Management AND

Analytics oN

Geotemporal

Data

MAGDa

Spatial Databases

Graph-based data models

Semantic Web

3D GIS and BIM

Cluster computing

Forecasting

Data visualization

https://projekt.beuth-hochschule.de/magda/

10 yrs time series from sensors

Floating Car Data from 500 taxis

Goal1: Crowdsourced Traffic Plattform

Goal2: Mobility Services

Goal3: Spatial Data Streaming / Mining

Goal4: Forecasting / Anomaly Detection

Methods: Statistical & Machine Learning (Python), Linear Referencing (PostGIS), Routing (Graphhopper, Java)

http://excell-mobility.com/

LIDAR Scans of Buildings

Goal1: Integrating BIM with GIS

Goal2: Query BIMs with semantic web technologies

Goal3: Test different aquisition methods and user interfaces for data exploring

Methods: RDF, SPARQL (Fuseki), Pointcloud Storage (PostgreSQL, MonetDB?)

Big Spatial Data

Are FOSS4G Tools we love

Too weak for Big Data?

How To Go Big?

Pros

Scale Out!

Easy in the cloud (AWS etc.)

Many specialized tools

Growing user base (even some GIS people)

Cons

Great lack of spatial functionality

Great lack of knowledge

Great lack of communities

Writing queries can be a PITR

Why not stick to our guns?

Do we actually have Big Data?

Not needed for simple features...

Big Spatial Data

https://www.youtube.com/watch?v=ffuxZ8m2TIc

These are not simple features

What do these examples have in Common?

But, it does not feel like the right match. and yes, it's slow...

We CAn use PostGIS.

Solution

Extend FOSS4G tools


[Array,Column,GPU]-DBs


Data Processing Pipelines


Data Streaming

Technology

Postgres forks, GDAL, PDAL

 

SciDB, MonetDB, MapD

 

GeoTrellis, PySpark, R

 

...

THank You

Management and Analytics on Geotemporal Data

By fxku

Management and Analytics on Geotemporal Data

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