Open access digital data seems unusable as it is plentiful. Learning to manage them is a challenge for today’s schools.
What are these famous “ open data “so often quoted without always being understood ? It is simply the large amount of digital data produced, collected and made available by public services and therefore accessible via the Internet. If you have already consulted the weather forecast online, searched with the navigator on your phone for the nearest pharmacy on duty, or even been able to calculate the road costs of your municipality, it means that you have already used public data” to open “.
Free but hard to read
The main obstacle of these “ big open data ” it is their volume, which makes their exploitation difficult. This data is free and open to all and cannot be read by all.
We learn today in high school, to analyze and exploit them. Take the example of digital road safety data freely available on the open French public data platform data.gouv. This data is stored in huge tables in raw form and decoding and sorting it proves very difficult without initiation. However, this information offers all citizens the tools to analyze the road risk factors present in the department. As part of city policy, the Canopé de l’Aude laboratory and the Jacques Ruffié high school have joined forces to train nearly fifty second-year students in the analysis and processing of data which can contribute to their road safety.
“ We work on raw and public data Here are the road data “ explains Tatiana. “ Those who are interested in what is happening in their city or near environment and know how to operate this software, can understand what is happening and analyze it from home “ adds Luke. “ We can investigate ourselves with reliable and objective sources “ Tatiana concludes.
says Luke : “ The first question we asked ourselves was the link between the severity of the accident and the gender of the driver and we cross-referenced this data. In other words, we asked ourselves whether serious accidents are caused more often by men or women and the data speak for themselves. : men are more often responsible “.
Carla B. specifies it “These data are somehow encoded: 1 for example, means male and 2, female; the letters “LUM” indicate the degree of luminosity during the incident; other symbols define the cause of the accident… So you have to translate and order dozens of tables first”.
His neighbor, Carla T. completes: “ The goal is to answer a question that concerns us, presenting the data in the form of dynamic tables and then legible and clear graphs”.
The two mediators of digital resources from the Atelier Canopé de Carcassonne were pleasantly surprised by the growing motivation of the students for data processing and the production of data visualizations, students gaining with each session, in skill and autonomy. Their math teacher involved in this initiation summarizes the manifest contribution of this project in three words “commitment, action and pleasure”. Indeed, these young high school students demonstrated, for several hours each week, motivation and enthusiasm in manipulating these lists of obscure numbers and transforming them into clear images capable of answering a concrete question: which is the most accident-prone road in the department , what is the time of day when the most accidents occur, which type of vehicle is the most affected, etc.? “Students built their own tools in a project they made themselves, concludes. Actors of their own learning, they have obviously understood and learned over the long term to use this digital data for tangible purposes”.
These young citizens now know how to freely and usefully process common data to better respond to societal problems.