Events


Datathon [23-26 June 2021] (Virtual)

The target of following challenges is to analyze the NYC Yellow Taxi Trip dataset (TAXI) and provide novel interactive visualization methods and visual analytics for the following analytical tasks. For more info see: Datathon home page.

Challenge 1: Visual Analytics for Traffic Prediction

Note. The data prediction and visualization are considered to be used in interactive applications, so real-time response is required. The focus of this task is on novel visualization methods that will allow users to use\run well-known prediction algorithms (e.g., regression) and interact with the predicted results.


Challenge 2: Visual Analytics for Dirty Mobility Data

Taxi and Other Mobility companies aggregate data from various sources, ending in having dirty\duplicate entries related to trips. A common task in such cases involves an analyst which wishes to analyze the dataset w.r.t. data quality. The use of visual techniques may reveal information (e.g., correlations, patterns) which are not easily captured by traditional (non-visual) methods. In our case, visually analyze "information" related to duplicate entries, will assist the analyst to recognize data patterns, values, or specific attributes, where duplicates records appear. Beyond the insights related to data quality, using these insights will enable the analyst to improve the effectiveness of their duplication techniques. Note. The duplicates records will be given to the participants beforehand.
Note. The data prediction and visualization are considered to be used in interactive applications, so real-time response is required.