Science as a Web Service

Although my roots before joining Microsoft were in supercomputing, I believe that “extreme computing” and adding gigaflops (billions of floating-point operations per second) are no longer the optimal solutions to most scientific and technical problems. Today, scientists and engineers can buy or build 10-gigaflop desktop computers for around $5,000, and within the next several years, we will see similar supercomputing power at the chip level.

Instead, the next breakthroughs in science and engineering will come from harnessing the power of software and data – for example, using low-cost sensors to collect terabytes of real-world data and using data management tools to understand it.

Of course, combining computer models and real-world data presents new challenges, particularly in learning how to store, search, analyze, visualize, publish, and record the provenance of that data and the resulting conclusions. I believe the software industry can play a key role in developing tools that automate these data management tasks.

Such tools are beginning to appear. Inexpensive databases that allow precious data to be stored in a structured format are readily available but are significantly underused by the scientific community. Another important software advancement is XML (the eXtensible Markup Language). XML allows sensors, services, and systems to easily exchange data. Data formatted with XML is easier to search, and because metadata is an integral part of XML, it allows the provenance of the data to be recorded.

XML is also one of the enabling technologies for grid computing and Web services, which will revolutionize the scientific community in the coming decade by enabling the free exchange of information across distributed systems. Remote computation will be directly accessible from any desktop, and sensors and instruments will have their own Internet addresses.

The immediate challenge for the scientific and engineering community is to take advantage of available data management and data analysis tools. The larger and longer-term challenge is for the leaders in academic research to leverage software and Web services technologies to standardize the way they present and track their data.

Craig Mundie is Microsoft’s chief technology officer for advanced strategies and policy.