iMarine initiative overview

Extended Board
Meeting
16-17 October 2013

Introduction – iMarine
Collaboration Opportunities

Marc Taconet (FAO)
Donatella Castelli (CNR)
iMarine Extended Board meeting, 16-17 October, FAO (Rome)

Introduction

• Welcome address and Meeting Participants
– iMarine Project staff
– iMarine Board members
– Members of the Extended Board
– Other invitees
• External
• FAO


Introduction
New: Extended Board
• ABAUNZA Pablo
• DE MOOR Willem
• EVRARD Maud
• MANZELLA Giuseppe
• SAGARMINAGA Yolanda
• TELLER Anne
• THOMAS Hannah
• WEBSTER Chloe
• HARRIS Peter
• CHASSOT Emmanuel
• STROMME Tore
• GUITTON Jerome
• GILMAN Eric
• YE Yimin
• CAMPANIS George
• FITZGERALD Brian
• RAMM David
• HARLEY Mark
• RUPP Jonas
• HERRERA Miguel
• DEVILLERS Rodolphe

Spanish Institute of Oceanography (IEO)
VLIZ
Science Europe
ENEA
Fundacion AZTI
EC
UNEP-WCMC
MEDPAN
GRID Arendal
IRD
NANSEN
Agrocampus
Sustainable Fish
FAO
SEAFO
Fishery Officer with the Sea Fisheries Protection Authority
CCAMLR
NAFO
GOLD
IOTC
TBTI


3

Introduction
Additional invitations to extended Board ex. FAO Staff
• BOEHM Klemens
• BAILEY Megan
• BUSH Simon
• GREENE Randal
• CONNOR David
• FONTAINE Olivier
• ERNENS Marcel
• SAAB Waddah
• LIHTENEGER Darja
• LEBLOND Emilie
• SHEPHERD iain
• MURRAY Alistair
• MARSHALL Barb
• HALL Martin
• PALLARES Pilar
• BERTELSEN Mette
• HERNANDEZ Pilar (FIPI)
• MORGAN Simon
• CAMPBELL Neil
• ROBIN Agnes
• KIEFER Dale
• HOAD Richard
• SINI Margherita

UNI-Karlsruhe
BESTTUNA
BESTTUNA
TBTI
Marine Environment and Water Industry, DG Environment
Maritime policy for the Mediterranean and Black Sea, DG MARE
EUROSTAT
DG RTD
European Environmental Agency (EEA)
IFREMER
EMODNET
MMO
NAFO
IATTC
ICCAT
ICES
GFCM
CCSBT
NAFO
Research Infrastructure Unit
University of Southern California
FAO
FAO


4

Outline
PART1 – What is a data e-infrastructure

PART2 - Serving policy frameworks facing BIG challenges – example of EAF

•x
PART 3 - The power of an e-Infrastructure -Synergies and efficiencies
through Global collaboration communities


5

Outline

PART1 – What is a data e-infrastructure

iMarine Extended Board meeting, 16 October 2013, FAO (Rome)

Project information

•
•
•
•
•
•

CNR
NKUA
CERN
E-IIS
FORTH
TERRA2

Members of the Community

Technology

• TrustIT

• ERCIM

Dissemination

Finance and admini

EU FP7 Capacity e-Infrastructure project, Nov 2012- Apr 2014

•
•
•
•
•

CRIA
FAO
FIN
IRD
UNESCO

• NEAFC

www.i-marine.eu
7

iMarine Objective
Launch an Initiative aimed at establishing and
operating a data Infrastructure supporting the
implementation of the principles of the
Ecosystem Approach
to Fisheries Management and Conservation of
Marine Living Resources


Challenges

Capacity & Diversity
• Analysis and processing of a large amount of heterogeneous,
across-domain produced information
• Multidisciplinary & multifacets collaboration at the local,
national, regional and international levels
Marine
resource
assessment
Marine
Planning

Socioeconomic
aspects

Habitat types

Inventories of
biological
information
Physical and
chemical
features


Fishery
operation,
processingand
trade

e-Infrastructure

Elecronic platform operated by a responsible entity offering
an open set of basic enabling facilities (including access to
resources) “as-a-service” to a distributed Community of
Practice.

