商学院引智项目-夏季小学期课程:Visual Analytics and Data Visualization Tools
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商学院引智项目-夏季小学期课程:

Visual Analytics and Data Visualization Tools

 

美国克莱顿州立大学(Clayton State University )计算机科学与信息技术系教授Junfeng Qu博士自7月2日到南开大学访问并开设Seminar,以下是Seminar的大纲,欢迎感兴趣的师生参加(面向信息资源管理系本科生,也欢迎感兴趣的同学和老师参加)!

 

时间:

7月2日周一,上午1-4节

7月3日周二,上午1-4节

7月4日周三,上午1-4节

7月5号周四,上午1-4节

 

地点:二主楼A104

   Junfeng Qu教授的主要研究领域包括数据科学,知识工程与发现,软件工程,软件测试与质量保证,计算机游戏开发与设计,图像处理与计算机视觉。请有兴趣参加的师生提前注册,注册邮件请发送到李颖老师的邮箱(liying@nankai.edu.cn),邮件请注明姓名、年级、专业及研究方向。

 

Visual Analytics and Data Visualization Tools
Junfeng Qu, Ph.D.

Professor

Department of Computer Science and Information Technology

College of Information & Mathematical Sciences

Clayton State University, USA


Visual analytics has a wide spectrum of applications such as finance, business, medical, health care, insurance, money laundering, capital crimes, terrorism, security, internet security, and network analysis etc. People use visualization tools and techniques to synthesize information and derive insight from massive, dynamic, ambiguous, and often conflicting data. The overall goal is to detect the expected and discover the unexpected. Data visualization and mining is a multidisciplinary field, we will focus on the following areas:


1. Data representations and transformations techniques that covers the data transformation and conversion of data in ways that support visualization and analysis
2. Analytical reasoning techniques that enable users to obtain deep insights to support assessment, planning, and decision making
3. Visual reorientations and interaction techniques that take advantage of the human perception principles to allow users to see, explore, and understand large amounts of information

Schedule:

Lecture

Topic

Reading(GAV)

1

Introduction, information visualization

Chapter 1, 2

2

Data collection, clean

Chapter 3

3

Stats and Layout

Chapter 4

4

Perception and Visual Attributes

Chapter 5

5

Explore and Explain

Chapter 6

6

Visualization tools

Chapter 7

7

D3 Basic

Chapter 8

8

Data Relationships

Chapter 9

9

Hierarchies

Chapter 10

10

Communities

Chapter 11

11

Flows

Chapter 12

12

Spatial Networks

Chapter 13

13

Design

Chapter 16

14

Big Data

Chapter 14

15

Project presentation


Prerequisites:

Basic programming concept, Computer Operating System knowledge and file operations

 

Course Materials & Readings:

Graph Analysis and Visualization (GAV), Richard Brath and David Jonker, Wiley 2015

ISBN: 978‐1‐118‐84584‐4

Illuminating the Path edited by J. Thomas and K. Cook, IEEE Press, 2006

http://vis.pnnl.gov/pdf/RD_Agenda_VisualAnalytics.pdf

 

Software tools:

Gephi: https://gephi.org/users/download/

Cytoscape: www.cytoscape.org

D3: https://github.com/d3/d3

NodeXL: http://nodexl.codeplex.com

Aperture JS: http://aperturejs.com/

yEd: https://www.yworks.com/products/yed/download