORE CLASS:
Read:
- Edward Tufte
- review chapters on git and GitHub above
Do:
- Finish and submit at least two iterations of your Non-digital data selfie, by email or GitHub
IN CLASS:
- Abram Stern, visiting artist
- Update: GitHub tutorial will happen this week! - please bring laptops to class.
- see installing git
Nov 23::
Visualizing networks and systems
Studio
BEFORE CLASS:
Read:
- review terminal commands for mac or windows
- networks and data in Fry's Visualizing Data
- See assignments page for final assignment
Do:
- practice cloning and pushing and pulling to students repository in SCIMA 300 organization
IN CLASS:
- More on Git and GitHub
- Studio time, review last Asgn
- ArrayList, Data examples
Nov 30::
Networks cont
Studio time
- See assignments page for final assignment
Wednesday 12:30-3 with J.D.
Friday 11:30-2:30 with Margaretha and Michael
Dec 07::
Studio time
Review semester's work
BEFORE CLASS:
A2 is due!