• Arcada - University of Applied Sciences in Helsinki (Finland)
• Professor: Sandra Becker
• Contact: Via Email
• Term: Winter 2022
• Lectures: 12 * 2h including 10min break
• Course material

Arcada is a multi-professional University of Applied Sciences in Helsinki (Finland) with the philosophy to work across disciplines and advance culture and knowledge. The curriculum of each degree programme at Arcada is composed of modules. The modules define the competencies that you need to attain in order to graduate.

"Data drives discovery"

Efficient pattern detection combined with logical interpretation is at the heart of any data driven project. People with these skills are in high demand. Or, one could even claim that everyone participating in modern work settings, need to be able to “read” data.

In this context data visualisation has become an intriguing field in many areas as it points to its underlying data and allow an active reader to question assumptions, consider alternatives, and derive new insights.

It has become a driving force in the task of unravelling data complexity and helping to bridge the gap between the flood of data and ensuring decision makers can make more effective and informed decisions.

This course will take on these interrelated challenges while striving to build student skillsets. Students will take on a variety of data manipulation and visualisation challenges throughout the semester, all loosely related to system modelling.

• Statistics Fundamentals
• Dataset Sourcing, Cleaning, and Joining
• HTML, CSS and JavaScript
• Interaction and Animation Principles
• Web based visualisation using d3.js
• Visual data literacy
• Workflow of visual data projects

After completing this course the students will have a deep understanding of visual data analysis in oder to facilitate pattern detection and interpretation.

This course is all about hands-on coding, therefore the focus will be to rebuild an advanced data visualisation project in a step by step approach. The final goal is to allow students to rebuild similar complex visualisations after finishing this course.

During the course the students will gain a deep understanding of the following programming languages and libraries:

• HTML to define the content of web pages, with a special focus on SVG

• CSS to specify the layout of web pages

• Javascript to program the behaviour of web pages

• Observable is a web-first interactive notebook to build fluid exploratory interfaces, test hypotheses by manipulating live simulations as well as visualize algorithms as they run. Working in the notebook allows you to tinker, try things and interact real-time as you explore. The notebook is a running environment with no compiling required.

• Arquero.js is a library for query processing and transformation of array-backed data tables. Following the relational algebra and inspired by the design of dplyr, Arquero provides a fluent API for manipulating column-oriented data frames.

• Plot.js is a library to help quickly visualize tabular data. It has a concise and easy to learn API to foster fluency. It's based on d3.js and very useful for explorative visual analysis

• D3.js is a library for data visualisation, which has since its invention by Mike Bostock at the NY Times Data Lab become the gold standard of data visualisation facilitation tools. The core paradigm of D3 is to bind data to Document Object Model (DOM) elements of a web page in order to drive the content and appearance of those elements: hence Data-Driven Documents!

• Lectures
• Practical exercises
• Assignments
• Individual studies
• Final project

In this course the students will work a lot with code and create their own data representations. Therefore the whole assessment will be "hands on".

I. Assignment - 15p
II. Assignment - 15p
Final Project - 70p

51 - 60p Pass
61 - 70p
71 - 80p
81 - 90p
91 - 100p Excellent

In this course we are using observable notebooks to explain concepts and general code patterns. Moreover for general data visualisation theory we will be using this presentation as well as this D3.js presentation. The main use case for this course will be the data visualisation project The Unwelcomed please check the code under this link

• Data Visualization video blog
• Society's Nightengale
• Pudding
• Flowing Data
• Information is Beautiful
• Design Coding
• Datawrapper blog
• Podcast serie: Datastori.es