SCM2200 Global Data Citizenship

Common Core Curriculum Office (CCCO) > SCM2200 Global Data Citizenship
Department
Supply Chain and Information Management
Cluster
2 (Social Sciences), B (Cultural Diversity and Global Awareness)
Sustainable Development Goal
Good Health and Well-being Industry, Innovation and Infrastructure Reduced Inequalities Sustainable Cities and Communities Climate Action Peace, Justice, and Strong Institutions

Prerequisite

GEN1000 for students admitted to Year 1 before AY2025/26, Year 2 before AY2026/27, or Year3 before AY2027/28, except with the permission of the Module Coordinator

Exclusion

SDS3000

Module Description

Recent figures show that human and machine generated data is experiencing an overall 10x faster growth rate than traditional business data, and machine data is increasing even more rapidly at 50x the growth rate. The acquisition and analysis of data significantly affect almost every aspect of our daily decisions, from personal finance to political election. Because of the vital importance of data, data quality, technology ethics and decision making in this data world have become alarming global concerns. Through this module, students will not only identify and examine the data related global issues and their local impacts or vice versa but also enhance their decision making and critical thinking abilities as responsible global citizens.

Module Intended Learning Outcomes (MILO)

Upon completion of this module, students should be able to:
a. Discuss data citizenship in a globalized world.
b. Identify and assess core issues of data citizenship in a global context.
c. Examine the application and implication of emerging data technologies addressing contemporary global issues.
d. Develop attitude of care and responsibility of data citizenship.

Module Content

1. Introduction

1.1 Framework of Data Citizenship
1.2 Concept of Data Responsibility

2. Nature of Data

2.1 Data Quality
2.2 Data Veracity
2.3 Fake Data

3. Global Data & Big Data Technologies

3.1 Big Data
3.2 Organization of Big Data
3.3 Impacts of Big Data Technologies

4. Data Citizenship in a Globalized World

4.1 Global Data Citizenship
4.2 Global & Local Data Issues
4.3 Data Analytics Application

5. Technology Ethics in Data World

5.1 Ethics in Technology
5.2 Data Security and Data Privacy
5.3 Social Responsibility
5.4 Local Differences

6. Decision Making in Data World

6.1 Logical Thinking in Data World
6.2 Statistical Thinking & Biases
6.3 Scientific Management
6.4 Group Decision-Making Methods

Assessment Methods

1. Class participation (10%)
2. Assignment(s) (40%)
3. Group Project (50%)