What does Web 2.0 mean for e-science?
First, let me define a few terms up front. By “Web 2.0,” I mean the evolution of the Web from relatively static pages, to highly responsive, dynamic online applications and the resulting changes in Web culture. There is some disagreement about why Web 2.0 has arrived now, but one thing many folks point to is the maturity of technologies for making web sites act more like regular applications. AJAX is certainly a player here, along with DHTML and sophisticated GUI toolkits such as Yahoo’s YUI. The result is a more interactive, collaborative, and dynamic Web (as evidenced by the recent extreme success of social networking sites). While I do not argue that technological advances are the only players leading to the advent of Web 2.0, I doubt many will argue that it is not a fundamental part.
By “e-science,” I mean networks of scientists in a community (or even cross-community) using highly advanced computing techniques (such a Grid computing) to accomplish the tasks of scientific research. An overwhelmingly large number of scientific communities have leveraged recent advances in network speed, processor speed, data storage, etc. to help them accomplish their research. For a few examples, see some of the following sites:
- US National Virtual Observatory
- Grid Physics Network
- Network for Earthquake Engineering Simulation
- Earth System Grid
The question I want to consider is: “What does Web 2.0 mean for e-science?” My hypothesis is that there is a nice marriage between the two, although most e-science communities have yet to embrace Web 2.0. My argument is simply that science by nature is collaborative and therefore we should be building tools that facilitate collaboration among scientists.
As a first step in this direction, we have seen many scientific communities that have made very large repositories of datasets available online. Many of these can be freely downloaded by anyone in the world for their own personal exploration (or at least to a very large audience of registered users). Of the sites listed above, the only one I have personal experience with is the Earth System Grid. From ESG you can access the datasets used by the Intergovernmental Panel on Climate Change (IPCC) for their latest assessment report.
Similar things are happening in other domains. For example, you no longer have to have a telescope to take a peek at points in the sky. The US Virtual Observatory DataScope application allows you to input a particular point or region and with a simple mouse click you are looking at the requested location!
While I admit that this trend toward more accessibility of data is a huge step forward, I think that applying the Web 2.0 philosophy to e-science may help to increase interactivity by moving some of the “science” that happens on individual machines out into online collaborative spaces. For example, consider this scenario presented to me by a colleague of mine working in the climate modeling domain. He pointed out that many analysts download datasets to study the effects of El Nino. Once a dataset is retrieved (from a site like ESG) it must undergo a series of processing steps to isolate the correct region of the globe, the right time periods, and the right variables. What’s not surprising is that much of the same processing is repeated by every analyst that downloads the dataset. That’s because once you have the dataset locally, it has lost all connections with the site where you found it.
Now imagine a scenario where much of the processing has been moved onto the Web (perhaps by a set of Web Services for climate data?). When scientist B visits the site for her El Nino exploration, she finds that scientist A has already performed much of the needed post processing and she grabs that dataset instead of the original. She also notices some comments made by the scientist A that the El Nino phenomenon is best seen during a certain year. Finally, scientist A has posted some plots that scientist B compares with her own plots.
So, in conclusion it seems that Web 2.0 philosophy and e-science could be good friends. It may be a few years in the making, but when it happens science will benefit from a whole new level of interactivity and collaboration that was previously not possible.