Master
2019/2020
Data Visualization
Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type:
Elective course (Prototyping Future Cities)
Area of studies:
Urban Planning
Delivered by:
Vysokovsky Graduate School of Urbanism
When:
1 year, 1 semester
Mode of studies:
offline
Instructors:
Хайман Эдуард Вадимович
Master’s programme:
Prototyping Future Cities
Language:
English
ECTS credits:
4
Contact hours:
40
Course Syllabus
Abstract
Learn how to translate analytical projects in the scope of applications, web-services or platforms. How to define goals and objectives for a new application, web-service or platforms including who can use it, capability for advantages and benefits. Building up design and developing workflow including a definition of a necessary toolbox, completeness of input data, maps and other assets, risk possibilities during the process of the design and developing. Learn how to use visualization data as a tool to make conversation between data and users. How to use modern GIS tools to make maps, what rules and specific requirements are necessary for data and what formalization and figuration are necessary for maps. What the best practice in data visualization and how to design a visualization approach tailored maid for the specific data structure, aims, and goals that refer to the scope of work and idea of the applications, web-services or platforms. Learn to build up design prototype for individual data analytical project. Unrolling of core idea for app into user experience and interface design. Define how app prototype can be scaled into complet industrial app in terms of functionality, business logic of the app, data base structure, workflow, user experience and user design, data visualization.
Learning Objectives
- Give broad spectrum of the contemporary theories and practice of application and platform development, user experience and user interface design related to urban analysis.
- Give a number of skills needs for building up of full workflow, design and development managing of urban analysis platforms and apps.
- Give a toolbox of soft and hard skills for interface prototyping and data visualization prototyping.
Expected Learning Outcomes
- As a result of mastering the discipline student have: to know: key points of user interface design; key points of user experience; key points of managing app and platform developing; key points data of geo-spatial data base; key points of data visualization related to urban data analysis; toolset with help of which design prototypes is developed; prototype of user interface of urban analysis app.
- To be able to develop prototype of interface to design data visualization assets to buildup app developing project
- To possess the following skills: to lead the app design and developing related to urban data analysis; to make presentation of app and platform proposals.
Course Contents
- Topic 1. How to translate analytical projects in the scope of applications, web-services or platforms.How to define goals and objectives for a new application, web-service or platforms including who can use it, capability for advantages and benefits. Building up design and developing workflow including a definition of a necessary toolbox, completeness of input data, maps and other assets, risk possibilities during the process of the design and developing.
- Topic 2. Using visualization data as a tool to make conversation between data and users.How to use modern GIS tools to make maps, what rules and specific requirements are necessary for data and what formalization and figuration are necessary for maps. What the best practice in data visualization and how to design a visualization approach tailored maid for the specific data structure, aims, and goals that refer to the scope of work and idea of the applications, web-services or platforms.
- Topic 3. Building up design prototype for individual data analytical project.Unrolling of core idea for app into user experience and interface design. Define how app prototype can be scaled into complet industrial app in terms of functionality, business logic of the app, data base structure, workflow, user experience and user design, data visualization.
Bibliography
Recommended Core Bibliography
- Iliinsky, N., & Steele, J. (2011). Designing Data Visualizations : Representing Informational Relationships. Sebastopol, Calif: O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=414870
Recommended Additional Bibliography
- An introduction to data visualizations for open access advocacy. (2015). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.9222CCB7
- Cox, D. J. (2004). The Art and Science of Visualization: Metaphorical Maps and Cultural Models. Technoetic Arts: A Journal of Speculative Research, 2(2), 71–79. https://doi.org/10.1386/tear.2.2.71/0
- Hemmersam, P., Martin, N., Westvang, E., Aspen, J., & Morrison, A. (2015). Exploring Urban Data Visualization and Public Participation in Planning. Journal of Urban Technology, 22(4), 45–64. https://doi.org/10.1080/10630732.2015.1073898
- Megrey, B. A., & Moksness, E. (2002). Visualization of Spatial Data Introduction. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.901DB04D
- Moere, A., & Hill, D. (2012). Designing for the Situated and Public Visualization of Urban Data. Journal of Urban Technology, 19(2), 25–46. https://doi.org/10.1080/10630732.2012.698065
- Revisiting Urban Dynamics through Social Urban Data: Methods and tools for data integration, visualization, and exploratory analysis to understand the spatiotemporal dynamics of human activity in cities. (2016). https://doi.org/10.7480/abe.2016.18