This tool allows to analyse the biological data from IOC Alien Species Database and the Instituto Español de
Oceanografía (IEO) oceanographic surveys stored in the SIRENO database. It is possible to calculate biological
indices
such as abundance. In addition, it facilitates to compare this information with the available data in OBIS and FAO. Also is possible to link this biological information with oceanographic information
provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at http://www.esrl.noaa.gov/psd/
When the user launches this tool, the "Select Samples" panel appears on the map.
This panel contains several selectors from which the user can choose the information that is loaded into the
map. The data source can be selected using the Source selector. The options include (i) the IOC Alien Species
database, (ii) the IEO surveys, which selects samples from the Instituto Español de Oceanografía region, (iii)
the OBIS option, which provides access to the open-source data available on the OBIS website, (iv) the FAO
species distribution selector, which allows to load the vectorial distribution information available through the
FAO's published WMS and (v) the IOC Alien Species-IEO-OBIS-FAO option enables visualization of all datasets.
Once a dataset is selected, specific selectors of the corresponding dataset become available.
In the IEO section, inside the Select Sample panel, two selectors allow to filter by survey and by species.
Clicking the 'View Result' button sends an Ajax request to the server, and the geoprocessing service returns the
data in JSON format. This response is added to the map as a point layer, which is then centred and zoomed. In
the following case, the survey with the acronym IBN SINA8104 is selected. If the Species selector is left blank,
all available survey samples are selected as default. Similarly, if no survey is selected from the Survey
selector, all surveys are added to the filter.
At the same time, the symbol panel appears, allowing you to select a style for the layer that has been loaded. The symbology tool's use will be described later.
If the biological index is available, a graph with that information is automatically added below the map. The user can make new selections, and a new graph appears below the map, allowing them to compare the results. For example, it is possible to compare one survey with another.
When the user hovers over an entity, a popup window appears that displays the metadata information for the selected sample.
The 'By Polygon' button allows to the user draw a polygon over the map. Click with the left mouse button to add
vertices and double click to finish. Once time finish the polygon the geometry is send to the corresponding
geoprocessing service as a spatial filter. The result of this query are the entities that are inside of the
polygon and satisfying the value requirements selected by the user.
The 'By Buffer' button allows to generate an area as spatial filter. When the user clicks over this button the
Geodesic Panel is displayed, this panel was described in Auxiliary Tools section. The user can generate an
influence
area and the resulting polygon is used as a spatial filter in the corresponding geoprocessing service. The
result of this service is returned as a POST Ajax call in JSON format. This result is loaded as a point layer in
the map.
In the OBIS section inside the Select Sample panel, the user find two selectors that allow filter by family and
by species.
As in the previous case, using the Select, By Polygon, and By Buffer buttons, the app sends the filter parameters (spatial or attribute) to the geoprocessing service, which returns the results in JSON format. The result is loaded into the map as a point layer. Due to the large number of entities returned, this layer is typically clustered, and only the first 10,000 records are displayed for operational reasons.
When user click over an entity a popup is displayed and the metadata of this sample is shown.
In the FAO section, the user can select the species to show the distribution area for the species selected.
This analytic tool allows to drag and drop CSV files on the map. To load the user's data into the app, the information must be stored in a text file with a CSV format CSV (Coma Separated Value). The file's header corresponds to the names of each column. This file must contain two fields, one called lon and the other lat. In both fields, the position is stored. The lon field corresponds to longitude and the lat field to latitude, both in the WGS84 (EPGS:4326) reference system and in decimal degrees with the comma as a decimal separator. Only these fields are required; the remainder of the fields correspond to the data that the user wishes to analyze.
Here is an example about the csv format ready to be uploaded by the application.
To load the file into the tool, simply drag and drop it over the map, and a layer of points with the CSV file's sample position is displayed.
First, a panel allows to load oceanographic data in the CSV table (Source: NOAA)
Then, the symbol panel appears, allowing you to select the appropriate symbology.
The Category selector allows access to a variety of symbols. It is possible to select the color once a symbol has been selected (by clicking over it).
Graduated symbols are used to show a quantitative difference between mapped features by varying the size of
symbols. Data is classified into ranges that are each then assigned a symbol size to represent the range. For
instance, if your classification scheme has five classes, five different symbol sizes are assigned. The color of
the symbols stays the same.
Symbol size is an effective way to represent differences in magnitude of a phenomenon because larger symbols are
naturally associated with meaning a greater amount of something. Using graduated symbols gives you a good degree
of control over the size of each symbol, because they are not related directly to data values as they are with
proportional symbols. This means you can design a set of symbols that have sufficient variation in the size that
represents each class of data to make them distinguishable from one another.
In the value selector the field to symbolize is selected. In the classes input the user can write the number of
classes to distinguish. With the min value and max value, the user can select the min and max value in pixels of
the symbol
Proportional symbology is used to show relative differences in quantities among features. Proportional symbology
is like graduated symbols symbology in that both draw symbols sized relative to the magnitude of a feature
attribute. Unlike graduated symbols, which divide features into distinct classes, proportional symbols represent quantitative values as a series of unclassified symbols, each sized according to a specific value.
In the value selector the field to symbolize is selected. With the min value and max value, the user can select
the min and max value in pixels of the symbol.
The Biological Data tool also includes the Geodesic, Print Map, and Export CSV tools, as described on the home page.