Geographic Components


The general aim of this activity is to provide the resources and applications able to publish, visualise, and analyze the distributional information associated with taxonomic information. Taxonomists require an easy and freely available application allowing to display and/or publish the distribution information directly from simple data sources. However, as present distributional data are far from accurate we urgently also need tools able to:

  • i) examine the degree of completeness of this information,

  • ii) discriminate well surveyed localities from those do not have reliable inventories, and

  • iii) locate the localities in which is necessary to carry on additional surveys in order to recover the environmental and spatial variation of the area. The activity is collaboratively carried out by all the partners.


To provide a generic and open source software solution for the Internet Platform for Cybertaxonomy and to use this as the base for specific tools to:

  • provide output for printed and on-line taxonomic publications

  • visualize distributional information

  • statistically analyse distributional information with regard to completeness of surveys

  • identify gaps to prioritise surveys in order to obtain an unbiased set of data for environmental analysis.


For complete list of Work Package 5.4 components reports visit Components & Milestones page

Map REST Services

The Map Services were developed for visualisation of distributional data.

The latest report presenting these services can be found at Component C5.112 page

Visualise specimen & observation coordinates as simple points

A webservice is built that creates and returns maps (as images) showing point occurrence data.

Specific documentation can be found at:

and examples at:

An example call to the service can look like this:,-0.822|38.328,-0.542|38.062,-0.893|38.062,-0.893|38.012,-1.883|40.78,-4.009|38.062,-0.893&os=1:c/f78755/10/&ms=700,350&bbox=-10,36,8,45&recalculate=true&legend=0

Visualise area distribution data

A webservice is built that creates and returns maps (as images) showing area distribution of a taxon.

Specific documentation can be found at:

and examples at:

An example call to the service can look like this:,,1&ms=500&label=1&bbox=-10,36,8,45

using TDWG area codes which are different than ISO 3166-1 codes

There needs to be separate services that allow uploading and listing of area codes+shapes and status codes.

By default TDWG areas should exist already on the mapping server and should be used if no areas parameter is given.

Analyse distributional data

Calculation service that sums up single occurrences per region can be developed.

A visualisation service for regions could then be used to display colored regions instead of simple points.


Component C5.111: The EDIT MapViewer version 3

The current URL of the web application is:

First implementation of the MapViewer was through Mapbuilder framework, a JavaScript library that provides a client-side solution for dynamically generated web pages from XML (such as Open Geospatial Consortium documents) as well as the OGC Requests (!GetMap, GetFeatureInfo, GetFeature...) necessary to view and query the geo-data.

Since version 2, the tool has been ported to the OpenLayers framework which offer wider functionality.

The geo-data is stored in PostgreSQL with PostGIS extension - a database with a consolidated spatial extension able to make spatial queries (intersect, point-in-polygon, calculate distances, centroids), reproject data, etc. and "usual" queries, including statistical functions. On the next steps we will take profit of both possibilities to statistically analyze geo-referenced data in order to locate well surveyed localities...

The link between data (PostGIS) and web-application (!OpenLayers) is done through GeoServer. It takes the requests and sends a response: a beautiful image (after applying styles).

This web application is not definitive at all. In fact, it lacks of two main issues:

  • Complete interactivity: user doesn't insert data and the analysis (point-in-polygon) to get biological information is not done "on-the-flight". We will have to work with programming (PHP probably) to send the parameters to a spatial SQL function (Contains) to be executed in PostGIS.

  • Complete interoperatibility - legend images are not OGC compliant. It means that they cannot be viewed through any other OGC compliant web-application.

The complete report presenting the EDIT MapViewer functionalities can be found at Component C5.111 page

Component C5.36: GIS database of vectorial and raster maps freely available at the European extent

EDIT geoplatform provides standard GIS layers of surface units (countries, squares, ...) to evaluate the spatial distribution of occurrence data -spatial completeness-, and standard GIS layers of environmental variables (climate, topography,...) to evaluate weather occurrence data represent adequately the gradients of environmental variation -environmental completeness-.

GIS layers of surface units include both administrative units (countries, provinces) and regular equal-area units of different sizes (UTM squares, latitudinal squares, icosahedric triangles). Administrative units exist only for terrestrial areas, while regular equal-area units cover both terrestrial and marine areas. GIS layers of regular equal-area units were elaborated by MNCN-CSIC (EDIT geoplatform, 2007), with the exception of the UTM squares of 2,500 Km2 elaborated by the European Environmental Agency (EEA, 2003).

GIS layers of environmental variables cover the main environmental issues: climate, topography, vegetation, land cover and human population. Climate data include around twenty variables (temperature, precipitation, seasonality, etc.) from Worldclim database. Topography data include elevation above sea level, from Worldclim database, and distance to coast in Km, elaborated by MNCN-CSIC (EDIT geoplatform, 2007). Vegetation data include maps of Normalized Difference Vegetation Index (NDVI) obtained from satellite images by NASA and processed at Clark Labs. Land cover data include the map of land cover categories for the world generated by the University of Maryland, Department of Geography (Global Landcover Facility), and the map of land cover categories for Europe generated by the European Commission Joint Research Centre (Global Land Cover 2000 database).

It's possible to use different geographical extents, from the whole Earth to a selected country or region within Europe. As spatial extent is reduced / increased, analyses can be done with more / less detailed spatial resolutions.

GIS layers in the EDIT geoplatform are all in geodetic coordinates (longitude, latitude), datum WGS84.

A more detailed description of the GIS layers of surface units and environmental variables can be found at:

or as a RTF document at:

Download of Geographic Information Systems (GIS) data layers:

Inventory completeness analysis and distribution modelling

Components C5.35: Predictive distribution modelling report and C5.38: Gap analysis in local inventories report

Taxonomists have to continue doing what they have done during the last three hundred years: to describe the variety of life organisms and their location. Although this colossal task is important by itself its relevance is higher now due to current need of reliable biodiversity data. In the attached report we review the available scientific information on the possibilities and usefulness of the compiled species distribution data for basic and applied purposes, two of the deliverables of EDIT Work Package 5.4 Geographical platform components (deliverables 5.35: Predictive distribution modelling report and 5.38: Gap analysis in local inventories report).

The main conclusions raised by this report are that:

  • (i) our current species distribution information is biased and insufficient for most taxonomic groups, and

  • (ii) modelling methods can not provide reliable and useful distribution predictions if they are based in these biased of data.

Therefore, we identify as a key priority for bioinformatics the development of tools to:

  • i) examine the degree of completeness of distributional information,

  • ii) discriminate well surveyed localities from those that do not have reliable inventories, and

  • iii) identify sets of areas where to carry out additional surveys, in order to increase the level of coverage of the environmental and spatial variation of a given region.

We encourage that these tools are made freely available and easy to use to universalize their application. A list of the available software is attached at the end of the report.

Our purpose is to use this report as a kick-off for a debate between the people interested in the utility of current taxonomic and distributional data. Such debate will be carried out in a forthcoming e-conference (EDIT deliverables 5.32 and 5.33), where the participation of taxonomists, conservationists and bioinformaticians are welcome. EDIT aims to provide resources for taxonomists and the development of these tools would be an opportunity to increase the correct use of the biological information, promoting also the participation of taxonomists in the use of their (our) own data. The e-conference is an opportunity to contrast opinions and identify key issues needed for the development of effective bioinformatic tools, such as the ones we suggest.

To download the report please click here:

Component C5.37: Application to examine inventory completeness

The analyses of spatial completeness are partialy developed in the EDIT MapViewer and can be tested at:

To perform some analysis it's supposed that the user has already:

  • 1.- selected the extent for the analysis (Iberian Peninsula is used as example)

  • 2.- submitted his file of point sample data (Jorge M. Lobo's data on Iberian Scarabaeidae are used as example)

  • 3.- selected a taxonomic level from those included in his data file (genus is used as example)

  • 4.- selected a GIS layer of surface units (UTM squares of 2500 are used as example)

  • 5.- choosed or clicked on 'perform anaysis of spatial completeness'

Then, three different maps are displayed:

  • Map of sampling effort (number of records in each square)

  • Map of taxonomic richness (number of genera in each square)

  • Map of inventory uncertainty. Inventory uncertainty in each surface unit is based not only on the number of taxa (S) and the number of records (N), but also on the relative frequency of the taxa (!FrSp = Fr1, ...., FrS). In this example, inventory uncertainty (IU) is measured as the probability of missing some of the taxa:

IU = 1 - Sp (1-(1-!FrSp)N)

The map of inventory uncertainty indicates the 'red' surface units where is necessary to carry on additional surveys in order to recover the spatial variation of the area, or where data on absences should be recorded.

A review of the available scientific information on the possibilities and usefulness of the compiled species distribution data for basic and applied purposes is available for download at

Recent reports

The recent components reports concerning inventory completeness analysis are:

M5.37 Report on data completeness assessment (gap analysis) for selected test data (ATBI)

C5.039 Report on the application of geoplatform software to map inventory

C5.110 Design document for a prototype software for data completeness assessment (gap analysis) for selected test data (e.g. ATBI and other datasets)

Minor components

Component C5.32 eConference on Geospatial Components of the Cybertaxonomy Platform

Report of the conference available at e-conference20071030.

Free GIS software links

Links to main Geographic Information Systems (GIS) free software:

The INSPIRE Directive

Directive 2007/2/EC of the European Parliament and of the Council of 14 March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE) was published in the official Journal on the 25th April 2007. The INSPIRE Directive entered into force on the 15th May 2007

You can find more information about INSPIRE at

The EU recommends and in certain cases requests that Geospatial components implemented in EU projects follow the INSPIRE guidelines. Staff members of EDIT partners are sitting in their national INSPIRE Committee and are regularly asked to comment documents and guidelines currently discussed within INSPIRE. This information received at early stage is very relevant and important for the EDIT Geospatial components. There is so an opportunity to comment at an early stage, answer specific questions of the EU in matters of Geospatial information and to give feed-back.

You can find the latest information at the following links:

Latest news from INSPIRE :

Related events :

INSPIRE library archive:

The report for component C5.158: Report on integration of Open OGC services, INSPIRE objectives and WP5 components in Geoplatform should be found at Components & Milestones page

Updated by Katja Luther over 1 year ago · 30 revisions