Fostering harmonization
& standardization across
communities

Economy of
scale

Time to
market

Quality of
service


Community of Practice point of view:
Services
Services
• Collaboration
• Sharing
• Publication
• Storage

• Processing
• Analysis
• Modeling
• Integration
• Enrichment
• Transformation
• Access
• Retrieval

Community of Practice point of view of the:
Open set of services

• The set of “services” can change over the time
– new / enriched elements in a family
– better quality elements
– new service families

• Support is provided to those adding new
elements in a family
e.g. models, statistical algorithms, mappings


Exploiting service through APIs


Virtual Research Environments

VRE

VRE

VRE

VRE = Comprehensive, flexible, and secure Web-based working environment
designed to serve the application needs of a community working for a specific goal

iMarine VREs
(16 October 2013)

gCubeApps
(public)

controlled
access

AquaMaps VRE


Documents Workflow VRE


ICIS VRE


Inside iMarine:
gCube

385 components
(web services, libraries,
portlets)

Hosted Technology and
data
• Cassandra/Hadoop/Mong
oDB Clusters
• Virtuoso TripleStore
• SDMX registry
• OGC services cluster
(GeoNetwork, Geoserver,
WPS, Thredds)
• FishBase and SeaLifeBase
DBs
• ……


gCube:
selected products

iMarine Product Catalogue
Application bundles
BiolCube
ConnectCube

StatsCube

GeosCube


e-Infastructure ecosystem
building on previous efforts


Inside iMarine:
data capacity
- FAO CodeLists
- IRD CodeLists
- FAO Global
Aquaculture
Production
- FAO Global Capture
Production
- FAO Global
Production
- Eurostat
- …

Semantic
Data

Documents

- FAO FishFinder Factsheeets,
OceanDocs, BHL, CEEMaR,
BioRisk,……
OAI-PMH, OpenSearch

Biodiversity

Statistical
data

data
Geospatial

RDF, OWL

data

SDMX *
- WorldOcean Atlas, MyOcean, Gebco,
NODC, W.O. Atlas, FAO GeoNetwork
….
ISO19139 (OGC W*S)

- FAO FLOD, DBPedia, IRD
Ecoscope, ……..

- OBIS, WoRMS, ITIS, AquaMaps,
FishBase, SeaLifeBase, CoL, GBIF
- ……..
DarwinCore


Same infrastructure: multiple projects

www.d4science.org

Outline

PART2 - Serving policy frameworks facing BIG
challenges – example of EAF


24

Serving policy framework facing BIG challenges – the EA

» BC1: Support to implementation of the EU Common Fishery Policy
» BC2: Support to FAO’s deep seas fisheries programme
» BC3: Support to regional tropical LME pelagic EAF community
 Collaboration with SmartFish
 Co-ordination with ABNJ

Biodiversity

• The iMarine Business Cases:

Environment

– Representatives of a set of influential community partners
– Act as mediators between EA-CoP at large and the
infrastructure, in order to drive technology developments
– stimulus - work together on three EA policy challenges
(business cases)

Fisheries

• iMarine Board – the Community Governing body:

• FAO
• DG MARE
• Eurostat
• NEAFC
• MEDDE/DOF
• IRD
• ICES
• IOC/OBIS
• FIN
• CRIA
• VLIZ
• T2/GENESIDEC

Matching the technology offer with community needs

A vision in support to EAF needs
Biodiversity and
habitat
preservation

Fishery resource
productivity

Social and
economic goals

values

Policy maker
Objectives

Fishery manager
Indicators /
Ref points
Scientist

Statistician

Distribution
of non-target
species /
habitats

Abundance
levels fish
stocks

Distribution
of fishery
activity

Socio-economic
structure of
fishing
communities

models

Data
repositories

Data manager

iMarine support to data needs in the EA policy framework
1. Species niche modeling to monitor health and trends of the ecosystems

