1. e-Science What is this all about? DINO, January 10th, 2007
Chuck Humphrey
University of Alberta

2. e-Science: a definition
Computationally intense science employing grid-computing technology to analyze very large data collections.
based on a definition on the National e-Science Centre website at
e-Science in the UK is equivalent to cyberinfrastructure in the US

3. Computationally based laboratories
Science involves problem articulation (hypotheses) based on scientific theory and literature, instrumentation, measurement, data management, analyses and knowledge dissemination.
To the degree that all of these functions are conducted through computing technology, we see the emergence of the computationally based laboratory.

4. Computationally based laboratories
Place a computational laboratory on the Internet and you have a virtual laboratory and arguably, e-Science.
The US National Virtual Observatory is an example of this model.

5. Virtual laboratories
Virtual laboratories are environments on the Internet that provide access to grid computing power and large data collections.
These laboratories are one manifestation of e-Science. It is unclear what other kinds of organizational models will emerge out of cyberinfrastructure.

6. Post ARL-NSF Consultation, September 2006
Charles Humphrey, University of Alberta, October 2006
Observational
Experimental
Computational

7. Final report from the ARL-NSF consultation
Like the social sciences, matters dealing with access receive more attention than preservation.
In the end, preservation became recognized as “the long-term stewardship of data.”

8. Sciences vs. Social Sciences
Similarities
Primary focus is on access systems.
Metadata are essential to the design of these access systems.
Standards are critical to the design of these access systems.
Differences
Metadata in many of the sciences are produced from the instruments generating the data.
Data are collected through international collaborative initiatives.
Some sciences are becoming data-driven, such as astronomy.