Deciding what data to collect implies that you have identified through a gap analysis what data and knowledge you need and what already exists about the questions you are trying to address (more here on how to find out what exists already).
For each issue (also called ‘monitoring theme’), you need to specify the following aspects:
- What needs to be observed,
- Where does it need to be observed,
- How often does it need to be observed,
- By whom, and
You can answer these questions by creating the following table that actually defines the data model (i.e., the form of each observation). This will help you ensure alignment of your approach and remain focused. It also allows you to keep an overview if your Citizen Observatory needs to address more than one monitoring theme.
In order to define the type of data your Citizen Observatory needs to generate, you should think about the question you are trying to answer.
The parameter to be observed defines what should be collected and can be a list numeric variable of names to be captured (with their units of measure, e.g. a temperature in degrees), pictures and annotations describing what is being observed.
Scientists can advise you on where the data needs to be collected (in a limited or in a vast zone, predetermined or random, in the field or from your computer at home) and how often (e.g. whether repeated observations are needed for the same sample).
You should take into account the type of information to collect, the sensors and technologies required, and in what level of detail and precision volunteers should collect that data (i.e., to comply with existing taxonomies), while also keeping in mind the implications in terms of personal data collected, the quality of the data and the provision of adequate metadata. The methods that should be employed for the definition of the above mentioned elements depend on the respective application domain and may differ from project to project.
When defining the data collection scheme it is essential to adhere to standardised definitions provided (OGC, INSPIRE, Public Participation in Scientific Research, etc.) in order to facilitate interoperability and combined use with other data sources.
The data collection scheme can inform the metadata describing the data set resulting from your data collections. Deciding on some metadata elements in advance can help you define the more technical aspects of your data collection scheme, such as the desired resolution of the data collected and thus the coordinate reference system used. See more on metadata for managing your data here and for sharing your data here.
The process of creating a data collection scheme can help a community to discuss what should be measured, when, where, how and by whom. Having a map of the geographic area where you would like to collect data allows everyone to pinpoint the location where they can capture data. Another useful tool is a shared calendar, so that everyone can collaborate on the best dates and times for capturing the data.