2026-09-10T09:44:28Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:27558 2026-09-10T05:38:42Z ddc:004 open_access

An Operator Framework for Real-Time Analytics of Streamed Fields Paul, JJ Nittel, Silvia Geostreaming Spatiotemporal phenomena Fields Data streams Real-time analytics Operators Algebra Continuous geospatial phenomena such as air quality, temperature, soil moisture, or noise evolve smoothly over space while potentially changing rapidly over time. They are increasingly observed through dense, real-time measurement streams from geosensor networks, mobile platforms, and live sensor infrastructures. While data stream engines provide low-latency processing over unbounded streams, they lack higher-level abstractions for spatially continuous phenomena. As a result, real-time field analysis is often implemented via ad-hoc pipelines that combine GIS tools, stream processing, and application-specific logic. In this paper we propose an analytical operator framework for streamed scalar fields. We derive a minimal, composable operator set building on principles of compact operator sets and dimensional reasoning over space, time, and theme. We demonstrate how analytics for streamed continuous phenomena are expressed through primitive operator compositions. The resulting framework provides a systematic basis for describing and implementing extensible stream-based, real-time field analytics. Schloss Dagstuhl – Leibniz-Zentrum für Informatik JJ Paul and Silvia Nittel 2026 Is Part Of LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.COSIT.2026.14 urn:nbn:de:0030-drops-275584 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.14 eng https://creativecommons.org/licenses/by/4.0/legalcode