The document summarizes curriculum development at the Tetherless World Constellation focusing on data science and related fields. It discusses themes like data science, semantic science, knowledge provenance and ontology engineering. It notes the Constellation involves over 35 faculty, post-docs, grad and undergrad students across multiple departments. It also lists some application themes like government data, environmental informatics and health/life sciences. Finally, it advocates teaching data science methodology and principles over technology in an interdisciplinary way and emphasizing collaboration.

1. Curriculum development at the
Tetherless World Constellation – the
days after the “Day One” initiative
RDAP
March 22-23, 2012, New Orleans, LA
Peter Fox (RPI and WHOI) pfox@cs.rpi.edu
Tetherless World Constellation

2. tw.rpi.edu Future Web
•Web Science
•Policy
•Social Hendler
Xinformatics
•Data Science Fox
Themes
•Semantic eScience
•Data Frameworks
McGuinness
Semantic Foundations
•Knowledge Provenance
•Ontology Engineering Environments
•Inference, Trust
Multiple depts/schools/programs ~ 35 (Post-doc, Staff, Grad, Ugrad)

3. Govt. Data
•Open
•Linked Hendler/ Erickson
•Apps
Env. Informatics
Application •Ecosystems Fox
Themes •Sea Ice
•Ocean imagery
•Carbon
McGuinness/Luciano
Platforms:
Bio-nano tech center Health Care/ Life Sciences
•Population Science
Exp. Media and Perf. Arts Ctr. •Translational Med
Comp. Ctr. Nano. Innov. •Health Records
Data Intensive

4. Also at RPI
• Data Science Research Center and Data
Science Education Center
• http://www.rpi.edu/about/inside/issue/v4n17/data
– Over 35 research faculty, 5 post-docs, ? grad
students
• Data is one of Rensselaer Plans’ five thrusts
• Other key faculty
– Fran Berman (VPR)
– Jim Myers (Director CCNI)

5. Context
http://tw.rpi.edu/web/Courses
Experience
Data Information Knowledge
Creation Presentation Integration
Gathering Organization Conversation
Data Science Xinformatics Semantic eScience
5
Web Science

6. Curriculum
• Web Science and IT – undergrad, and MSc.
and PhD. (with science concentrations)
• Environmental Science with Geoinformatics
concentration
• Bio, geo, chem, astro, materials - informatics
• GIS for Science
• Master of Science – Data Science (pending)
• Multi-disciplinary science program (2012) PhD
in Data and Web Science

7. Dayz after…
• Science and interdisciplinary from the start!
– Not a question of: do we train scientists to be
technical/data people, or do we train technical
people to learn the science
– It’s a skill/ course level approach that is needed
• We must teach methodology and principles
over technology *
• Data science must be a skill, and natural like
using instruments, writing/using codes
• Team/ collaboration aspects are key **
• Foundations and theory must be taught ***

8. Modern informatics enables a new
scale-free framework approach