Geospatial Data Management Research: Progress and Future Directions
Without geospatial data management, today’s 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...
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-02-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/9/2/95 |
| _version_ | 1818310489401196544 |
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| author | Martin Breunig Patrick Erik Bradley Markus Jahn Paul Kuper Nima Mazroob Norbert Rösch Mulhim Al-Doori Emmanuel Stefanakis Mojgan Jadidi |
| author_facet | Martin Breunig Patrick Erik Bradley Markus Jahn Paul Kuper Nima Mazroob Norbert Rösch Mulhim Al-Doori Emmanuel Stefanakis Mojgan Jadidi |
| author_sort | Martin Breunig |
| collection | DOAJ |
| description | Without geospatial data management, today’s 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 “in-situ” 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’ 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. |
| first_indexed | 2024-12-13T07:46:52Z |
| format | Article |
| id | doaj.art-84d95bf7e1764b07a6f9e344bef97600 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-12-13T07:46:52Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-84d95bf7e1764b07a6f9e344bef976002022-12-21T23:54:48ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-02-01929510.3390/ijgi9020095ijgi9020095Geospatial Data Management Research: Progress and Future DirectionsMartin Breunig0Patrick Erik Bradley1Markus Jahn2Paul Kuper3Nima Mazroob4Norbert Rösch5Mulhim Al-Doori6Emmanuel Stefanakis7Mojgan Jadidi8Geodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, GermanyGeodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, GermanyGeodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, GermanyGeodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, GermanyGeodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, GermanyGeodetic Institute, Karlsruhe Institute of Technology, 76128 Karlsruhe, GermanyCollege of Information Technology, University of Fujairah, P.O. Box 1207 Fujairah, UAEDepartment of Geomatics Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, CanadaDepartment of Earth & Space Science & Engineering, Lassonde School of Engineering, York University, Toronto, ON M3J 1P3, CanadaWithout geospatial data management, today’s 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 “in-situ” 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’ 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.https://www.mdpi.com/2220-9964/9/2/95geo-data managementbig geospatial data<i>nd</i> geo-databasetopologygraph databaseartificial intelligence |
| spellingShingle | Martin Breunig Patrick Erik Bradley Markus Jahn Paul Kuper Nima Mazroob Norbert Rösch Mulhim Al-Doori Emmanuel Stefanakis Mojgan Jadidi Geospatial Data Management Research: Progress and Future Directions ISPRS International Journal of Geo-Information geo-data management big geospatial data <i>nd</i> geo-database topology graph database artificial intelligence |
| title | Geospatial Data Management Research: Progress and Future Directions |
| title_full | Geospatial Data Management Research: Progress and Future Directions |
| title_fullStr | Geospatial Data Management Research: Progress and Future Directions |
| title_full_unstemmed | Geospatial Data Management Research: Progress and Future Directions |
| title_short | Geospatial Data Management Research: Progress and Future Directions |
| title_sort | geospatial data management research progress and future directions |
| topic | geo-data management big geospatial data <i>nd</i> geo-database topology graph database artificial intelligence |
| url | https://www.mdpi.com/2220-9964/9/2/95 |
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