@article {qin_toward_2022,
	title = {Toward Democratizing Access to Facilities Data: A Framework for Intelligent Data Discovery and Delivery},
	journal = {Computing in Science \& Engineering},
	volume = {24},
	number = {3},
	year = {2022},
	note = {Conference Name: Computing in Science \& Engineering},
	month = {may},
	pages = {52{\textendash}60},
	abstract = {Data collected by large-scale instruments, observatories, and sensor networks (i.e., science facilities) are key enablers of scientific discoveries in many disciplines. However, ensuring that these data can be accessed, integrated, and analyzed in a democratized and timely manner remains a challenge. In this article, we explore how state-of-the-art techniques for data discovery and access can be adapted to facilitate data and develop a conceptual framework for intelligent data access and discovery.},
	keywords = {Data collection, Data models, Data transfer, Distributed databases, Observatories},
	issn = {1558-366X},
	doi = {10.1109/MCSE.2022.3179408},
	author = {Qin, Yubo and Rodero, Ivan and Parashar, Manish}
}
