a Postgres cache database, you must be connected with a server running
12.0 or above). To connect to a server, click on the
button and enter the connection
parameters. If no cache database has been created so far you
get a message that no database is available and will be connected to the default
Click on the button to create a new cache database (see below). You will be asked for the name of the database and a short description.
After the database was created, you have to update the database to the current version. Click on the Update button to open a window listing all needed scripts. To run these scripts just click on the Start update button. After the update the database is ready to take your data. Subsequent updates may become necessary with new versions of the database. For an introduction see a short tutorial . To remove the current database from the server, just click on the button.
In the image on the right you see a screenshot from the tool pgAdmin III. You may use this tool to inspect your data and administrate the database independent from DiversityCollection. Please keep in mind, that any changes you insert on this level may disable your database from being used by DiversityCollection as a sink for your cache data. The data are organized in schemata, with public as the default schema. Here you find functions for marking the database as a module of the Diversity Workbench and the version of the database. The function highresolutionimagepath translates local image paths into paths for high resolution images. To use this function it must be adapted to your local server settings. The tables in this schema are TaxonSynonymy where the data derived from DiversityTaxonNames are stored and ScientificTerm where the data derived from DiversityScientificTerms are stored. For every project a separate schema is created (here Project_BFLsorbusmmcoll). The project schemata contain 2 functions for the ID of the project and the version. The data are stored in the tables while the packages in their greater part are realized as views and functions extracting and converting the data from the tables according to their requirements.