Our Pedagogy

The task of education is to learn to interpret the world, and the data revolution of the last ten years rests on new approaches to computer algorithms for automating interpretation. We teach our students that this isn’t magic, and that students from all backgrounds and majors can learn how to use these new approaches to make a better world.

MEANING

Instead of memorizing the rules of proper thinking, students learn to see meaningful patterns emerge from out of the noise. Experts are people who know how to use the tools to interpret the world.

MENTORS

Faculty - like Mentor himself in Homer's Odyssey - point to what is meaningful in the world, and lay out the paths students must decide between. We demand a lot of thought and time because the projects matter.

STUDENTS

Run the show - as a group, and with mentors from the faculty and community. Students learn how to use the tools we make available, and how to visualize projects in terms of data, but the direction is their choice.

Projects

Courses

CCS 2350 – 19378 Perspectives Cultural Studies: Big Data in Social Science

Fall 2016/Alex Bentley, Peggy Lindner and Dan Price

The availability of big data is dramatically changing how culture is analyzed in business and computational social sciences. Unfortunately, big-data “nowcasting” and social analysis often act like a “black-box” with data from yesterday in, and predicted data for tomorrow out. This class is about what we can do to more actively grapple with big data, combining established theory with new computational tools for extracting meaning from social data. The class will emphasize hands on projects, balanced with articles exploring the theory and practice of cultural analysis using quantitative and computational methods. Students are not expected to already know theories of culture or how to code, but to be open to learning in a collaborative environment.

Data Analytics and Health (Hon 4198)

Fall 2015/Giulia Toti

Practical introduction to new techniques in health epidemiology, comparing machine learning and data mining approaches to traditional statistical methods. Students will use R for their projects.
Students should have some familiarity with statistics.

Philosophy Beyond Production (1): Pollution and Policy

Spring 2015/Dan Price

Humanities courses often talk about how meaning is produced in a work of art, and social science courses teach us about how different cultures produce meaning in different ways. But what do we mean by “producing meaning”? The model is industrial and commercial and has begun to seem quaint in light of modern technology and the new economy. In this course we will use the concepts of a post-industrial economy – data mining, social networks, crowd-sourcing and open data – to understand how meaning occurs in post-industrial culture. We have a very active example (air pollution, regulations, and individual health), and will look at the philosophyof meaning-making in/as culture and work toward a better post-industrial understanding. Readings will begin with important older texts from critical literary and social studies – Foucault, Derrida, Latour and Butler – but quickly move into recent suggestions for a new idea of culture, with a new vocabulary about what matters in a world of data flows and emergent forms.

Open Data: Tools for a New Age

Spring 2015/Peggy Lindner

Conceptual and practical overview for new data analytics tools used in health, environment, business and science. We will learn how to visualize multidimensional data, compare different types of data, and use different types of spatial algorithms for decisions and recommendations across affinity groups. We will be using examples from environmental and social problems facing the city, and expect everyone to get their hands dirty with some light programming.

Team

Dr. Daniel Price

Research Assistant Professor

Dan is a native Houstonian who graduated with a B.A. from Rice in 1987, then spent time living abroad until returning to the U.S. His writing is concerned with the intersection of social, political and aesthetic thought in French and German thinkers and includes Touching Difficulty: Sacred Form from Plato to Derrida (Davies Publishers, 2011). He has taught in various capacities at UH since 2000, but has been increasingly devoted to funded interdisciplinary research projects in the digital humanities and air pollution.

Dr. Peggy Lindner

Research Assistant Professor

Born in East Germany, Peggy has a keen appreciation for the importance of making data free and accessible to everyone. Her training in High Performance Computing has infused all the projects with higher expectations for quality and stability and her expertise in data representation has made it possible to think about larger and more integrated data projects. In addition to teaching with DASH, she is the liason for digital humanities with the Center for Advanced Computing and Data Sciences (CACDS) here at UH.

Our Students

Carlson Stephen

CIS

Fatemeh Mirghassemi

Biology

Giulia Toti

PhD in Computer Science

Christopher Holley

Computer Science

Trevor Self

Economics

Abel Chacko

Health (Public Health Track)

Matthew Joseph

Biotechnology

Maxwell (Max) Ciotti

Computer Science

Sumaiya Asif

Computer Science

Michelle Tran

Computer Science

Carol Upchurch

Bioengineering

Contact

Address

212 M.D. Anderson Library,
Houston, TX 77004
dash@uh.edu
+1 (713) 743-4581