Marine Knowledge Meeting, 11-12 Oct 2012, Brussels: All About iMarine

iMarine

Donatella Castelli (CNR-ISTI)

Anton Ellebroek (FAO)

Marc Taconet (FAO)

Pasquale Pagano (CNR-ISTI)

Outline

1. Project Info & Objectives (D. Castelli)

2. e-Infrastructure seletected capabilities

(A.Ellenbroek)(A.Ellenbroek)

3. e-Infrastructure governance (M. Taconet)

4. Concluding remarks (M. Taconet)

Marine Knowledge All Projects meeting,

11-12 October 2012

iMarine project info

• Research Infrastructures CP & CSA funded by the

European Commission under the FP7 Capacities

Programme - eInfrastructure Unit DG INFSO

• 1 Nov 2011 - 30 Apr 2014• 1 Nov 2011 - 30 Apr 2014

• 13 partners

• 660 p/m co-funded by EU + 123 p/m in-kind

contribution from externals collaborators


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iMarine Community


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Objective

Launch an initiative aimed at establishing and

operating an e-infrastructure contributing to the

implementation of the principles of the Ecosystem

Approach to Fisheries Management andApproach to Fisheries Management and

Conservation of Marine Living Resources.


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Implementing the EA

• Analysis and processing of a large amount of heterogeneous,

across-domain produced information

• Multidisciplinary & multifacets collaboration at the local,

national, regional and international levels


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Physical and chemical features

Inventories of biological

information

Habitat types

Socio-economic

aspects

Marine resource

assessment

Fishery operation,

processingand trade

e-Infrastructure

Elecronic platform operated by a responsible

entity offering an open set of basic enabling

services (including access to resources) to a

distributed Community of Practice. By distributed Community of Practice. By

exploiting these shared services the members of

the Community of Practice realise economies of

scale.


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iMarine focus…

Assemble

«The creation of the marine knowledge begins with

the observation of the sea and oceans. Data from

these observations are assembled, then analysed

to create information and knowledge.

Subsequently, the knowledge can be applied to Analyse

Production

…

Subsequently, the knowledge can be applied to

deliver smart sustainable growth, to assess the

health of the marine ecosystem or to protect

coastal communities.»

Marine Knowledge 2020 Communication


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iMarine offer…

Assemble

Analyse

Production

…


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Functionality Capacity

Building upon existing e-Infrastructures

e-Infrastructure

services

GBIFMyOcean

Genesi-

DEC

VENUS-C

(cloud)

EGI

(Grid&Cloud)

EMODNET


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e-Infastructure ecosystem

• Interoperability

‒ Each e-Infrastructure can outsource

required facilities to other e-

Infrastructures

The same e-infrastructure can play – The same e-infrastructure can play

both provider and consumer roles

• Competition

– The most effective and sustainable

e-Infrastructures will survive


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Data infrastructure components

Physical architecture

(computing & storage resouces)

Data & sw tool resources

e-Infrastructure software system

Governing procedures and policies

resources


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Software system

Data M

anagement

WorkspaceTime SeriesEcologicalNiche

Modelling

Business DocumentWorkflow

Application

VesselActivityAnalyser

ResourceManagement

ResourceDiscovery

Process Execution

Security

Enabling

SearchMining

Storage

Access

Data M

anagementTransformation


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Functionality classes

Data import & sharing

Data harmonization, validation and

enrichment

Data transformation, publishing and

visualization

Advanced data analysis

Collaborative environments

(Virtual Research

Environments)


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Data resources

• FIGIS (reports)

• MyOcean (environmetal data)

• GENESI-DEC (earth observation data)

• DRIVER (publications)

• OBIS (marine species data)

• GBIF (occurrence points)

• Catalogue of Life (taxonomy)

• WoRMS (marine taxonomy) -> GENESI-DEC• WoRMS (marine taxonomy)

• ITIS (taxonomy)

• FAO SDMX Registry (statistical data)

• AquaMaps (species maps)

• FLOD (open linked data)

• Geonetwork (georefenced data)

• ….

