{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T21:12:15Z","timestamp":1784322735881,"version":"3.55.0"},"reference-count":117,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2020,2,4]],"date-time":"2020-02-04T00:00:00Z","timestamp":1580774400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["BR 2128 \/18-1"],"award-info":[{"award-number":["BR 2128 \/18-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["FOR 1546-2"],"award-info":[{"award-number":["FOR 1546-2"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001655","name":"Deutscher Akademischer Austauschdienst","doi-asserted-by":"publisher","award":["DAAD 57390945"],"award-info":[{"award-number":["DAAD 57390945"]}],"id":[{"id":"10.13039\/501100001655","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Without geospatial data management, today\u2019s challenges in big data applications such as earth observation, geographic information system\/building information modeling (GIS\/BIM) integration, and 3D\/4D city planning cannot be solved. Furthermore, geospatial data management plays a connecting role between data acquisition, data modelling, data visualization, and data analysis. It enables the continuous availability of geospatial data and the replicability of geospatial data analysis. In the first part of this article, five milestones of geospatial data management research are presented that were achieved during the last decade. The first one reflects advancements in BIM\/GIS integration at data, process, and application levels. The second milestone presents theoretical progress by introducing topology as a key concept of geospatial data management. In the third milestone, 3D\/4D geospatial data management is described as a key concept for city modelling, including subsurface models. Progress in modelling and visualization of massive geospatial features on web platforms is the fourth milestone which includes discrete global grid systems as an alternative geospatial reference framework. The intensive use of geosensor data sources is the fifth milestone which opens the way to parallel data storage platforms supporting data analysis on geosensors. In the second part of this article, five future directions of geospatial data management research are presented that have the potential to become key research fields of geospatial data management in the next decade. Geo-data science will have the task to extract knowledge from unstructured and structured geospatial data and to bridge the gap between modern information technology concepts and the geo-related sciences. Topology is presented as a powerful and general concept to analyze GIS and BIM data structures and spatial relations that will be of great importance in emerging applications such as smart cities and digital twins. Data-streaming libraries and \u201cin-situ\u201d geo-computing on objects executed directly on the sensors will revolutionize geo-information science and bridge geo-computing with geospatial data management. Advanced geospatial data visualization on web platforms will enable the representation of dynamically changing geospatial features or moving objects\u2019 trajectories. Finally, geospatial data management will support big geospatial data analysis, and graph databases are expected to experience a revival on top of parallel and distributed data stores supporting big geospatial data analysis.<\/jats:p>","DOI":"10.3390\/ijgi9020095","type":"journal-article","created":{"date-parts":[[2020,2,5]],"date-time":"2020-02-05T03:18:48Z","timestamp":1580872728000},"page":"95","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":149,"title":["Geospatial Data Management Research: Progress and Future Directions"],"prefix":"10.3390","volume":"9","author":[{"given":"Martin","family":"Breunig","sequence":"first","affiliation":[{"name":"Geodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5595-490X","authenticated-orcid":false,"given":"Patrick Erik","family":"Bradley","sequence":"additional","affiliation":[{"name":"Geodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Markus","family":"Jahn","sequence":"additional","affiliation":[{"name":"Geodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Kuper","sequence":"additional","affiliation":[{"name":"Geodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nima","family":"Mazroob","sequence":"additional","affiliation":[{"name":"Geodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Norbert","family":"R\u00f6sch","sequence":"additional","affiliation":[{"name":"Geodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mulhim","family":"Al-Doori","sequence":"additional","affiliation":[{"name":"College of Information Technology, University of Fujairah, P.O. Box 1207 Fujairah, UAE"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emmanuel","family":"Stefanakis","sequence":"additional","affiliation":[{"name":"Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2692-6157","authenticated-orcid":false,"given":"Mojgan","family":"Jadidi","sequence":"additional","affiliation":[{"name":"Department of Earth &amp; Space Science &amp; Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,2,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Tan, Z., Yue, P., and Gong, J. (2017). An Array Database Approach for Earth Observation Data Management and Processing. ISPRS Int. J. 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