TY - RPRT T1 - The KnowWhereGraph Ontology Y1 - 2023 A1 - Cogan Shimizu A1 - Shirly Stephen A1 - Kitty Currier A1 - Pascal Hitzler A1 - Rui Zhu A1 - Krzysztof Janowicz A1 - Mark Schildhauer A1 - Mohammad Saeid Mahdavinejad A1 - Abhilekha Dalal A1 - Adrita Barua A1 - Ling Cai A1 - Gengchen Mai A1 - Zhangyu Wang A1 - Yuanyuan Tian A1 - Sanaz Saki Norouzi A1 - Zilong Liu A1 - Meilin Shi A1 - Colby K. Fisher ER - TY - CONF T1 - The KnowWhereGraph Ontology: A Showcase Y1 - 2023 A1 - Cogan Shimizu A1 - Shirly Stephen A1 - Rui Zhu A1 - Kitty Currier A1 - Mark Schildhauer A1 - Dean Rehberger A1 - Pascal Hitzler A1 - Krzysztof Janowicz A1 - Colby K. Fisher A1 - Mohammad Saeid Mahdavinejad A1 - Antrea Christou A1 - Adrita Barua A1 - Abhilekha Dalal A1 - Sanaz Saki Norouzi A1 - Zilong Liu A1 - Meilin Shi A1 - Ling Cai A1 - Gengchen Mai A1 - Zhangyu Wang A1 - Yuanyuan Tian ER - TY - JOUR T1 - Diverse data! Diverse schemata? JF - Semantic Web Y1 - 2022 A1 - Krzysztof Janowicz A1 - Cogan Shimizu A1 - Pascal Hitzler A1 - Gengchen Mai A1 - Shirly Stephen A1 - Rui Zhu A1 - Ling Cai A1 - Lu Zhou A1 - Mark Schildhauer A1 - Zilong Liu A1 - Zhangyu Wang A1 - Meilin Shi VL - 13 UR - https://doi.org/10.3233/SW-210453 ER - TY - JOUR T1 - Know, Know Where, KnowWhereGraph: A Densely Connected, Cross-Domain Knowledge Graph and Geo-Enrichment Service Stack for Applications in Environmental Intelligence JF - AI Magazine Y1 - 2022 A1 - Krzysztof Janowicz A1 - Pascal Hitzler A1 - Wenwen Li A1 - Dean Rehberger A1 - Mark Schildhauer A1 - Rui Zhu A1 - Cogan Shimizu A1 - Colby K. Fisher A1 - Ling Cai A1 - Gengchen Mai A1 - Joseph Zalewski A1 - Lu Zhou A1 - Shirly Stephen A1 - Seila Gonzalez A1 - Bryce Mecum A1 - Anna Lopez Carr A1 - Andrew Schroeder A1 - Dave Smith A1 - Dawn Wright A1 - Sizhe Wang A1 - Yuanyuan Tian A1 - Zilong Liu A1 - Meilin Shi A1 - Anthony D’Onofrio A1 - Zhining Gu ER - TY - CONF T1 - Environmental Observations in Knowledge Graphs T2 - DaMaLOS 2021 @ ISWC Y1 - 2021 A1 - Rui Zhu A1 - Shirly Stephen Ambrose A1 - Lu Zhou A1 - Cogan Shimizu A1 - Ling Cai A1 - Gengchen Mai A1 - Krzysztof Janowicz A1 - Pascal Hitzler A1 - Mark Schildhauer AB -

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. 

JF - DaMaLOS 2021 @ ISWC ER - TY - CONF T1 - SOSA-SHACL: Shapes Constraint for the Sensor, Observation, Sample, and Actuator Ontology T2 - The 10th International Joint Conference on Knowledge Graphs, IJCKG 2021, December 6-8, 2021, Virtual Event, Thailand Y1 - 2021 A1 - Rui Zhu A1 - Cogan Shimizu A1 - Shirly Stephen A1 - Lu Zhou A1 - Ling Cai A1 - Gengchen Mai A1 - Krzysztof Janowicz A1 - Mark Schildhauer A1 - Pascal Hitzler JF - The 10th International Joint Conference on Knowledge Graphs, IJCKG 2021, December 6-8, 2021, Virtual Event, Thailand PB - ACM ER -