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Long-lived digital data collections are those that meet the following definitions.


Long-lived digital data collections are increasingly crucial to research and education in science and engineering. A number of well-known factors have contributed to this phenomenon. Powerful and increasingly affordable sensors, processors, and automated equipment (for example, digital remote sensing, gene sequencers, micro arrays, and automated physical behavior simulations) have produced a proliferation of data in digital form. Reductions in storage costs have made it cost-effective to create and maintain large databases. And the existence of the Internet and other computer-based communications have made it easier to share data. As a result, researchers in such fields as genomics, climate modeling, and demographic studies increasingly conduct research using data originally generated by others and frequently access these data in large public databases found on the Internet.

Data collections provide more than an increase in the efficiency and accuracy of research; they enable new research opportunities. They do this in two quite different ways. First, digital data collections provide a foundation for using automated analytical tools, giving researchers the ability to develop descriptions of phenomena that could not be created in any other way. While this is true for science that studies natural physical processes, it is particularly enabling for the social scientists.

Second, digital data collections give researchers access to data from a variety of sources and enable them to integrate data across fields. The relative ease of sharing digital data — compared to data recorded on paper — allows researchers, students, and educators from different disciplines, institutions, and geographical locations to contribute to the research enterprise. It democratizes research by providing the opportunity for all who have access to these data collections to make a contribution.