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ISPRS Int. J. Geo-Inf. 2019, 8(2), 54; https://doi.org/10.3390/ijgi8020054

An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics

Geospatial Technologies Research Group (GEOTEC), Universitat Jaume I, Av. Vicente Sos Baynat s/n, 12071 Castellón de la Plana, Spain
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Received: 30 November 2018 / Revised: 11 January 2019 / Accepted: 22 January 2019 / Published: 26 January 2019
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Abstract

In large-scale context-aware applications, a central design concern is capturing, managing and acting upon location and context data. The ability to understand the collected data and define meaningful contextual events, based on one or more incoming (contextual) data streams, both for a single and multiple users, is hereby critical for applications to exhibit location- and context-aware behaviour. In this article, we describe a context-aware, data-intensive metrics platform —focusing primarily on its geospatial support—that allows exactly this: to define and execute metrics, which capture meaningful spatio-temporal and contextual events relevant for the application realm. The platform (1) supports metrics definition and execution; (2) provides facilities for real-time, in-application actions upon metrics execution results; (3) allows post-hoc analysis and visualisation of collected data and results. It hereby offers contextual and geospatial data management and analytics as a service, and allow context-aware application developers to focus on their core application logic. We explain the core platform and its ecosystem of supporting applications and tools, elaborate the most important conceptual features, and discuss implementation realised through a distributed, micro-service based cloud architecture. Finally, we highlight possible application fields, and present a real-world case study in the realm of psychological health. View Full-Text
Keywords: metrics; spatio-temporal analytics platform; context-aware systems; location-aware applications metrics; spatio-temporal analytics platform; context-aware systems; location-aware applications
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Rodríguez-Pupo, L.E.; Granell, C.; Casteleyn, S. An Analytics Platform for Integrating and Computing Spatio-Temporal Metrics. ISPRS Int. J. Geo-Inf. 2019, 8, 54.

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