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課程名稱 |
資訊視覺化
Information Visualization |
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開課學期 |
104-1 |
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授課對象 |
文學院 圖書資訊學系 |
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授課教師 |
蔡天怡 |
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課號 |
LIS5079 |
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課程識別碼 |
126EU1440 |
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班次 |
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學分 |
3 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期二2,3,4(9:10~12:10) |
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上課地點 |
圖資資訊室 |
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備註 |
本課程以英語授課。U選課程，大學部與研究所學生均可修習。
總人數上限：30人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1041LIS5079 |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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課程大綱
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課程概述 |
Information can be abstract and needs to be processed so that messages are converted to things that make sense to the receivers. Utilizing various digital tools to visualize information helps us deliver information to our target audience in an intuitive and efficient way.
This course provides an overview about the state of the art in information visualization. The course highlights the principles of producing effective visualizations and introduces practical visualization procedures, including how to visualize information with software and digital tools such as the R package , Tableau, and Google fusion tables.
Specific topics include:
1. The history and background of information visualization;
2. Design principles of information visualization;
3. Data analysis methods and hands-on applications of visualization techniques;
4. Interface design issues in information visualization;
5. Future trends in information visualization.
The course will be delivered through a combination of lectures, presentations, class activities, and discussions.
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課程目標 |
This course aims to provide students with knowledge of how to effectively visualize information and hands-on experience in visualizing different types of information. The ultimate goal of this course is to provide non-technical students with tools to process, visualize, and analyze information of their own interests (e.g., data collected for their theses).
Upon successful completion of the course, students will be able to:
1. Describe the principles of information visualization;
2. Use data analysis methods and visualization tools, such as R, to manage and analyze abstract information;
3. Identify interface design issues in visualization;
4. Apply visualization techniques to specific domains of their own interests.
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課程要求 |
Students are expected to do weekly readings, to participate in class, and to work in groups for projects. Specific course requirements include:
1. Weekly readings
2. Participation and in-class activities
3. Mid-term Project
4. Final Project
Note: This course will be delivered in English. However, all deliverables (i.e., written assignments, term papers, oral presentations, and discussions) can either be in Mandarin Chinese or in English, whichever students feel more comfortable with.
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預期每週課後學習時數 |
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Office Hours |
另約時間 |
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指定閱讀 |
See course schedule |
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參考書目 |
Chang, K.-J. (2010). Evaluation of Visualization-based Information Retrieval Interface- A Case Of EBSCOhost 2.0. Retrieved from http://ntur.lib.ntu.edu.tw/handle/246246/251277#.U2yjy_mSx8F
Few, S. (2009). Now you see it: Simple visualization techniques for quantitative analysis. Oakland, CA: Analytics Press.
Fry, B. J. (2004). Computational Information Design. MIT.
Intel IT Center (2013). Big data visualization: Turning big data into big insights. Intel white paper.
Mazza, R. (2009). Introduction to information visualization. London: Springer.
Maindonald, J. R. (2008). Using R for Data Analysis and Graphics: Introduction, Code and Commentary. Retrieved from http://cran.r-project.org/doc/contrib/usingR.pdf
Spence, R. (2007). Information Visualization: Design for Interaction (2nd ed.). New York: Prentice Hall.
Tufte, E. R. (2001).The Visual Display of Quantitative Information. Cheshire, Conn.: Graphics Press.
Ware, C. (2013). Information visualization (3rd ed.). Waltham, MA: Morgan Kaufmann.
Wu, I.-C., & Hsieh, S.-H. (2012). A framework for facilitating multi-dimensional information integration, management and visualization in engineering projects. Automation in Construction, 23, 71-86.
Online resources:
Lee, M. Data Visualization. Retrieved from http://muyueh.com/seeall/
R project website: http://www.r-project.org/
R Tutorial. Retrieved from http://cyclismo.org/tutorial/R/ and http://www.statmethods.net/graphs/index.html
Stefaner, M. Visual tools for the social semantic web. http://well-formed-data.net/thesis
Visual methods: information visualization design for the people. Retrieved from http://visualmethods.blogspot.tw/
Note: Tableau's data visualization software is provided through the Tableau for Teaching program. |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
Participation and class activities/assignments |
30% |
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2. |
Final project |
40% |
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3. |
Mid-term project |
30% |
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週次 |
日期 |
單元主題 |
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第1週 |
9/15 |
Course Overview |
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第2週 |
9/22 |
Introduction to Information Visualization: Overview, History, Relation to Other Disciplines |
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第3週 |
9/29 |
Big Data, Visualization, and Digital Humanities |
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第4週 |
10/6 |
Visualization Design Principles |
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第5週 |
10/13 |
Cleaning Data and Preparing for Visualization |
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第6週 |
10/20 |
Visualization Systems and Tools |
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第7週 |
10/27 |
Information Visualization in Action
Guest Lecture with Pei-Hong Wu |
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第8週 |
11/3 |
Data Analysis and Table/Graph Design |
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第9週 |
11/10 |
Mid-term project presentations |
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第10週 |
11/17 |
Networks Visualization |
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第11週 |
11/24 |
Hierarchies and Trees Visualization |
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第12週 |
12/1 |
Data Visualization: Buses, Hospitals, and Colors
Guest lecture with Muyueh Lee |
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第13週 |
12/8 |
Geographic Data Visualization |
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第14週 |
12/15 |
Temporal and multidimensional data displays |
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第15週 |
12/22 |
Large Image Collections and Semantic Data Visualization |
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第16週 |
12/29 |
Interaction Techniques and Distortion
Current Trends in Information Visualization |
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第17週 |
1/5 |
Final project presentations |
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第18週 |
1/12 |
Final project presentations |
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