Silvana Philippi Camboim
There are many dimensions to the term "open". We need (and should) build environments based on open-source software, open science and open data. However, before all technology, it is the human dimension that proves to be the most challenging.
As educators, we need to turn our gaze to spreading this approach of going further than enabling the use of open tools, but creating participatory communities where a new generation of mappers is formed. Communities with access to open education focus on reducing inequalities in gender, race, and the immense poor distribution of resources on the planet. Communities that can hear and be heard, global communities. In this way, networks such as Geo for All and its Iberoamerican version, and the Youth Mappers network, bring that extra vision to academia. In this talk, I want to share with you the experiences of these two groups and how this form of active learning has affected my vision as a teacher and the relationship with my students and the community.
To be determined. More information soon.
This research presents two applications developed using Jupyter Notebook in the Google Colab, combining several Python libraries that enable an interactive environment to query, manipulate, analyse, and visualise spatial data. The first application is from an educational context within the MAPFOR project, aiming to elaborate an interactive map of the spatial distributions of teachers with higher education degrees or pedagogical complementation per vacancies in higher education courses. The Jupyter solutions were applied in MAPFOR to better communicate within the research team, mainly in the development area. The second application is a framework to analyse and visualise collaborative emotional mapping data in urban mobility, where the emotions were collected and represented through emojis. The computational notebook was applied in this emotional mapping to enable the interaction of users, without a SQL background, with spatial data stored in a database through widgets to analyse and visualise emotional spatial data. We developed these different contexts in a Jupyter Notebook to practice the FAIR principles, promote the Open Science movement, and Open Geospatial Resources. Finally, we aim to demonstrate the potential of using a mix of open geospatial technologies for generating solutions that disseminate geographic information.