SIG DSA - Data Science and Analytics for Decision Support

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Paper Type

ERF

Paper Number

1283

Description

Government-produced data are consumed by thousands of scientists, researchers, industries, and students around the world daily, but are often difficult to locate because they are collected and stored in a duplicative state at varying levels of quality, inhibiting their usefulness for data science investigations and analysis. To address these challenges, the United States Department of the Interior bureaus have been implementing FAIR Data Principles into their data sharing strategies since 2016. Differing interpretations of the FAIR Data Principles are leading to data that are not documented uniformly and are not properly integrated for reuse. In order to establish a FAIR baseline, analysis of select datasets is being performed with peer-reviewed FAIR assessment tools. Delphi panels are being conducted with DOI Chief Data Officers and DOI Federal data consumers to gain insights as to how to affordably deliver this data according to the FAIR Data Principles.

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Aug 10th, 12:00 AM

U.S. Department of the Interior: Sharing FAIR Data Fairly

Government-produced data are consumed by thousands of scientists, researchers, industries, and students around the world daily, but are often difficult to locate because they are collected and stored in a duplicative state at varying levels of quality, inhibiting their usefulness for data science investigations and analysis. To address these challenges, the United States Department of the Interior bureaus have been implementing FAIR Data Principles into their data sharing strategies since 2016. Differing interpretations of the FAIR Data Principles are leading to data that are not documented uniformly and are not properly integrated for reuse. In order to establish a FAIR baseline, analysis of select datasets is being performed with peer-reviewed FAIR assessment tools. Delphi panels are being conducted with DOI Chief Data Officers and DOI Federal data consumers to gain insights as to how to affordably deliver this data according to the FAIR Data Principles.

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