Extracting and visualizing a new classification system for Colombia's National Administrative Department of Statistics. A visual analytics framework case study
January 29, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Pierre Raimbaud, Jaime Camilo Espitia Castillo, John Guerra-Gomez
arXiv ID
2401.15994
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.IT
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
In a world filled with data, it is expected for a nation to take decisions informed by data. However, countries need to first collect and publish such data in a way meaningful for both citizens and policy makers. A good thematic classification could be instrumental in helping users navigate and find the right resources on a rich data repository as the one collected by Colombia's National Administrative Department of Statistics (DANE). The Visual Analytics Framework is a methodology for conducting visual analysis developed by T. Munzner et al. [T. Munzner, Visualization Analysis and Design, A K Peters Visualization Series, 1, 2014] that could help with this task. This paper presents a case study applying such framework conducted to help the DANE better visualize their data repository, and present a more understandable classification of it. It describes three main analysis tasks identified, the proposed solutions and the collection of insights generated from them.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted