@article {906,
	title = {The KnowWhereGraph Ontology},
	year = {2023},
	author = {Cogan Shimizu and Shirly Stephen and Kitty Currier and Pascal Hitzler and Rui Zhu and Krzysztof Janowicz and Mark Schildhauer and Mohammad Saeid Mahdavinejad and Abhilekha Dalal and Adrita Barua and Ling Cai and Gengchen Mai and Zhangyu Wang and Yuanyuan Tian and Sanaz Saki Norouzi and Zilong Liu and Meilin Shi and Colby K. Fisher}
}
@conference {916,
	title = {The KnowWhereGraph Ontology: A Showcase},
	year = {2023},
	author = {Cogan Shimizu and Shirly Stephen and Rui Zhu and Kitty Currier and Mark Schildhauer and Dean Rehberger and Pascal Hitzler and Krzysztof Janowicz and Colby K. Fisher and Mohammad Saeid Mahdavinejad and Antrea Christou and Adrita Barua and Abhilekha Dalal and Sanaz Saki Norouzi and Zilong Liu and Meilin Shi and Ling Cai and Gengchen Mai and Zhangyu Wang and Yuanyuan Tian}
}
@article {894,
	title = {Diverse data! Diverse schemata?},
	journal = {Semantic Web},
	volume = {13},
	year = {2022},
	pages = {1{\textendash}3},
	doi = {10.3233/SW-210453},
	url = {https://doi.org/10.3233/SW-210453},
	author = {Krzysztof Janowicz and Cogan Shimizu and Pascal Hitzler and Gengchen Mai and Shirly Stephen and Rui Zhu and Ling Cai and Lu Zhou and Mark Schildhauer and Zilong Liu and Zhangyu Wang and Meilin Shi}
}
@article {887,
	title = {Know, Know Where, KnowWhereGraph: A Densely Connected, Cross-Domain Knowledge Graph and Geo-Enrichment Service Stack for Applications in Environmental Intelligence},
	journal = {AI Magazine},
	year = {2022},
	author = {Krzysztof Janowicz and Pascal Hitzler and Wenwen Li and Dean Rehberger and Mark Schildhauer and Rui Zhu and Cogan Shimizu and Colby K. Fisher and Ling Cai and Gengchen Mai and Joseph Zalewski and Lu Zhou and Shirly Stephen and Seila Gonzalez and Bryce Mecum and Anna Lopez Carr and Andrew Schroeder and Dave Smith and Dawn Wright and Sizhe Wang and Yuanyuan Tian and Zilong Liu and Meilin Shi and Anthony D{\textquoteright}Onofrio and Zhining Gu}
}
@conference {869,
	title = {Environmental Observations in Knowledge Graphs},
	booktitle = {DaMaLOS 2021 @ ISWC},
	year = {2021},
	abstract = {<p>The notion of Linked Open Science rests on the assumption that Linked Data principles contribute to science and scientific data management in several distinct ways (e.g., by adding rich semantics to improve retrieval and reuse of data). This begs the question of the right level of granularity for such semantic enrichment. On the one extreme of the spectrum, one may provide semantic annotations on the level of entire datasets to improve retrieval while leaving the actual data untouched. On the other end, one may semantically describe every single datum, such as a particular observation leading to data that supports reasoning, automated conflation, and so on, while, at the same time, dramatically increasing the size of data, including redundancy. This paper reports on our experience in modeling heterogeneous environmental data using a semantically-enabled observation framework, namely the SOSA ontology and its extensions to handle observation collections. We discuss different means of using these observation collections and compare their pros and cons in terms of data size and ease of querying.\&nbsp;</p>
},
	author = {Rui Zhu and Shirly Stephen Ambrose and Lu Zhou and Cogan Shimizu and Ling Cai and Gengchen Mai and Krzysztof Janowicz and Pascal Hitzler and Mark Schildhauer}
}
@conference {899,
	title = {SOSA-SHACL: Shapes Constraint for the Sensor, Observation, Sample, and Actuator Ontology},
	booktitle = {The 10th International Joint Conference on Knowledge Graphs, IJCKG 2021, December 6-8, 2021, Virtual Event, Thailand},
	year = {2021},
	publisher = {ACM},
	organization = {ACM},
	author = {Rui Zhu and Cogan Shimizu and Shirly Stephen and Lu Zhou and Ling Cai and Gengchen Mai and Krzysztof Janowicz and Mark Schildhauer and Pascal Hitzler}
}
