UNITED NATIONSECONOMIC AND SOCIAL COMMISSION FOR ASIA AND THE PACIFICSTATISTICAL INSTITUTE FOR ASIA AND THE PACIFIC (SIAP)

e-Learning Course
Advanced Data Visualization for Official Statisticsand SDG Indicators
3 - 28 July, 2023
I. About the Course
This course is an advanced course in data visualization, conceived as an extension toSIAP’s facilitated course “Data Visualization for Official Statistics and SDG Indicators”
conducted in 2021 and 2022 or, alternatively, to the self-paced course “Principles of Data
Visualization for Official Statistics and SDG Indicators” available on SIAP’s e-learning
platform. This new course focuses on methods to produce high-quality graphics formonitoring and publishing official statistics and the Sustainable Development Goals(SDGs) indicators. It also highlights advanced topics such as network visualization, highdimension data visualization, visualizing uncertainty and address some important issues
when communicating with graphics. In particular, storytelling and the construction ofvisual narratives for any type of audience, or inclusive data visualization, is emphasizedand discussed.
The course provides an opportunity for participants to improve their techniques of datavisualization for data exploration as well as for data presentation of complex, unstructured
or high dimension data. The course proposes cases studies and strategies for visualizing in
multi-dimensions as well as practical methods for representing statistical indicators onmaps or within dashboards.
The course is not based, nor does it focus, on any software. While some popular software
will be used and showcased in the course, participants will be free to use their favourite
software for their needs.
The e-course has been developed as an interactive training composed of 4 +1 modules.
Each module is composed of several mandatory pedagogical activities, following a logicalstructure. Activities include interactive videos, forums, interactive graphical interfaces,
live lectures, webinars, exercises, polls and quizzes. A preliminary module, M0, serves as1

a reminder of data visualization notions, terminology and basic concepts. These notions
will be used throughout the course.1
The course is hosted on the SIAP’s Learning Management System (LMS) which contains
a forum for general questions and interactions with the SIAP’s lecturers and e-learning
platform administrators. Mandatory weekly webinars, in the form of presentations orQ&A sessions will be proposed using the Microsoft Teams platform. The participants are
expected to interact during live sessions and through forums embedded in each module.
Communication, pedagogical resources and webinars are in English.

II. Target Audience
The course is designed for personnel working in the field of statistics, whose main
responsibilities include data collection, exploration, analysis or dissemination of SDG
indicators and related statistics. The course is also open to any personnel in charge of thedesign of data based dashboards and platforms, including people working in the IT or in
the communication sector.
As this course is at an advanced level, participants must have successfully completed
one of these courses prior to registration :- “Data Visualization for Official Statistics and SDG Indicators” a facilitated course
conducted in 2021 and 2022
or, alternatively,- “Principles of Data Visualization for Official Statistics and SDG Indicators” aself-paced course available on SIAP’s LMS..
Participants are expected to have some experience in producing data-based graphics usingany type of software.

III.

Learning Objectives

At the end of the course, participants should be able to:1

Identify data visualization objectives and limits
Comprehend data visualization as a visual language
Visually apprehend data in multiple dimensions
Apply data visualization design rules and principles
Elaborate strategies for visualizing statistical indicators on maps
Apprehend network representation and identify the limits of their construction
Discuss visual narrative concepts
Apprehend data storytelling
Identify and focus on inclusive data visualization
Analyse the importance of visualizing graphics when uncertainty exists

The module M0 is not a substitute to the completion of data visualization mandatory courses.

2IV.

Course Design and Content

The course is divided in 4modules and will last for 4 weeks and will require approximately
3h of work each. The elements (slides and references) used for each activity will beavailable for download in pdf format. We also propose optional activities based on popular
data visualization software, links to free online tools and to bespoke interactive pedagogicalexercises.

ModuleCoverage

0 – What is Data Visualization-Data visualization objectives and limits
Features and goals of popular graphics
Types of graphics to represent SDG indicators
Design of a graphic based on a data set-

Statistical indicators on maps
Construction of networks
Visualizing relationships with networks
Issues in network visualization-

Visualizing in high dimensions
Visualizing uncertainty
Visualizing uncertainty in High Dimensions
Visualizing surfaces-Interactivity in data visualization
Design principles
Gestalt principles
Visual narratives
Storytelling

1 - Maps and Networks

2 – Advanced Data Visualization Methods

3 - Interactivity, Storytelling and VisualNarration

4- Inclusive and Ethical Visualization

3Unused data visualizations
Inclusive visualization
Ethical visualization

V. Evaluation
The evaluation will be based on the learner’s ability to apply the methods and training
materials described during the course, as well as on their capacity to recall the main
outcome of each module. The final grade will be based on two mandatory assessments
exercises:
1) Multiple Choice Questions (MCQ)-like tests to complete at the end of each module.
2) An individual data-based project to be submitted before the end of the course.

To succeed in the course participants must have at least a total score of 70/100, and comply
with the following conditions:- Complete all of the mandatory activities in each module.
- Complete all the tests at the end of each module- Complete the individual data-based project activity in due time
Participation to the various chats and Q&A will provide bonus points.

Participants must complete the end-of-course evaluation to receive a certificate.

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