|
課程名稱 |
時空資料視覺化
Spatiotemporal Data Visualization |
|
開課學期 |
113-1 |
|
授課對象 |
學程 人口學程 |
|
授課教師 |
溫在弘 |
|
課號 |
Geog5127 |
|
課程識別碼 |
228EU3400 |
|
班次 |
|
|
學分 |
3.0 |
|
全/半年 |
半年 |
|
必/選修 |
選修 |
|
上課時間 |
星期四7,8,9(14:20~17:20) |
|
上課地點 |
地理電腦室 |
|
備註 |
本課程以英語授課。人口學程選修領域（四）：遷移與空間。
總人數上限：20人 |
|
|
|
|
課程簡介影片 |
|
|
核心能力關聯 |
本課程尚未建立核心能力關連 |
|
課程大綱
|
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
|
課程概述 |
This course provides various visualization methods for detecting patterns and discovering insightful information behind the raw data. These visualization methods, from producing static graphics to creating interactive dashboards and data animations, are categorized into four data types in the course, including numerical/categorical, temporal, spatial, and space-time data. The course also provides practical examples from real-world datasets for helping students understand how to apply these methods for telling stories. Experience in R programming and basic concepts of statistical analysis are prerequisites. |
|
課程目標 |
The objectives of the course are to provide students with the principles for visualization and abilities of storytelling with various types of data. Students will learn how to apply these visualization techniques for real-world datasets and create interactive data dashboards for effective data storytelling. |
|
課程要求 |
Course participation, weekly readings, and written assignments |
|
預期每週課前或/與課後學習時數 |
|
|
Office Hours |
另約時間 |
|
指定閱讀 |
Carson Sievert (2020), Interactive web-based data visualization with R, plotly, and shiny, Chapman and Hall/CRC, https://plotly-r.com/.
Lamigueiro (2018), Displaying Time Series, Spatial, and Space-Time Data with R, Chapman and Hall/CRC, https://oscarperpinan.github.io/bookvis/.
|
|
參考書目 |
Wickham (2021), Mastering Shiny: Build Interactive Apps, Reports, and Dashboards Powered by R, O'Reilly Media. https://mastering-shiny.org/
Data Visualization with R: https://rkabacoff.github.io/datavis/
Fundamentals of Data Visualization: https://clauswilke.com/dataviz/
|
|
評量方式
(僅供參考) |
|
No. |
項目 |
百分比 |
說明 |
|
1. |
Assignments |
40% |
|
2. |
Midterm Exam |
30% |
|
3. |
Term Project |
30% |
|
- 本校尚無訂定 A+ 比例上限。
- 本校採用等第制評定成績，學生成績評量辦法中的百分制分數區間與單科成績對照表僅供參考，授課教師可依等第定義調整分數區間。詳見學習評量專區 (連結)。
|
|
針對學生困難提供學生調整方式 |
|
上課形式 |
|
|
作業繳交方式 |
|
|
考試形式 |
|
|
其他 |
由師生雙方議定 |
|
|
週次 |
日期 |
單元主題 |
|
第1週 |
|
Course introduction |
|
第2週 |
|
Visualize numerical/categorical variables |
|
第3週 |
|
Visualize the relation of two or multiple variables |
|
第4週 |
|
Create an interactive data dashboard |
|
第5週 |
|
Visualize over time: Time on the horizontal axis |
|
第6週 |
|
*Break* (National Holiday) |
|
第7週 |
|
Visualize maps: Interactive geospatial visualization |
|
第8週 |
|
## Mid-term exam |
|
第9週 |
|
## Proposal presentation |
|
第10週 |
|
Spatiotemporal Representations |
|
第11週 |
|
Temporal Visualization: Time as grouping/complementary variables |
|
第12週 |
|
Spatiotemporal Point Observations |
|
第13週 |
|
Visualizing Trajectories |
|
第14週 |
|
Spatiotemporal raster maps |
|
第15週 |
|
Creating space-time animations |
|
第16週 |
|
## Final project presentation |
|