Submit a Data Challenge

What do I need to prepare a data challenge?

A data challenge is provided as a 'data brief'. A data brief is a short description of a data set and its associated challenge you have with your data in terms of analysis, visualization, or presentation. Below, you will find the form to submit your brief. You can submit as many brief's and challenges as you wish and work with as many student groups as you like.

Based on your data challenge and presentations, we will chose those challenges suited for the course and our students (graduate students with backgrounds in graphic design, product design, computer science, web-development, media, etc.)

From this list, students will then choose their project. In your data challenge you should address the following information, keeping in mind that your audience are graduate students in design and computer science.

Data and Context:

• Data: What is the data about and where does come from?
• Data type: network data, geographical data, temporal, etc.
• Analysis: Current state of data analysis, related projects.

Challenge?

• Motivation: Why does the data needs to be analyzed / visualized?
• How is the intended audience for your data / analysis / visualization?

Others:

• Are there specific skills / techniques required to work with the data?
• Can we show the data in public, or are there restrictions to data access beyond the classroom. Students can sign a non-disclosure agreement if necessary

What is a "good" data challenge?

Databriefs can cover a vide variety of data sets from research and other areas, including problems and we are curious about your submission. A 'good' data challenge should have the following characteristics:

1. provide data that allows students to understand the importance of analyzing and visualizing these data
2. provide data that makes students feel they are contributing valuable work and creative ideas and tell ideally provide a means for dissemination
3. provide data that challenges creativity and skills
4. provide accessible data and does not require major wrangling.
5. define a challenge that is scoped but potentially open enough for students to diverge from the initial goal (if skills start to diverge).
6. do not expect exact results and do not make fix plans of using the results.
7. ideally, provide data that students can include in their portfolio and show in public — in anonymized or in raw form.

Submitting a Data Brief