The most important core-feature in SPOTTERON is that we not only build your apps, but also update and maintain them during the whole runtime. Especially in the ecosystem of mobile technology it is very important, to regulary patch and improve your project-apps to provide stability and compatiblity for your users. Furthermore, we also introduce new features and extensions for the Citizen Scientists and also the project administrators on a regular basis - because SPOTTERON is all about working together to build the best Citizen Science tools for the future.
In collaboration we specify a custom color scheme. The primary color supports the key elements and indicate interaction, while the secondary color highlights important areas or information structure. Supplementary colors are calculated by a 50% opacity of the main and secondary colors and are used as structre elements and in visual ordering.
Each SPOTTERON application features the project logo in the header area as a primary element. Further logos and links can be placed in the bottom area of the app menu for e.g. project partners or sponsors.
Every SPOTTERON app can provide its own data set for spots and contents for the users. Besides the standard fields like spot name, description and photo we have implemented 3 levels of definition.
The category tree can be used as a defined structure for entries. It features unlimited depth and can be structures individually.
Example: Classification (Mammal > Mustelidae > Badger)
The spot attributes specify spot traits within the add spot form, which can be individually set to be required or optional . For each attribut field unlimited options are possible.
Example: How are you travelling? (walking, by bike, by motorbike, by car, by truck, other)
The predefined tags are used as a more freely set of information in the apps. While attributes just allow one option per selection field, tags can be selected freely by the users. In addition, tags can be filtered in the filter menu for viewing just spots with one or more specific tags.
Example: classification unsure (Yes / No).