Ecogrid & Virtual Laboratory for e-Science Willem Bouten, project leader Floris Sluiter, design...

Ecogrid&

Virtual Laboratory for e-Science

Willem Bouten, project leaderFloris Sluiter, design & implementationGuido van Reenen, data analysis

Victor Mensing, VlinderstichtingDirk Zoetebier, SovonAart Jan van der Linden, Talmon Comm.

from field observation to spatial knowledge

CBPG

Virtual Laboratory for e-ScienceMission

To boost e-Science by creating an e-Science environment and carrying out research on methodologies.

Essential components

- e-Science development areas

- a Virtual Laboratory development area

- a Large-Scale Distributed computing development area, consisting of high performance networking and grid parts

Virtual Laboratory for e-ScienceAim

To develop and apply a Grid and Virtual Lab technology based information system and research environment.

Virtual Laboratory for e-Science

P1 – e-Science in ApplicationsP2 – generic Virtual Laboratory methodologyP3 – large-scale distributes systemsP4 – scaling up & validating in ‘real-time’ applications

VL- e

The VL-e project has four programme lines, most of them containing more than one subprogramme.

Virtual Laboratory for e-Science

P1 – e-Science in ApplicationsSP1 – Data Intensive ScienceSP2 – Food InformaticsSP3 – Medical Diagnosis & ImagingSP4 – BiodiversitySP5 – Bioinformatics ASPSP6 – The Dutch Telescience Laboratory

VL- e

e-Science in Applications

Research of the P1 line is carried out within the following subprogrammes:

Virtual Laboratory for e-Science

Biodiversity

Aim

To develop and apply a Grid and Virtual Lab technology based information system and research environment

for identification, distribution, integration and analyses of observations and model results of the dynamics of flora and fauna

VL- e

e-Science in Applications

biodiversity

Virtual Laboratory for e-Science

Biodiversity

Partners:

CBPG – Computational Bio- and Physical Geography(IBED – Institute for Biodiversity and Ecosystem Dynamics)(UvA – Universiteit van Amsterdam)

RNLAF – Royal Netherlands AirforceVOFF – Association for Research of Flora & Fauna

And co-operation with other programme lines, especially subprogrammes of P2 (generic Virtual Laboratory methodology)

VL- e

e-Science in Applications

biodiversity CBPG

Virtual Laboratory for e-Science

Biodiversity

Two main components:

1. a national database for biodiversity information

this talk (Ecogrid)

2. a PSE for integrated analysis of observations and model results

topic of Judy Shamoun-Baranes (BAMBAS)

VL- e

e-Science in Applications

biodiversity

EcoGrid

EcogridObjectives

1. Construct a virtual database that is connected to geographically distributed databases which contain information on the distributions of species, on landscape characteristics and on weather.

EcogridObjectives

1. Construct a virtual database that is connected to geographically distributed databases which contain information on the distributions of species, on landscape characteristics and on weather.

2. Develop generic methodologies and tools for scale conversions, to be able to integrate and interpret data that are observed at different spatial scales.

EcogridObjectives

1. Construct a virtual database that is connected to geographically distributed databases which contain information on the distributions of species, on landscape characteristics and on weather.

2. Develop generic methodologies and tools for scale conversions, to be able to integrate and interpret data that are observed at different spatial scales.

3. Use this infrastructure across the boundaries of organisations to indentify:- spatial wood web structures- biodiversity hotspots- effects of changed land-use- ...

Example: insect diversity and Red-backed Shrikes

### #

##

#

#####

###

##

##

### ############ #####

######### ##### #

##### ######### ##

##### ########

# ####

###

#

## ######

## ######

#### #####

## ### #

#####

#####

## ## #

######

#####

####

# #

##

##################

## ###################

########### #

### #

###

######

#

#

######

############ #

#### ####

####

####

### #

#

##

#

###

###

####

##

## #

# ##

## ####

# #

#

#

#

#

# #

##

#

##

########

Nitrogen dep. }

Initial Situation

VlinderstichtingFLORONNMVRAVONBLWGVZZ ANNEMOONEIS-NLTineaSOVON

VOFF{

Ecogrid - data acquisition

} centralVOFF

database

Ecogrid - data acquisition

observationobservationtaxonomytaxonomy localitylocality

SOVON

NCO databases

central databases

NCO databases

Data shared by all NCO’s

NCO-specific data

RAVON

GISmapsetc.

ACTIVE MEMBER

PK Person ID

central databases

SPECIES

PK Taxon ID

OBSERVATION

PK Observation ID

Species ID

NCO databases

OBSERVATOR GROUP

FK Person ID

FK Observation ID

Main Observator

TAXONOMYWEBwebpages

PERSONSportal login

METADATA

GIS LOCATION

km hokx, yrouterelevé

EXTRA INFO

• Spatial functions to query (SQL) within and across layers:

• Equals()

• Disjoint()

• Intersects()

• Touches()

• Crosses()

• Within()

• Contains()

• Overlaps()

• Special indexing techniques (GisT)‘Layers’ build with these data types,

stored as tables in PostgreSQL/PostGIS.

spatial databases

dataacquisition

portal

dataacquisition

portal

EcoGridvirtualmeta

database

Spotfire

data miningmodules

geostatistics

scale conversionmodules

modelexperiments

processeddata

centraldatabases

VOFF

centraldatabases

VOFF

landscapelandscape

weatherweather

VL-eScience Research Environment

scienceportal

scienceportal

BAMBASdatabase

Ecogrid system - overview

dataacquisition

portal

dataacquisition

portal

EcoGridvirtualmeta

database

Spotfire

data miningmodules

geostatistics

scale conversionmodules

modelexperiments

processeddata

landscapelandscape

weatherweather

VL-eScience Research Environment

scienceportal

scienceportal

BAMBASdatabase

Ecogrid system - prototype

SOVON

Ecogrid - portal prototype

Ecogrid - portal prototype

Ecogrid - portal prototype

Ecogrid - portal prototype

Ecogrid - portal prototype

• PostgreSQL (and Postgis) are especially suited for large scientific databases

• By the end of this year all the databases will be populated and we will have online data acquisition.

• Then we will shift our focus on using the data and concentrate on Analysis and Datamining

Concluding remarks