T1.3 – Performance Benchmarking and Evaluation

A benchmarking strategy will be developed and the platforms performance will be evaluated, based on well-established benchmarks, such as the Sequoia 2000 and Paradise benchmark3. In particular, the benchmark will be based on OSM and Natural Earth datasets, complemented by synthetic social data from the LOD2 Social Intelligence Benchmark. Further, to perform benchmarking tests that can deal with very large datasets, we will develop a suitable infrastructure by (1) evaluating existing high-performant and compact GIS storage formats for adoption of best practices (e.g. Oracle Spatial, PostGIS), (2) developing a suitable process for extract-transform-load of geo data, including coordinate transforms and schema mapping (e.g. GDAL/OGR, GeoKettle). This is in itself a matter of benchmarking but also enables running benchmarks targeting diverse geospatial workloads such as localized, potentially high frequency accesses for route planning and querying; as well as aggregation queries that span large portions of the map and join with thematic data. The Sequoia workload is an initial checklist item for validating functionality and relative performance as opposed to existing GIS. Geoknow will move beyond the state of the art by using and further refining the geospatial benchmark built in LOD2, emulating heavy drill-down style online access patterns and accessing large volumes of thematic data. An example of this is zooming on a map shaded according to population density or real estate prices. Beyond this, benchmarking will look at more complex analytics such as deciding locations of services based on population distribution, competitive services, road network capacity and the like. The last category is not expressible as a query but requires database resident application logic. Further, to compare GKS and its components with other state of the art systems, we will use the SEALS project benchmarking services. This will provide us with an objective evaluation of the GKS and its components. Benchmarks will be done early, so as to provide constant tracking of performance. Virtuoso's relational GIS functionality will be compared to PostGIS using the full scale OSM data and typical OSM queries and updates. Further, an RDF version of this will be run on Virtuoso and its performance will be compared to the performance attained with OSM in relational form on Virtuoso.


D1.3.1 Design and Setup of Benchmarking System
D1.3.2 Continuous Report on Performance Evaluation
D1.3.3 Continuous Report on Performance Evaluation
D1.3.4 Continuous Report on Performance Evaluation

Other Tasks in this Workpackage

T1.1 Common requirements specification
T1.2 GeoKnow architecture & system design
T1.4 Component integration and GeoKnow Generator

Hosted by

Universität Leipzig , InfAI: Institut für Angewandte Informatik

Funded by

EU Seventh Framework Programme (FP7)

Community and Social Media



EDF2015 and Linked Data Europe: Big Geospatial Data Workshop ( 2015-11-24T23:46:33+01:00 Alejandra Garcia Rojas)

2015-11-24T23:46:33+01:00 Alejandra Garcia Rojas

In 2015, the European Data Forum took place in Luxembourg on the 16th and 17th November. GeoKnow team had the pleasure to be present at the event with a booth for showing GeoKnow results. The conference welcomed over 700 participants from industry, research, policy makers, and community initiatives form all over Europe. Read more about "EDF2015 and Linked Data Europe: Big Geospatial Data Workshop"

Linked Open Data Switzerland at SWBI2015 ( 2015-10-12T09:56:15+02:00 Daniel Hladky)

2015-10-12T09:56:15+02:00 Daniel Hladky

Daniel Hladky from Ontos presented GeoKnow at the SWBI2015 conference two talks. The first talk was the keynote on October 7, 2015 with the title “Linked Data Service (LINDAS): Status quo of the Linked Data life-cycle and lessons learned“. Read more about "Linked Open Data Switzerland at SWBI2015"

FAGI-gis: fusing geospatial RDF data ( 2015-10-05T13:08:20+02:00 Giorgos Giannopoulos)

2015-10-05T13:08:20+02:00 Giorgos Giannopoulos

GeoKnow introduces the latest version of FAGI-gis, a framework for fusing Linked Data, that focuses on the geospatial properties of the linked entities. Read more about "FAGI-gis: fusing geospatial RDF data"

GeoKnow Public Datasets ( 2015-09-19T16:15:29+02:00 Alejandra Garcia Rojas)

2015-09-19T16:15:29+02:00 Alejandra Garcia Rojas

In this blogpost we want to present three public datasets that were improved/created in GeoKnow project. LinkedGeoData Size: 177GB zipped turtle file URL: http://linkedgeodata.org/ LinkedGeoData is the RDF version of Open Street Map (OSM), which covers the entire planet geospatial data information. Read more about "GeoKnow Public Datasets"

GeoKnow at Semantics 2015, Vienna ( 2015-09-18T15:12:48+02:00 Alejandra Garcia Rojas)

2015-09-18T15:12:48+02:00 Alejandra Garcia Rojas

Several partners of GeoKnow were present this year at the Semantics conference 2015. The previous day of the conference we organised a workshop about the work done during these last three years in GeoKnow. Read more about "GeoKnow at Semantics 2015, Vienna"