ESIP_2019s_xm_poster.pdf (5.07 MB)
Download file

Towards a Machine-Readable Knowledge Base of Deep Time: Challenges, Current Progress, and Future Work

Download (5.07 MB)
posted on 2019-07-23, 20:27 authored by Xiaogang Ma, Chao Ma

In the open data environment, we need a Web-based and machine-readable knowledge base of deep time to automate data access and synthesis in executable workflows. This poster was presented in July 2019 at the Earth Science Information Partners (ESIP) Summer Meeting held in Tacoma, Washington.


NSF - Grant No. 1835717