We're sorry but this page doesn't work properly without JavaScript enabled. Please enable it to continue.
Feedback

Using Jupyter Notebooks for viewing and analyzing geospatial data: Two examples for emotional maps and educational data

Formal Metadata

Title
Using Jupyter Notebooks for viewing and analyzing geospatial data: Two examples for emotional maps and educational data
Title of Series
Number of Parts
237
Author
Contributors
License
CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
Identifiers
Publisher
Release Date
Language

Content Metadata

Subject Area
Genre
Abstract
Using Jupyter Notebooks for viewing and analyzing geospatial data: Two examples for emotional maps and educational data 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. Authors and Affiliations – Gabriele Silveira Camara Federal University of Parana, Brasil. Graduate Program in Geodetic Science. Silvana Philippi Camboim Federal University of Parana, Brasil. Graduate Program in Geodetic Science. João Vitor Meza Bravo Federal University of Uberlandia, Brasil. Institute of Geography, Graduate Program in Geography and Graduate Program in Agriculture and Geospatial Information. Requirements for the Attendees – https://github.com/GabrieleCamara/emotional_maps/blob/master/visualizer_emotional_maps.ipynb https://github.com/GabrieleCamara/Mapfor/blob/main/maps_mapfor.ipynb Track – Academic Topic – Open and Reproducible Science Level – 2 - Basic. General basic knowledge is required. Language of the Presentation – English