2. Fine grained catch & effort for resources assessment,
management of fishing quota, fishing impact assessments

3. Mapping of sensitive or fragile habitats in need of special management
(EBSAs or VMEs)

4. Comprehensive species knowledge base to address
impact of fishing on marine ecosystems


27

Outline

PART 3 - The power of an e-Infrastructure -Synergies
and efficiencies through Global collaboration
communities


28

Synergies and efficiencies through Global collaboration & CoP
Monitoring ecosystem health and trends requires baselines
Species predictive mapping

BiolCube

Source: Kaschner et. al. (2006)


29

Maintaining ecosystem health requires
Identification of Sensitive or fragile habitats
– Biodiversity models

GeosCube

• Joint occurrence of n taxa

– Environmental enrichment of
species occurrence data

Source: Coll et al. (2010)

BiolCube


30

– Environmental enrichment of species occurrence data
Enriched species
occurrences

for each occurrence,
selection of the most
appropriate proxi data
according to:

Environmental
variables

-Time range
- Z range (depth)
Physical
variables


fishery policy making and management requires
Global assessments of high seas resources vs. resources inside EEZs
Fish quotas allocation

StatsCube

1. Higher resolution catch & effort assessment
• through post-factum reallocation of coarse resolution catch statistics based on species distribution
maps

SPREAD


32

Fishery control and surveillance, and adaptive fishery management, require :
- quota uptake monitoring, fishing impact assessment

CONTRIBUTION
TO VALID

2. Near-real-time management of high
resolution fisheries operational data
•
•

StatsCube

Single simplified, more consistent, and cost
efficient workflow
more integrated and higher quality data in
coverage, timeliness, resolution and accuracy

3. Access to MCS data by science
– VMS and e-LogBook data processing under
confidentiality requirements

VTI

33

2. Near-real-time management of high resolution fisheries operational data


2. Near-real-time management of high resolution fisheries operational data
– Promote FLUX as European Global data exchange standard, for MCS and Science
– Demonstrate iMarine’s capacity to produce quality data: VALID
ASSOCIATED INFORMATION
(CODE LISTS, GEOGRAPHIC DATA)
VTI - e-Logbooks, VMS
(Fishing Activity Reports)

FLUX

Flag
State

FLUX

VALID
rules

E-Logbooks
vs.
Species geographic
distributions

FLUX
FLUX

Coastal
State

FLUX

FLUX

DG
Mare

Non-EU
country
RFMO

FLUX

FLUX Infrastructure
2nd iMarine Review

- Brussels, 12 September 2013

SDMX
OTHERS

36

Mapping of sensitive habitats is required for applying special management measures:
Aimed at reducing ecosystem impacts of e.g. Deep sea fishing on fragile ecosystems
(VMEs assessments)


37

Mapping of sensitive habitats is required for applying special management measures:
Aimed at reducing ecosystem impacts of, e.g. Tuna Fishing on by-catch species
(sharks, small tunas, marine mammals, turtles, seabirds)

1. Workflow management for fishery
and scientific data collected on Board
fishing vessels, e.g. by-catch species
identified by Observers on Board fishing
vessels
•

Isurus oxyrinchus (Shortfin mako - shark)

FLUX and FishFrame support
Source: IRD ECOSCOPE

2. Modeling of species geographic
distribution,
•

Source: OBIS / IRD ECOSCOPE

Application of Predictive mapping models,
such as developed by Aquamaps
Source: iMarine / AquaMaps


38


Synergies – a case study
•

In fisheries monitoring, attention is brought to:
– By-catch species: Associated, discarded, protected
– Species which are indicators of fragile habitats (e.g.
VME encounters)

•

Species identification guides are being developed
at regional / national level
– Local efforts would benefit from collated knowledge

