AR3023 Data Visualisation and Analysis Syllabus:
AR3023 Data Visualisation and Analysis Syllabus – Anna University Regulation 2021
OBJECTIVES
To give exposure to the importance of understanding Information through visual thinking.
Enabling skill in exploring the various ways of visualising and analysing data.
To enable generating innovative diagrams from the collected data to discern and recognise patterns and phenomena.
UNIT I INTRODUCTION TO DATA VISUALISATION
Introduction to data visualisation. Principles of data visualisation. Conventional methods of visualisation. various applications. Types of Digital Data and Data structures. Terminologies Used in Big Data Environments. Various ways of Collection, Processing and Analysing the data. Classification of Data. Analytics frameworks. Open data platforms.
UNIT II OUTLINE OF DATA VISUALISATION TOOLS
Overview on Visual analysis languages. Interactive data visualisations. Multivariate visualisation. Geospatial visualisation. Data Visualisation platforms-Tableau, Polaris, GGplot2, Matplotlib,PowerBI, etc.
Exercises using some of the above platforms using sample datasets.
UNIT III DATA VISUALISATION IN ARCHITECTURE
Introduction to mapping and data visualisation in architecture. Types of visualisation tools -2D/3D. Architectural design process outline. Various Data collection techniques. Basics sets of architecture and urban design data required. Quantitative and Qualitative data. Spatial and Non-Spatial data. Introduction to functional visualisation of various attributes of buildings – Activity, zoning, matrix, proximity chart, human behaviour, demographics, circulation patterns, etc.
Exercises related to above.
UNIT IV ANALYSIS OF ARCHITECTURAL AND URBAN DATA
Overview of recent design approach related to study and design for people and space with help of big data. Analysis and visualisation of data. Quantitative and Qualitative data. Programme, Micro climate, Geospatial Analysis, Energy modelling, Vegetation, User behaviour studies, Sensory analysis, Post occupancy studies, Participatory/Interactive approach etc.
Case studies of Data Visualisation as design process- Works of Rem Koolhaas, UN Studio, FOA etc.
OUTCOME
Knowledge about the importance of data visualisation.
Familiarity with different methods and techniques of data visualisation.
Skill in working out simple exercises related to data visualisation in the realm of architecture and urban design.
TEXTBOOKS
1. Winifred E. Newman, Data Visualisation for Design Thinking: Applied Mapping, Routledge 2017
2. C. J. Date, A. Kannan, S. Swamynathan, “An Introduction to Database Systems”, Eighth Edition, Pearson Education, 2006.
3. Andy Kirk, “Data Visualization: a successful design process”, Second Edition, Packt publishing limited,2012
4. Andy Kirk , “Data Visualisation: A Handbook for Data Driven Design”,Second Edition, SAGE Publication Ltd,2019
5. David McCandless ,”Knowledge is Beautiful”,William Collins,2014
6. David McCandless ,”Information is wealth”,William Collins,2012
7. Anthony Vidler, ‘Diagrams of Diagrams: Architectural Abstraction and Modern Representation’, Representations, No. 72. (Autumn, 2000), pp. 1-20
8. Mark Garcia, ‘The Diagrams of Architecture’, Wiley 2010.
9. Iain Fraser and Rod Henmi, ‘Envisioning Architecture – An Analysis of Drawing, 1991’,John Wiley and Sons, 1993.
REFERENCES
1. Robert S. Wegant, ‘BIM Content Development: Standards, Strategies, and Best Practices’, John Wiley, 2011.
2. Chuck Eastman et al, ‘BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors’, John Wiley, 2011.
3. Joseph Clarke, ‘Energy Simulation in Building Design’, Routledge, 2007
4. BIM Handbook: A guide to building information modeling for owners, managers, designers, engineers and contractors (second edition) by Chuck Eastman, Paul Teicholz, Rafael Sacks, and Kathleen Liston Available online (e.g. $55 on Amazon) – please use the second edition ISBN-13: 978-0470541371 ISBN-10: 0470541377