85466 - Web Writing and Digital Storytelling (1)(LM)

Academic Year 2020/2021

Learning outcomes

At the end of the course the student will learn how to write for the Web, understanding the principles related to target audience, clear phrasing and keeping short. These principles will dialogue with the relationships between text and other media. In this context the use of digital media for telling stories will be analyzed. The students will be able to use different techniques for exploiting digital narrative methods.

Course contents

At the end of the course the student knows principles and methods for knowledge acquisition, data reengineering, and sense making. The student is able to manipulate and existing datasets, organise them according to existing vocabularies, transform them in Linked Open Data, and create web applications that leverage data storytelling techniques.

The course is organised in lectures. Each lecture discusses one aspect of the pipeline for creating multi-purpose digital resources that leverage Linked Open Data, and includes references to existing tools and resources. Hand-on classes, in a tutorial-fashion, will provide real-world examples of applications development by means of well-known programming languages (e.g. Python, Javascript). Basic knowledge of Python, Github, and web languages is required.

The lectures [L] and hands-on classes [H] are organised as follows:

  1. [L] Course introduction
  2. [L] Preliminary concepts on Data and Data visualization strategies
  3. [L/H] Preliminaries of Semantic Web
  4. [L/H] Data access and extraction
  5. [L/H] Data sense making and data exploration
  6. [H] Languages and libraries for data analysis: Jupyter notebook, Data exploration
  7. [L/H] Web development and Client-side libraries for data visualisation
  8. [L/H] Communication strategies and digital storytelling techniques
  9. [L/H] Seminar / 
  10. [L] Publication, tools and best practices. Course recap, evaluation grid, Q&A

Readings/Bibliography

Lecture notes will be freely available from a dedicated GitHub repository (https://github.com/marilenadaquino/epds).

Slides and any additional material will be made available a few days before each lecture in the same repository.

Suggested readings will be provided during classes.

Teaching methods

16-hour lectures, 14-hour hands-on classes

Assessment methods

Students are required to present either a group web project or an individual web project leveraging technologies shown during the course (or other compatible technologies despite not discussed in depth during the course).

The exam consists of a 15-minute presentation of the project, followed by question and answering.

In case of group projects, single students’ contributions to the project will be evaluated.

The evaluation grid will be discussed during the course.

Teaching tools

Students must be able to access course classes that are available on GitHub (https://github.com/marilenadaquino/epds). By the end of the course students should create a GitHub account (free of charge) in order to publish the web project.

Students must have installed an updated version of python (the latest if possible) on their personal computers and have chosen a preferred rich text editor. The teacher will show examples by using Atom editor. PyCharm, SublimeText 2.0, or similar editors are good solutions too.

Office hours

See the website of Marilena Daquino