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--- teaching:mfe:is [2019/07/09 17:56]
msakr
+++ teaching:mfe:is [2020/09/29 17:03]
mahmsakr [Data modeling of spatiotemporal regions]
@@ Line 49: / Line 49: @@
 **Interested?** Contact :  [[svsummer@ulb.ac.be|Stijn Vansummeren]]
-**Status**: available
+**Status**: taken
 ===== Graph Indexing for Fast Subgraph Isomorphism Testing =====
@@ Line 96: / Line 96: @@
   * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]]
-**Status**: available
+**Status**: taken
-=====Python driver for Trajectories=====
-Similar to the previous topic, yet for Python.
-**Interested?**
-  * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]]
-**Status**: available
 =====Mobility data exchange standards=====
@@ Line 134: / Line 127: @@
 **Status**: available
-=====Data modeling of spatiotemporal regions=====
-In moving object databases, a lot of attention has been given to moving point objects. Many data model have been proposed for this. Less attention has been given to moving region objects. Imagine a herd of animals that moves together in the wild. At any time instant, this herd can be represented using a spatial region, e.g., their convex hull. Over time, this regions changes place and extent. A spatiotemporal region is an abstract data type that can represent this temporal evolution of the region.
-This thesis is about proposing a data model for spatiotemporal regions, and implementing it in MobilityDB. This includes surveying the literature on moving object databases, and specifically on spatiotemporal reigons, proposing a discrete data model, implementing it, and implementing the basic data base functions and operations to make use of it.
-**Interested?**
-  * Contact : [[ezimanyi@ulb.ac.be|Esteban Zimanyi]]
-**Status**: not available
 =====Scalable Map-Matching=====
-GPS trajectories originate in the form of a series of absolute lat/lon coordinates. Map-matching is the method of locating the GPS observations onto a road network. It trasforms the lat/lon pairs into pairs of a road identfier and a fraction representing the relative position on the road. This preprocessing is essential to trajectory data analysis. It contributes to cleaning the data, as well as preparing it for network-related analysis. There are two modes of map-matching: (1) offline, where al the observations of the trajectory exist before starting hte map-matching, and (2) online, where the observation arrive to the map-matcher one by one in a streaming fashion. Map-matching is known to be an expensive pre-processing, in terms of processing time. The gorwing amount of trajectory data (e.g., autonmous cars) call for map-matching methods that can scale-out. This thesis is about proposing such a solution. It shall survey the existing Algorithms, benchmark them, and propose a scale out architecture.
+GPS trajectories originate in the form of a series of absolute lat/lon coordinates. Map-matching is the method of locating the GPS observations onto a road network. It transforms the lat/lon pairs into pairs of a road identifier and a fraction representing the relative position on the road. This preprocessing is essential to trajectory data analysis. It contributes to cleaning the data, as well as preparing it for network-related analysis. There are two modes of map-matching: (1) offline, where all the observations of the trajectory exist before starting the map-matching, and (2) online, where the observation arrive to the map-matcher one by one in a streaming fashion. Map-matching is known to be an expensive pre-processing, in terms of processing time. The growing amount of trajectory data (e.g., autonomous cars) call for map-matching methods that can scale-out. This thesis is about proposing such a solution. It shall survey the existing Algorithms, benchmark them, and propose a scale out architecture.
 MobilityDB has types for lat/lon trajectories, as well as map-matched trajectories. the implementation of this thesis shall be integrated with MobilityDB.