Technology Assessment of High Capacity Data Storage Systems: Can We Avoid a Data Survivability Crisis?
This technology assessment of long-term high capacity data storage systems identifies an emerging crisis of severe proportions related to preserving important historical data in science, healthcare, manufacturing, finance and other fields. For the last 50 years, the information revolution, which has engulfed all major institutions of modem society, centered itself on data-their collection, storage, retrieval, transmission, analysis and presentation. The transformation of long term historical data records into information concepts, according to Drucker, is the next stage in this revolution towards building the new information based scientific and business foundations. For this to occur, data survivability, reliability and evolvability of long term storage media and systems pose formidable technological challenges. Unlike the Y2K problem, where the clock is ticking and a crisis is set to go off at a specific time, large capacity data storage repositories face a crisis similar to the social security system in that the seriousness of the problem emerges after a decade or two. The essence of the storage crisis is as follows: since it could take a decade to migrate a peta-byte of data to a new media for preservation, and the life expectancy of the storage media itself is only a decade, then it may not be possible to complete the transfer before an irrecoverable data loss occurs. Over the last two decades, a number of anecdotal crises have occurred where vital scientific and business data were lost or would have been lost if not for major expenditures of resources and funds to save this data, much like what is happening today to solve the Y2K problem. A pr-ime example was the joint NASA/NSF/NOAA effort to rescue eight years worth of TOVS/AVHRR data from an obsolete system, which otherwise would have not resulted in the valuable 20-year long satellite record of global warming. Current storage systems solutions to long-term data survivability rest on scalable architectures having parallel paths for data migration.