Getting Started

Last updated on 2023-11-16 | Edit this page

Estimated time: 12 minutes

Overview

Questions

  • What makes us understand the context of data?
  • How do you approach an unknown dataset?

Objectives

  • Getting familiar with the example dataset.
  • Facing a common challenge when exploring an unknown dataset.

Challenge 0: What do you see?

Your collaborators sent you a link to one of their tabular datasets with the request to inspect and comment on the collected data.

  • Download the data: exampleDataObject.csv (csv file, delimiter: “,”)

  • Open the CSV file with your day-to-day data analysis tool (Python, MS Excel, R, Matlab, etc.)

  • Inspect the data

  • Ask yourself the following questions:

    • Do you get information out of the data?
    • Which challenges do you face?
    • Do you think that something is missing?

  • Write down your answers and impressions. You will have the opportunity to discuss them with everyone in the lesson.

Important: There is no right or wrong in this task. Just note down whatever comes to your mind!

This challenge is meant to get the learners into the mindset of the lesson by giving them a (usually) familiar problem: unsufficiently annotated, uninterpretable data.

Send this challenge to the learners before the lesson starts. During the warm-up and introduction session of your lesson, ask the learners to briefly share their impressions with the dataset. You can use the questions in the overview as a guideline.

We recommend collecting the learners’ statements in bullet points on a white board or in a shared document. After the introduction session, an ad-hoc summary of the statements can be used to lead over to the lesson topic.

The subject of the example data will be revealed after the introductory lecture on “What is data?”, while bridging over to the topic of metadata.