DATA ANALYSIS PLATFORM
Make data analysis accessible to participants
After the environmental issues and health data collection campaign, it is necessary to have a strategy for the data analysis. Even if this data was gathered in a participatory way, sometimes it is not easy to involve participants in this stage because its technical barriers with typical data analysis software (e.g. R analytics) or because participants don’t feel prepared for doing it.
How can we present data gathered by each individual and enable participants to analyse the data themselves, even though they have different levels of computer skills?
Creating a user-friendly platform for analysis and data overview by participants with different capacities and backgrounds enables to open up this stage. The opportunity for citizens to analyse in a simpler way their own data empowers them and can give researchers new insights about the data or new variables to look for it.
Download the toolbox
We share with you some resources that can be useful to carry out this activity.
Discover the tool in action!
Read the case study and understand how this tool has been used in a real citizen science project.
CitieS-Health Data Analysis Platform
CitieS-Health Ljubljana Pilot
In the Ljubljana CitieS-Health pilot, the participants gathered a lot of data from different sources: noise level, location (GPS), mood, cognitive abilities, sleep quality, location characteristics, heart rate, and stress levels… This gave the participants the freedom to gain knowledge not only on the effects of noise but also on the health and living environment characteristics that they were interested in. However, this posed a challenge: How to deliver this data to them so they can get meaningful insights? A traditional PDF-style report would be too long and complex, and we would risk leaving out connections between the data that each individual was interested in. We chose to build an online platform, where individuals could analyse the data by themselves, without having the technical knowledge in Excel, BI, R, or other similar programs. After signing in, their data would be loaded automatically, and chart templates created for them. All they would need to do is to choose what type of chart they prefer and which variables they want to compare. Along with this they could review their activity, inspect the data in tables, and view their measurements on a map. All this would be accompanied by explanations of what different variables mean, how to use them in charts, and how to interpret them. Apart from the benefit to the participants, the researchers would gain greater insight into what issues the participants care more about and get a different view of the data than they have themselves.
To give participants access to their own data.
To give each participant the option to analyse the data by himself.
To eliminate the need for technical knowledge in order to analyse the data.
To give researchers even greater insight into what issues are more important to the participants.