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Open AccessArticle

An Ontology-driven Cyberinfrastructure for Intelligent Spatiotemporal Question Answering and Open Knowledge Discovery

1
School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA
2
Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(11), 496; https://doi.org/10.3390/ijgi8110496
Received: 10 October 2019 / Revised: 25 October 2019 / Accepted: 31 October 2019 / Published: 3 November 2019
The proliferation of geospatial data from diverse sources, such as Earth observation satellites, social media, and unmanned aerial vehicles (UAVs), has created a pressing demand for cross-platform data integration, interoperation, and intelligent data analysis. To address this big data challenge, this paper reports our research in developing a rule-based, semantic-enabled service chain model to support intelligent question answering for leveraging the abundant data and processing resources available online. Four key techniques were developed to achieve this goal: (1) A spatial and temporal reasoner resolves the spatial and temporal information in a given scientific question and enables place-name disambiguation based on support from a gazetteer; (2) a spatial operation ontology categorizes important spatial analysis operations, data types, and data themes, which will be used in automated chain generation; (3) a language-independent chaining rule defines the template for input, spatial operation, and output as well as rules for embedding multiple spatial operations for solving a complex problem; and (4) a recursive algorithm facilitates the generation of executive workflow metadata according to the chaining rules. We implement this service chain model in a cyberinfrastructure for online and reproducible spatial analysis and question answering. Moving the problem-solving environment from a desktop-based environment onto a geospatial cyberinfrastructure (GeoCI) offers better support to collaborative spatial decision-making and ensures science replicability. We expect this work to contribute significantly to the advancement of a reproducible spatial data science and to building the next-generation open knowledge network.
Keywords: spatial decision support; scientific workflow; provenance; reproducibility; open knowledge discovery; cyberinfrastructure; knowledge graphs spatial decision support; scientific workflow; provenance; reproducibility; open knowledge discovery; cyberinfrastructure; knowledge graphs
MDPI and ACS Style

Li, W.; Song, M.; Tian, Y. An Ontology-driven Cyberinfrastructure for Intelligent Spatiotemporal Question Answering and Open Knowledge Discovery. ISPRS Int. J. Geo-Inf. 2019, 8, 496.

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