EMERGENT SCIENCE: ACCELERATING THE SCIENTIFIC PROCESS VIA SIMPLE COLLABORATIVE INTERACTIONS

We are already seeing the impact of social collaboration in our daily lives. A simple example is our use of online reviews posted by other consumers in evaluating whether to buy a particular product. This social phenomenon has been well documented and is referred to by many names such as Smart Mobs, Wisdom of Crowds, Wikinomics, Crowd Sourcing, We-Think and Swarm Collaboration. Similar social collaborations during the science process can lead to “emergent science”. We define "emergent science" as way complex science problems can be solved and new research directions forged out of a multiplicity of relatively simple collaborative interactions.

Recent advances in Cyberinfrastructure have democratized the use of computational and data resources. These resources, coupled with new social networking and collaboration technologies, present an unprecedented opportunity to impact the science process. These technological advances can move the science process from “circumspect science” -- where scientists publish primarily when a project is complete, publish only the final results, seldom publish things that did not work, and communicate results with each other using paper technology -- to “open science” -- where scientists can share and publish every element in their research, from the data used as input, workflows used to analyze these data sets, possibly failed experiments, and the final results.

This presentation will look at existing barriers that prevent social collaboration within the science process. Some of these barriers are technical, such as lack of science collaboration platforms, and the others are social. In addition, the authors will present two examples of collaborative platforms fostering “emergent science”. The first is a web-based portal where scientists can create, execute and share complex scientific data mining workflows with one another. Such shared workflows allow for reproducible analysis results. The second is an online journal with the goal of documenting interesting Earth Science phenomena using peer-reviewed micro-articles. The goal of this journal is to provide the science community a platform to catalog interesting phenomena seen in publicly available datasets. These micro-articles can then be used by both the researchers and by the education community.