Ecosystem Approach Community of Practice: SPREAD

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SPREAD Profile

The SPatial REallocation of Aquatic Data (SPREAD) aims to provide the conversion of geospatial explicit data from one resolution to another.

The Use Cases were already descibed in D4Science-II, and can be found under the Advanced Curation Use Case.

It was included under ICIS Advanced Curation because in the context of D4Science-II, the starting point for a re-allocation is a TS-Object, and the re-allocation was perceived as a precision of geospatial location of a reported capture without much reasoning or change of the reported values.

A progress report on SPREAD accomplishments and opportunities can be found on BSCW (SPREAD120207.docx).


The problem of re-allocation is fully described in the SPREAD report.

The UNGA asked for a distinction between capture from the High Seas and those taken from EEZ's. Since the reporting for FAO does not include that distinction, a means has to be identified to disaggregate time-series.


The implementation progress can be tracked through the high level ticket in TRAC is [[1]]


With SPREAD capture time-series from ICIS can be re-allocated to another area using geospatial information on:

  • species distribution, and
  • capture areas, and
  • EEZ.

If the intersection between reporting area and target area is not known, SPREAD relies on a facility to generate the intersection using a accurate projection. This intersection engine is located in and developed by FAO. The resulting layers have to be made discoverable and accessible to iMarine services through GeoNetwork.

The generated products are reviewed before they are shared with other users and VRE for e.g. inclusion in species distribution analysis, which can be either and expert-review, or a machine driven review.

No public tools are foreseen, all data and products remain the property of the SPREAD user.

Priority to CoP

List proposed solution priority following the iMarine Board priority setting criteria:

  • Identified community: Users now: The need was identified by the UNGA, and the users are in FAO-FI. In general, disaggregation is in high demand in understanding Time-Series in the agriculture and fisheries domains.
  • Potential for co-funding: reasonable, if a community can be identified that requires a. dynamic intersection generation, b. statistical data disaggregation.
  • Structural allocation of resources: To be discussed in a. SB, b. iMarine Board
  • Referred in DoW: Not explicitly.
  • Business Cases: Supports BC 1.
  • How does the proposed action generally support sustainability aspects If based on OGC standards, SPREAD will be key to bringing the power of the infrastructure to a geospatial explicit data community as a product that is easy to understand (for OGC community members), brings additional resources that do not exist in geo-statistical workflows (integrated R, TS management), and offer VRE secure collaboration.
  • How consistent it is with EC regulations/strategies (eg INSPIRE, ... ): For SB
  • Re-usability of SPREAD works in two directions; it re-uses components if the iMarine infrastructure such as ICIS, and from the FAO infrastructure such as benefits – Since SPREAD relies on the further development of existing resources, the compatibility of the the resulting services and products is high.


Relation to EA-CoP Software
SPREAD relies for its geospatial products, such as intersections, on the FAO SDI, namely the intersection engine and the Geonetwork. In addition, the EEZ's are managed through FAO, but were provided by VLIZ.
Relation to D4S technologies
The data for SPREAD will rely on ICIS for some of data to be re-allocated. The Timeseries contain the capture records, and information on some of the environmental preferences for the species.
The SPREAD algorithm is foreseen as a WPS process.
The results of SPREAD will rely on the GeoExplorer to vizualize the results of the re-allocations. ICIS is foreseen as the store of re-allocated TS-Objects. For
Does the proposed solution solve other problems associated with EA-CoP Business Cases?
SPREAD has interesting features that can be made available to other use cases. For the development of SPREAD, a lot of ground was broken to establish a SDI, and the integration with WPS and the i-Marine infrastructure was pioneered in SPREAD. This has equipped the infrastructure for advanced processing of Geospatial data. These features are indeed interesting to BC1, and BC2.


How big is the expected user community after delivery?
SPREAD has different user categories: Developers, Users, and Consumers.
* The developers arrange the content, ensure they align to iMarine metadata formats, and are of good enough quality. They also ensure that the algorithm has sufficient resources, and performs well.
* The users perform re-allocation by selecting the dataset to be re-allocated, the target to re-allocate to, the algortihm to apply, and publish the results.
* The consumers are iMarine VRE users (remember, this is not a public dataset producer), or trusted collaborators having been granted access to the geospatial products directly. They are trusted with the task to analyse the results, and re-use the products outside the e-infrastructure.


Are the proposed measures effective?
SPREAD is a new developemnt, and it's productivity can not be measured against a benchmark.
Does it reduce a known workload?
Since SPREAD is a new and groundbreaking application, it can not be stated tht it reduces a work-load.


Is the proposed solution cheap?
No, it should only be pursued if the components can be re-used in other scenarios. The iMarine Board will be involved in the development of the Business Case supporting SPREAD.
Expected effort in PM:


How is the component delivered to users? (Design / on-line help / training material / support).
SPREAD is conceived to be delivered through a VRE that starts from the ICIS (timeseries data to re-allocate). This should provide GIS features to GIS-enable the time-series.
It also requires an user interface to select a target area & probability-based data sources used to re-allocate,
For the algorithm, machine access to the intersection layer is required.
The output are timeseries with a new geospatial dimension (target area).
Reallocated data maps (as well as initial data maps) have to be managed by generic TimeSeries thematic mapping functionalities.
These maps will have to be accessible by other VREs if the owner so decides.


Are they safe?
There are no privacy issues of legal or physical persons involved. However, the risk of misinforming the general audience with SPREAD products requires that a proper work-flow is ensured before data can be published.
Need the proposed solution to manage confidential info at data / dataset / organizational level?
Initially this is not needed.
However, every map produced can only be shared by the VRE User that generated it in the VRE. Only the VRE manager can publish the generated maps to render them discoverable and visible to other VREs.
Describe security and privacy issues:
The SPREAD Policy for data access and sharing is described here


The SPREAD Policy for data access and sharing is described here


Do they introduce moral hazard? (A hazard here is the risk that users will behave more recklessly if they are insulated from the effects of the software, or if they do not understand what it produces, where data come from, what they represent etc. .)

Several critical comments were made that have to be better understood before SPREAD can be fully implemented:

  1. Several FI officers have doubts that the produced re-allocated maps can be distributed openly as FAO and / RFB maps. They may convey a message that goes beyond the quality of the data and the algorithm involved.
  2. There is no intrinsic generic mechanism to check the statistical relevance of the products. This may lead to a product that can not be validated.
  3. The quality of the source data may not be up to standards for the required processes. One important reason to develop SPREAD was indeed to identify these gaps in e.g. reliable maps of EEZ's, difficulties in generating reliable intersections, solving issues with authoritative metadata, e.g. to differentiate between country, flag, and sovereignty.
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