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Data Visualization

 

MALS students take four classes within the program—Introduction to Graduate Liberal Studies, two core courses in their chosen track, and the thesis/capstone project—and choose their remaining electives from among courses offered across the doctoral and certificate programs in the Social Sciences and Humanities at the Graduate Center.

 

The images on this page are visualizations of cultural data created by Prof. Lev Manovich (The Graduate Center, CUNY), his students and the members of Software Studies Initiative (softwarestudies.com).

MALS Track in Data Visualization

 

Introduction

The MALS Track in Data Visualization is the first program nationally and internationally to focus on the critical study of data visualization, placing its subject matter in the context of humanities and cultural theory (in addition to teaching the students necessary practical skills). In the last fifteen years, software-driven visualization has emerged as one of the key areas of digital culture. More recently, it has also been recognized as the essential part of digital humanities’ set of methodologies. As more disciplines and areas of society start using large and complex data sets, and as data-driven analysis and knowledge creation grow in importance, we can expect that the importance of visualization will also continue to grow side-by-side.Learning about the field of digital humanities will expose students to important examples and practices of humanistic visualizations. It will also help them to approach the practice of visualization critically. They will learn to think reflectively about the decisions that go into the stages of data exploration and visualization: constructing a dataset, selecting which variables to visualize, selecting visualization techniques, making design decisions regarding colors, graphic styles, composition, etc.  For example, which projection method should they chose when designing a map? What are the histories of various visualization methods? Or more, generally, what does it mean to translate a novel, theatre play, or a video game into “data” which is then visualized? What new aspects of humanistic experience can be gained though such a translation, and what is lost? How to combine “distant readings” (exploring patterns in large cultural data sets) and “close reading” (detailed analysis and interpretation of the details of artistic texts)? 

Students in the track will take two core courses: one is “Introduction to Digital Humanities,” which explores this innovative methodological and conceptual approach to scholarly inquiry and teaching, and the second is a course on “Data Visualization Methods,” which will introduce students to foundational techniques in data visualization. After taking these two core courses, students will take classes through the GC curriculum, gaining contextual knowledge that will help ensure that the visualizations they create are grounded in disciplinary practices and discourses. Understanding the history of art, literature, theatre, film, and other subjects will allow students to consider data visualization as another visual communication medium, with its own language and conventions. At the same time, exposure to modern art and/or history of film will help them understand how visualization artists are challenging these conventions, experimenting with new techniques and approaches.

     

Degree Requirements

This Master's degree program requires the following coursework for a total of 30 credits:

  • A required introductory course [MALS 70000: Introduction to Graduate Liberal Studies].

  • Two required core courses to introduce the student to data visualization topics, and current scholarship in the field [MALS 75400 and MALS 75300].

  • 18 credits from courses of the student's choice.

  • A master's thesis/capstone project [MALS 79000].
 

Core Courses

  • MALS 75400 Introduction to the Digital Humanities

The dramatic growth of the Digital Humanities (DH) over the past half dozen years has helped scholars re-imagine the very nature and forms of academic research across a range of scholarly disciplines, encompassing the arts, the interpretive social sciences as well as traditional humanities subject areas. This initial core course will explore the history of the digital humanities, focusing especially on diverse pioneering projects and core texts that ground this innovative methodological and conceptual approach to scholarly inquiry and teaching. It will also emphasize ongoing debates in the digital humanities, such as the problem of defining the digital humanities, controversies over new models of peer review for digital scholarship, issues related to collaborative labor on digital projects, and the problematic questions surrounding research involving “big data.” The course will also emphasize the ways in which DH has helped transform the nature of academic teaching and pedagogy in the contemporary university with its emphasis on collaborative, student-centered and digital learning environments and approaches. The course will also take up broad social, legal and ethical questions and concerns surrounding digital media and contemporary culture, including privacy, intellectual property, and open/public access to knowledge and scholarship. Students completing the course will gain broad understanding of the emerging role of the digital humanities across several academic disciplines and will begin to learn some of the fundamental skills used often in digital humanities projects. 

  • MALS 75300 Data Visualization Methods

This class is designed to teach the students practical skills in visualizing and analyzing cultural and social datasets. The main tool we will use is R, the leading open source platform for data analysis. The students will be also introduced to other popular tools for creating interactive web-based visualizations.
 
We will cover the following practical topics: preparing data for analysis and visualization; summarizing data; basic visualization techniques for 1D, 2D, and multi-variable data; use of visualization for exploratory data analysis; creative data visualization; history of visualization; elements of graphic design for visualization and project web site design; strategies for presenting projects online; how to write effective project descriptions for the web presentation; promoting projects through social media and getting media coverage. We will also examine papers from computational social science and data analysis/visualization projects by designers and artists.

Elective Courses

Electives can be chosen among courses offered across most of the doctoral and certificate programs in the Social Sciences and the Humanities at the Graduate Center.

For related coursework in Data Visualization, students may look to offerings in the MALS concentration in Digital Humanities, the certificate program in Film Studies, and the doctoral programs in English, Theatre, History, and Economics.

Faculty

GC and other CUNY faculty associated with this track:

Library Resources

Visit the GC Mina Rees Library's Liberal Studies Research Guide.
Students' contact for Data Visualization research is reference librarian Stephen Zweibel.


Questions about the MALS track in Data Visualization may be directed to liberalstudies@gc.cuny.edu.

Photo Credits:
The images on this page are visualizations of cultural data created by Prof. Lev Manovich (The Graduate Center, CUNY), his students and the members of Software Studies Initiative (softwarestudies.com).