Everything accessible through

– TAPIR, DigiR, OAI-PMH, OpenSearch, OGC W*S ,SDMX,….

-> GENESI-DEC


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Products

The initiative

( CoP, board, policies, sustainability,…..)

The e-infrastructureThe e-infrastructure

(the operational platform)

The system

(the enabling sw system)


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We are not starting from scratch

iMarine

(2011-2014)

Tech

no

log

yTe

chn

olo

gy

EA

P

art

ne

rsh

ips

DILIGENT

(2004-2006)

D4Science (2008-2009)

D4ScienceII (2010-2011)

Info

rma

tio

nTe

chn

olo

gy

Info

rma

tio

nTe

chn

olo

gy

EA


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iMarine Opportunities

1. Functionality

Anton Ellenbroek, FAO

2. Technology

1. Functionality

Select from different Applications

iMarine e-Infrastructure - Options


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TimeSeries

Data

TimeSeries

Data

• Import

• Validation

• Analysis

• Mining

Biodiversity

Data

Biodiversity

Data

• Discovery

• Access

iMarine e-Infrastructure – Selected Options

DataData• Access

• Analysis

Geospatial

Data

Geospatial

Data

• Discovery

• Access

• Process


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Import Formatted and unformatted dataCSV-Import, harmonize, structure, publish as Time Series

Time Series - Import


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Harmonize, Format, and Structure dataUse rules for formatting, range check, code-list recognition, etc.

Time Series - Validation


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Time Series are treated as

tabular data

The Options include:

• Union / Join / Merge / Sum

• Graphs

• Plot on maps

• Analysis with R, weka,

Time Series – Data Analysis

• Analysis with R, weka,

RapidMiner

• Safely Share

• Publish to ‘World‘


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Import Formatted and unformatted Code ListsCreate your own, or import from SDMX registry. Useful in validation

Time Series – Code Lists


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Outlier detection allows to recognize anomalies in n-dimensional data-sets

Time Series Analysis - Data Mining

• Outlier detection

• Frequency detection


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Example: Time Series analysis of Position Observations

Time Series processing techniques can be exploited for :

- Aggregating Vessel Data

- Calculating fishing effort

- Classifying the fishing activity

Time Series Analysis - Vessel Position Analysis


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Biological datasetsBiological Data Provider Status

Catalogue of Life Released (2.9.0)

GBIF Released (2.9.0)

ITIS Released (2.9.0)

OBIS Released (2.9.0) OBIS Released (2.9.0)

WoRMS Released (2.9.0)

IRMNG Release (2.10.0) – October 16

NCBI Release (2.10.0) – October 16


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Biodiversity Products Retrieval

Discovery and access across heterogeneous providersSearch by scientific name or common name; retrieval of taxonomy items and

occurrence points


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Biodiversity – Taxonomic Items

• Active links on selected

items

• Common names matrix

• Checklists (DwC-A)

production via jobsproduction via jobs

– Executed in batch

– Concurrent jobs

– Live monitoring


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Biodiversity – Occurrence Points Visualization

• Active links on selected

items

• Geo-visualisation

• Export

– DarwinCore– DarwinCore

– CSV

– CSV for openModeller


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A set of probabilistic operations on Occurrence Points.

Two thresholds: T° for spatial proximity. Ts for a similarity confidence.

TsTBAMerge ,),( °

TsTBAInters ,),( °

A

x,y

Event Date

Modif Date

Author

B

x,y

Event Date

Modif Date

Author

<T°

=

Biodiversity – Occurrence Points Analysis

TsTAesNoDuplicat ,)( °

)( AOnEarth

)( AInSea

Author

Species

Scientific

Name

Author

Species

Scientific

Name

LexicalD(Author)

*

LexicalD(SciName)

> Ts

Take the most Recent


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Biodiversity – Occurrence Points Analysis

