Advancing Commercialization of Digital Products from Federal Laboratories (2021) / Chapter Skim
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Appendix C: Definitions of Digital Products
Appendix C: Definitions of Digital Products
Pages 139-142
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From page 139... ...
When stored in a form amenable to external analysis, raw and/or preprocessed data may be distributed outside of the lab to ensure reproducibility of scientific results and allow external researchers to advance new use cases and improve data processing pipelines. Datasets and Databases While raw data may sometimes be valuable to researchers outside of the federal laboratories, it is often more beneficial for the labs to release datasets: structured collections of data pertaining to a particular endeavor or measurement.
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From page 140... ...
Code Snippets Code snippets are small subsets of software with lightweight documentation intended to be reused. They allow a programmer to use a standard implementation of a specific statistical technique, reducing error and increasing replicability.
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From page 141... ...
AI/ML employs highly flexible models that can identify complex or unexpected patterns in data, thereby fueling increased predictive performance, instead of prescribing a specific mathematical description of a phenomenon, such as is done in traditional statistical modeling. Deep learning, one popular subtype of AI/ML, uses neural networks to "understand" very complex data, including images, text, speech, and videos.
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From page 142... ...
Cloud computing allows individual users to remotely access the computational power of many computers at once, which can be essential to harness and analyze the vast datasets, complex software, and powerful statistical models routinely produced by federal labs and the private sector. Computing power may be provided by a cluster of computers at an individual lab or a centralized scientific computing facility (e.g., the National Energy Research Supercomputing Center)
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