Tuna atlas

iME4a. iMarine Tuna AtlasiME4a. iMarine Tuna Atlas

Marc Taconet/ Anton Ellenbroek / Yann Laurent

FAO Fisheries Department

Tuna Atlas Presentation Outline

• Collection

• Harmonization

• Aggregation

Tuna Atlas Use Case

Tuna Atlas Data Analysis and Dissemination

• Code List Management

• Mapping and mapping; COTRIX and GEO-Explorer

• Statistical data analysis

• Spatial Data Analysis; SPREAD,

• Storage and Dissemination; SDMX and FIRMS

Tuna Atlas Data Analysis and Dissemination

The results and summary

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The Tuna Atlas use casethe seascape

Collection

HarmonizationHarmonization

Aggregation

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Data Collection

• FAO compiles global tuna nominal catches and

tuna and billfishes catches (Tuna Atlas) annually

• Loaded in a database and published on-line:

– http://www.fao.org/fishery/statistics/tuna-

catches/query/en

Tuna Atlas Use Case

catches/query/en

– http://www.fao.org/figis/geoserver/tunaatlas/

• Mostly manual, data sources are heterogeneous

• How can a VRE improve the collection process?

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• Convert to one standard structure

• Validate against reference standards (e.g. to

the ISSCFG / ASFIS / ISO Country code list)

• Validate content (errors, gaps, formats)

Time series harmonization

Tuna Atlas Use Case

• Validate content (errors, gaps, formats)

• Reconcile with existing data (older)

• How can a VRE produce Harmonized time

series for analysis, mapping, publication

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Aggregation; much more than the sum of

all contributions, about more than data

• Policy framework for co-management of tuna data:– based on Open Access / Open Data

– sharing data, tools and processes

– software development policies

– Guidelines and best practices

Tuna Atlas Use Case

– Guidelines and best practices

• Policy for governance– Any institution can become an iMarine partner

– Everybody can be part of the development of the tools

• How can a VRE deliver flexible interoperable data sharing; FIRMS aggregation offers leading examples

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Harmonization• Code list management

• Data validation

• Shared formats (SDMX)

• Shared standard (FLUX)

Aggregation• Fisheries

• Vessel data

• Occurrences

TA Requirements summary

Tabular Data

Policy

Guidelines

Best Practices

AnalysisAnalysis• Time series

Sharing• Repositories

• Open Data

• Fact sheets

• Print

Collection• Multiple formats

• Multiple structure

• Multiple domains

• Data quality MapDisplay• GeoCode

• Store and

synchronize

• Project and share

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Tabular Data

Management

• Time series

trends

• Forecasting

• Modelling

Tuna Atlas Data Analysis and Disseminationa selection of components

Code list management

Mapping

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Spatial Data Reallocation

Analysis

Storage and dissemination

iMarine network of interoperable,

managed and shared resources

TA Analysis and Dissemination components

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• TabMan supports the validation and

harmonization of tuna atlas data

– Code list manager exposes reference data

(including from RFMO)

TA Analysis and Dissemination components

Code list management

(including from RFMO)

– Code lists are easily added in a VRE

• COTRIX will extend this support

– Manage code lists ‘outside’ iMarine

– Living apart together …. Remote but integrated

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Cotrix Import Manage, Publish Code Lists

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TA Analysis and Dissemination components

Mapping 1 Link data: Occurrences Enrichment

Associate Environmental information to a set of

occurrence points of a species using their code lists

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Spatial Data ReallocationReallocate from FAO areas to EEZ

Change spatial resolution and precision of

capture data to better understand fisheries

• SPREAD use FIGIS geospatial data • SPREAD use FIGIS geospatial data

infrastructure and iMarine

• Spread data processing with WPS using

Terradue resources

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SPREAD WPS

Select an external process

Remote resource

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Parameters for the re-allocation

Statistical Manager; OperatorsE.g to extract indicators from Tuna Atlas data

• Tabular data can be processed to e.g.:

– Spatial data reallocation => SPREAD

– (Species) name reconciliation => BiOnym

TA Analysis and Dissemination components

– Trend Analysis => Trendylyzer

– Bayesian modelling => FishBayes

• Select your algorithm and resources

– Algorithms can be predefined, or bring your own

– Resources in infra, remote, or cloud

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Integrating WPS with the D4Science e-Infrastructure

D4Science

Information

System

Other

D4Science

Facilities

E.g. Storage, Social, Geo

Another Another

External (Cloud)

Computing

Facility

WPS

Interface

WPS

Interface

Statistical

Manager

Services

Statistical

Manager

Services

D4Science

Cloud Computing

User

System

User’s Data

101010101

Processing

WPS

Example: Occurrence Enrichment

Occurrences Table with

fields indication

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User-defined spatial

resolution for the projection

Layers: inputs can be i-Marine Geonetwork

UUIDs or Titles, or direct external HTTP links to

files

Supported Formats: WCS, WFS, NetCDF, ASC,

GeoTiffs

Names of the environmental features

Mapping; Project aggregated dataEffort indicator

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• SDMX one option for Tuna Atlas data storage

• Tabular data are easily exposed as Open Data (as Chimaera will explain)

• Tabular data can be extracted and included in

iMarine infrastructure Components

Data storage, sharing and disseminationExample options

• Tabular data can be extracted and included in iMarine information fact-sheets such as VME-DB

• Tabular data can be displayed on maps and stored as map-products

• Dissemination can also rely on sharing through mail, the workspace, or download

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Not a product, but an advanced solution

• A pool of tools:– SDMX format / registry to facilitate data exchange

– An opportunity to access a rich library of integrated tools • Time series presented as Graphs, Maps

• Code lists manager to share reference data and mapping

• Standard Mapping capacities

• R statistical capacities for advanced data analysis and processing

TA Results

• R statistical capacities for advanced data analysis and processing

• Access to remote data (write your own plugin)– Environmental

– Biodiversity

– Fisheries

• A Collaborative managed infrastructure– Policies, basic best practices, and generic guidelines

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