• Dedicated environment for

occurrence points

management

• Open environment

• Export

– DarwinCore

– CSV


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– CSV

– CSV for openModeller

Geospatial A Simple Scenario

After the Joint Activity with the other participants

Marine Knowledge All Projects meeting, 11-12

October 2012

Aq

ua

ma

ps

Su

itab

le

Distrib

utio

n

Visualization Example; Neural Network inferred suitable range maps

DISTRIBUTIONS

AQUAMAPS_SUITABLE

Aq

ua

ma

ps

Ne

ura

l

Ne

two

rk S

uita

ble

Distrib

utio

n

DISTRIBUTIONS

AQUAMAPS_SUITABLE_NEURAL_

NETWORK


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Quality Analysis on Absence\Presence Points (Res. 0.5 degrees)

Aquamaps_suitable ( eq. to native)

TRUE POSITIVES 13

FALSE POSITIVES 0

TRUE NEGATIVES 7

FALSE NEGATIVES 21

ACCURACY 0.49

SENSITIVITY 0.38

SPECIFICITY 1

OMISSION RATE 0.62

ROC BEST THRESHOLD 0.17

AUC 0.41

A big plus: Integrated Quality Analysis with Biodiversity products

EVALUATORS

QUALITY_ANALYSIS

Quality Analysis on Absence\Presence Points (Res. 0.5 degrees)

Neural Network_suitable (eq. to native)

TRUE POSITIVES 32

FALSE POSITIVES 0

TRUE NEGATIVES 7

FALSE NEGATIVES 2

ACCURACY 0.95

SENSITIVITY 0.94

SPECIFICITY 1

OMISSION RATE 0.059

ROC BEST THRESHOLD 0

AUC 1


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iMar

ine

iMarine e-Infrastructure

Data M

anagement

WorkspaceTime SeriesEcologicalNiche

Modelling

Business DocumentWorkflow

Application

VesselActivityAnalyser

EUPL

Application Platform

ResourceManagement

ResourceDiscovery

Process Execution

Security

Enabling

SearchMining

Storage

Access

Data M

anagementTransformation

Externalinteractions

SUBSYSTEM BOUNDARY

Subsystem Boundary


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Se

rve

rS

erv

er

Se

rve

r

Secure, Powerful, and Standard-based

Portal

application

Se

rve

rapplication

• Secure: all data moved over the network and all server to server communications

are authorised and encrypted; data can be stored encrypted

applicationgCube Enabling Technology


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Virtual Research Environments

User uploads/selects

apps

User uploads/selects

apps

• Stored in Software Repository

User register/selects

data sets

User register/selects

data sets

• Accessible through Mediators

VRE is the hardware, data, and applications allocated for a timeframe

to a group of people for effective collaborations

VRE is the hardware, data, and applications allocated for a timeframe

to a group of people for effective collaborations

data setsdata sets Mediators

Apps are executed on the most suitable HWApps are executed on the most suitable HW

• System deploys, configures, executes and monitors

User invites other usersUser invites other users

• System controls authentication and enforces policies


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Summary

• An advanced data e-Infrastructure

• across location and ownership boundaries

• across technological boundaries

• regulated by governance and policies (EUPL)

• Designed for future developments• Designed for future developments

• integrate or develop applications

• designed to grow incrementally in size

• share, harmonize, transform data


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e-Infrastructure Governance

Marc Taconet

(FAO)


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e-Infrastructure governance

• Objective 1 of iMarine<<

To develop community-driven policies enabling:

– governance and operation of a data infrastructure,

– sharing of data and other resources, and processing data


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– sharing of data and other resources, and processing data

In order to support the Community of Practice in implementing the Ecosystem

Approach to fishery management and marine living resource conservation

>>

� role of the iMarine Board

iMarine Boards’ tasks

• Mobilize user community

• Develop governance model

• Address systems’ harmonization


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The iMarine Board

• Mobilize the user community

– Core set of influential partners

stimulated to work together on three

main business cases:Support to implementation of the EU Common Fishery Policy

• FAO

• DG MARE

• Eurostat

• NEAFC

• MEDDE/DOFFis

he

rie

s

Support to implementation of the EU Common Fishery Policy

Support to FAO’s deep seas fisheries programme

Support to regional tropical LME pelagic EAF community

– Raise awareness on the offer

– Position/align the offer versus the needs


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• IRD

• ICES

• IOC/OBIS

• FIN

• CRIA

• VLIZ

• T2/GENESI-DEC

En

vir

on

tB

io-d

ive

rsit

y

The iMarine Board

• Develop Governance model, with sustainability

focus» Governance is the combination of

processes (including relationships among stakeholders),

structures (including formal and informal institutions), and


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structures (including formal and informal institutions), and