•

Issue: many species
names are reported,
with variations and
errors

Chondrichthyes (class), Scombridae (family), Lutjanus spp (genus)
Condrycthiens (vs. Chondrichthyes)
P. notialis (vs. Penaeus notialis)
Pomadasydés, Sparidae (Pageot), Penaeus sp, langouste, seiche
Farfantepenaeus notialis (deprecated) vs. Penaeus notialis (official)

39


Synergies – a case study:

Cross-fertilization opportunities between
fisheries sciences and bio-ecological sciences

•

Taxa name matching / mapping
– Names validation through cross-referencing
with glo bal taxonomic databases
– Capturing mappings between local
expressions and authority lists

Plus …
•

Fisheries Linked Open Data (FLOD)
– Organizing concepts and terms in
comprehensive ontologies available as
Linked Open Data

Results in …
• Comprehensive knowledge bases on:
– Species vernacular / multilingual names
– broad range of species information

•

contributing to fill the gap of knowledge

40

Fisheries science will benefit from comprehensive knowledge bases integrating fishery
and biodiversity data sources:

APPLIFISH
• Species focused information
disseminated through mobile
applications, for use by anyone at
consumer places
– Requires capacity to integrate multiple /
complementary sources
– Efficiency will rely on broad knowledge base
on species names, combined with GPS
information of Mobile user

Connect
Cube

APPLIFISH


41



42



43


Elements of synergies
– Various Business Cases complement each other:
– End-up building comprehensive toolkit required for entire flow from
raw data collection to policy indicators
– Data produced by A. are inputs to B. – all accessible from same
environment

– Tools are pooled and can be reused across different
communities having similar needs, and enriched
– Exchange among disciplines enhance quality
– Bridge MCS data with science (confidentiality requirements)

Elements of efficiencies
– Partner systems tend to specialize on their strength and
delegate to others


44

Outline

CONCLUSION
What are the ingredients of success


45

Conclusion – ingredients of success

Powerful technology
Community governance
Data access and sharing policies
Business model for Exploitation of the data
infrastructure
– Public-led Partnership business model

46

Outline

Thanks for your attention


47

Synergies and efficiencies
EA-CoP
uptake
BC
overview
P/S support
to BCs

Uptake
Status

GeosCube
BiolCube
2nd iMarine Review

- Brussels, 12 September 2013

48

Fisheries data flow in support to EU’s CFP
Non-EU
country

eRS or national
format 

DOF
Coastal
State

Raw or Aggregated data

Raw data eRS

 FLUX

 FLUX

RFMO

FLUX
eRS

DOF Flag  FLUX
Catch report
State

DG
Mare

SDMX

 FLUX

National
format

Small fleet segments

DCF format ( Fishframe in
future?)

Research
institute

ICES
JRC

DCF

Operational data

Business cases in support to decision making in EA

Other
"iMarine e-Infrastructure for Data Driven Decision Making and Research Workshop"
14th & 15th May 2013, Brussels

Where iMarine infrastructure can support – National nodes

Offer infrastructure services
Non-EU
country

eRS or national
format 

DOF
Coastal
State

Raw or Aggregated data

Raw data eRS

 FLUX

 FLUX

RFMO

FLUX
eRS

DOF Flag  FLUX
Catch report
State

DG
Mare

SDMX

 FLUX

National
format

Small fleet segments

DCF format ( Fishframe in
future?)

Research
institute

ICES
JRC

DCF

Operational data

Business cases in support to decision making in EA

Other
"iMarine e-Infrastructure for Data Driven Decision Making and Research Workshop"
14th & 15th May 2013, Brussels

EU projects

Conclusion – synoptic view
iMarine

FAO projects
ABNJ Deep-Seas
ABNJ
Tunas
IOC Smartfish

Global
Taxonomy
Biodiversity

Emodnet
EuroMarine
GeoSeas
Assemble
JPI Oceans

Human
activity

Genomics

Habitats
Geology

Ocean Observ.
physico-chemico

Physico
Chemico

52

Discussion time


iMarine initiative overview

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