Digital Research Data Sharing and Management

摘要

Progress in science and engineering depends on the collection of data through observation, experimentation, and computation. A core expectation of the scientific method is the documentation and sharing of results, underlying data, and methodologies. This process enables other researchers to reproduce experiments and studies, verify and validate results, and build upon previous work to produce further scientific advances. The increasing ease with which research data can be gathered, processed, analyzed, and disseminated digitally has greatly expanded the scale, scope, and complexity of science and engineering data collections. Increased National Science Foundation (NSF) funding of data-intensive projects, which are often, but not exclusively, large-scale, collaborative efforts, has highlighted the need for improved data policies to maximize the use and value of digital research data. Enabling access to digital research data helps promote broad participation at all levels of scientific and engineering research and education. Digital research data have proliferated due to advances in information and computational technologies that have made gathering and processing data from large-scale, collaborative projects easier. In this report digital research data refers to all data generated in a digital format, analog data that have been subsequently digitized, and digital metadata that may be associated with digital research data, as a result of research funded by NSF.