instruments (policies, laws)

implemented by the board,

» through which stakeholders interests are articulated, right and

obligations are established, and differences are mediated

iMarine BoardAdvisory

Council

Recomm.

Explain

Marine Community

Project

Boards

iMarine Project

Eurostat

DGMare

• An interface between the CoP and the data infrastructure owners

• Designed to allow control of EA Community on Data Infrastructure Developments

• Forerunner of a Governance structure

The iMarine Board –develop Governance model


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DecisionRecommendations

ICESEurostat

UNEPIUCN(GOBI)

FAO

RFBs

FIGIS

Emodnet

Cat.of LifeEcoscope

IFSA

OBIS

The iMarine Board

• Develop Governance model, with sustainability

focus

– Policies as governing instruments

• Data access and sharing policies

• Software and hardware sharing policies


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• Software and hardware sharing policies

The iMarine Board

• Address the harmonization of systems

– Rationalizing solutions among partners (cost efficiency)

• 4 technical clusters: Biodiversity, Geo-spatial, Statistical, semantics

– Agreeing on “iMarine” standards

• OGC, Darwin Core, SDMX, RDF

• Includes promotion of new standard (e.g. FLUX)

– Mainstreaming requirements and specifications

�Operationalization of the agreed formats and protocols


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The iMarine Board• Result of Systems harmonization

VLIZ

IOC

T2

MyOcean

SeaDatanet

Other sources

Oce

an

en

viro

nm

en

tTa

xon

om

y

Emodnet

WORMS

OBIS

Niche Niche Policy fmk

FLUX std

Policy fmk

FLUX std

xxx

Geo-

Processing

services

Geo-

Processing

services


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FIN

CRIA

IRD FAO

SDMX

FIGIS

FLOD

FisheriesBiodiversity

ESTAT

DG-MARE

OGC

SDMX

National DOF

Ecoscope

ICES

SDMXDCRDF

RDB

Aquamaps

Niche

modelling

algorythms

Niche

modelling

algorythms Open Source

software

OpenSSDMX -

CLM

Open Source

software

OpenSSDMX -

CLM

FLUX stdFLUX std

Conclusion

What’s peculiar about iMarine ?


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What’s peculiar about iMarine ?

What are we looking for ?

What’s peculiar about iMarine

• The iMarine resources offer is about

– Integrating and managing services across systems’

administrative boundaries

– End users:– End users:

• Interactive gateway for collaborative science: VREs

– Infrastructure owners:

• Platform providing outsourcing services: computing,

distribution, scaling, interoperability

• Cloud hosting services


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• iMarine Positioning in Open data perspective

O

B

I

S

O

B

I

S

SE

AD

ATA

NE

T

Ge

no

mic

s

F

I

R

M

S

F

I

R

M

S

iMarine

Thematic

aggregators

Cross-thematic

federator

What’s peculiar about iMarine


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SE

AD

ATA

NE

T

GE

OS

EA

S

Ge

no

mic

s

SS

Data locked

in isolated

computers

• Strategic alliances with Federators:

– Thematic aggregators of data providers

For major impact, we look for


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– Thematic aggregators of data providers

– Scientists end-user needs

– Governance and policy models

LandscapeLandscape

D4Science e-InfrastructureD4Science e-Infrastructure

gCube FrameworkgCube Framework

Thanks for your attention

www.i-marine.org

portal.i-marine.d4science.org


11-12 October 2012

gCube FrameworkgCube Framework

gCube AppsgCube Apps

DiscussionDiscussion

portal.i-marine.d4science.org

www.gcube-system.org

gcube.wiki.gcube-system.org