Abstract

To better understand how climate may change in the future, scientists look at how it has varied in the past, a field called paleoclimatology. Doing so requires the use of proxies such as the rings of trees or the chemical composition of ice cores to infer climate variability over thousands to millions of years. Given the importance of these datasets, it is crucial that scientists have the ability to efficiently locate, access, and integrate data. Paleoclimate studies often require the integration of hundreds of datasets that are stored in unstructured files, currently requiring scientists to spend a significant fraction of their time manually reformatting the data before they can work with it. The goal of this project is to use artificial intelligence to identify tables in files automatically so these tables can be used more easily in analyses. The end goal is to make more data available to scientists, to reduce the time scientists spend on data …

Date

January 1, 1970

Authors

Deborah Khider

Journal

NSF Award Number 2411267. Directorate for Computer and Information Science and Engineering

Volume

24

Issue

2411267

Pages

11267