Deployment
COLLABORATIVE CORRELATION DATA ANALYSIS
Video tool
Type of tool: Research
Phase: Deployment
DATA ANALYSIS PLATFORM
Make data analysis accessible to participants
The Challenge
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?
The Tool
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.
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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
What
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.
Why
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.
How
Make a plan
First, a plan had to be created on what we wanted to achieve and how to achieve it. An important aspect of this was that the app had to be user-centred, and understandable to participants with no data analytics knowledge. The technical and ethical aspects had to be considered as well – what language works best, where it will be hosted, and how the data will be secured (as it contains a lot of personal information).
Data treatment
First, all of the data from different sources had to be merged, cleaned, and, if needed, aggregated or transformed.
Basic platform creation
The platform was then created using the R Shiny environment. In the first phase, it was created the “skeleton” of the platform, where only basic visualisations and functions were included. An important point is the design and the UX experience. It is important to take care of the aesthetically pleasing and removed features and graphical elements that were not essential. This was done to further engage the participants while using the platform and not confuse them with unnecessary items.
Help info added
A challenge is to make the functional elements of the platform and all the charts helpful and comprehensible. This was done so anyone can use it by finding helpful information right next to the issue at hand (and not on a separate page). Help information included was how to use the platform, descriptions of variables, how to interpret the plots...
Tests tests and more tests
Sometimes developers overlook some issues or do not pay enough attention to how other people perceive things – to correct this kind of shortcomings we invited a few volunteers to a focus group in order to give us a review of the application. After their feedback, we made the necessary changes to the app.
To make sure that everyone can use the app correctly, a workshop was also organised to present the platform and its features to the participants.
Launch and feedback
Lastly, the application was launched and shared with all participants. With their consent, their activity on the platform was monitored and some of the participants were interviewed to get their thoughts about the usefulness, possible improvements, and further implementation of the platform.