What is IMAGINE doing?
Visual Analytics

John Alexis Guerra Gómez
@duto_guerra


http://johnguerra.co/slides/whatIsImagineDoing

What is Visual Analytics?

How to make sense of data?

  • Statistical Analysis
  • Machine Learning and Artificial Intelligence
  • Visual Analytics (and data analytics)

Data Mining/Machine Learning

Information Visualization

Infoviz + Algorithms

Photo Visualization

PhotoTreemap

How can we represent a set of photos with numerical data?

Luis Mesa
PhotoTreemap

PhotoRing

How can we explore large repositories of photos?

David Mauricio Delgado

Navigation List

How can we navigate long lists of items

Andrés Laiton
Navigation List

Large DataViz

Navio

Shipyard

Interface for configuring and testing Navio

Juan Guillermo Murillo

TADAVA

Scaling up Navio/Shipyard to large datasets

Juan Camilo Ortiz

TADAVA Architecture

TADAVA Architecture

Nautilus

Can we use Navio with Voyager?

Lady Pinzón
Nautilus

Stand alone Shipyard

Can we use more resources for Shipyard running locally?

Felipe Sabogal
Standalone shipyard

InfoViz

BackViz

Framework for automated testing of DataVis

Nychol
BackViz_visual_Analytics
BackViz_compared_to_visual_regression_testing
BackViz_barchart
BackViz_Result

BioCicle

Help Biologist comparing sequential data results

Meili VanegasFabio Lopez
BioCicle_contributions

BioCicle

DCP

Compare two cohorts with respect to a temporal event

Juan Sebastián Cardona
DCP

Concejo Abierto

App to bring access to Bogota's Council data

Esteban Dalel
Concejo Abierto

Drug Market Share

Can we estimate the size of the illegal drugs' market from news articles

Nicolás Chaves
Drug Market

Colombian Senate

How do Colombian Senators vote?

Juan Jose Castro

Accessibility

Magica11y

How can we make website more accessible for the blind?

Antonio de la Vega

Magica11y

Tactile Graphics Finder

How can we help finding images for the blind?

Felipe Martínez

Tactiled

Can we run the model on the browser

Carlos GonzalezRicardo Gonzalez

Thank you!

Why should we visualize

Traditional

  • Query for known patterns
  • Display results using traditional techniques

Pros:
  • Many solutions
  • Easier to implement

Cons:
  • Can’t search for the unexpected

Data Mining/ML

  • Based on statistics
  • Black box approach
  • Output outliers and correlations
  • Human out of the loop

Pros:
  • Scalable

Cons:
  • Analysts have to make sense of the results
  • Makes assumptions on the data

InfoVis

  • Visual Interactive Interfaces
  • Human in the loop

Pros:
  • Visual bandwidth is enormous
  • Experts decided what to search for
  • Identify unknown patterns and errors in the data

Cons
  • Scalability can be an issue

Why should we visualize?

Anscombe's quartet

I II III IV
x y x y x y x y
10.0 8.04 10.0 9.14 10.0 7.46 8.0 6.58
8.0 6.95 8.0 8.14 8.0 6.77 8.0 5.76
13.0 7.58 13.0 8.74 13.0 12.74 8.0 7.71
9.0 8.81 9.0 8.77 9.0 7.11 8.0 8.84
11.0 8.33 11.0 9.26 11.0 7.81 8.0 8.47
14.0 9.96 14.0 8.10 14.0 8.84 8.0 7.04
6.0 7.24 6.0 6.13 6.0 6.08 8.0 5.25
4.0 4.26 4.0 3.10 4.0 5.39 19.0 12.50
12.0 10.84 12.0 9.13 12.0 8.15 8.0 5.56
7.0 4.82 7.0 7.26 7.0 6.42 8.0 7.91
5.0 5.68 5.0 4.74 5.0 5.73 8.0 6.89
Property Value
Mean of x 9
Variance of x 11
Mean of y 7.50
Variance of y 4.125
Correlation between x and y 0.816
Linear regression y = 3.00 + 0.500x
Coefficient of determination of the linear regression 0.67

Anscombe's visualized

More examples same stats

https://dabblingwithdata.wordpress.com/2017/05/03/the-datasaurus-a-monstrous-anscombe-for-the-21st-century/

Datasaurus!

https://dabblingwithdata.wordpress.com/2017/05/03/the-datasaurus-a-monstrous-anscombe-for-the-21st-century/

In Infovis we look for Insights

  • Deep understanding
  • Meaningful
  • Non obvious
  • Actionable

How do we do it?

What do we use?