Richard A. Ikeda

ORCID iD
https://orcid.org/0000-0003-4015-5528
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NIH Office of Research Information Systems

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Richard A. Ikeda (2014-07-22)

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Scopus Author ID: 7201505897

Sources:
Scopus - Elsevier (2013-06-13)

Biography

As data driven decision making has become an important tool and process for NIH, senior NIH management determined that data and data analysis capabilities required a more focused management organization. To address these needs, the Office of Research Information Systems was reorganized in July 2017. As Director of the Office of Research Information Systems (ORIS), I remain the Program Manager of RCDC and the supervisor for DDQ, but I have added supervisory duties for the Office of Data Analysis Tools and Systems (DATA Systems), and the Statistical Analysis and Reporting Branch (SARB). The RCDC Program implements an automated text and data mining process designed to report the annual amount of NIH funding in each of ~340 reportable categories of disease, condition, or research areas (http://report.nih.gov/rcdc/). DATA Systems (https://grants.nih.gov/aboutoer/oer_offices/odats.htm) develops and maintains databases, reports, and analysis tools for both the public as well as NIH staff. The most prominent of DATA Systems tools is the public Research Portfolio Online Reporting Tools (RePORT- https://report.nih.gov/index.aspx). SARB (https://grants.nih.gov/aboutoer/oer_offices/subopac_sarb.htm) is the reporting office for the NIH Office of Extramural Research and provides custom data analyses, and reports on NIH's research investments to support strategic decision-making and policy development. Finally, the DDQ (https://grants.nih.gov/aboutoer/oer_offices/suboris_ddq.htm) is responsible for maintaining the data quality of the 200 terabytes of scientific and administrative data that NIH has collected from its applications and grants from 1970 to the present. Current projects include improving RCDC categorization through the use of advanced Natural Language Process and semantic understanding. We are also investigating the application of Artificial Intelligence to help inform data driven decision making.
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