DMP: Task-Oriented Guidance for Information Visualization Recommendation
Creators: name: Borde, Thibault
Publisher: name: Zenodo
Year: 2024
Subjects: subject: Data Management Plan
subject: Data Visualization

description: This deliverable is the first version of a Data Management Plan (DMP) for a research paper on Task-Oriented Guidance for Information Visualization Recommendation. The aim of this document is to outline the strategies for managing, storing, sharing, and preserving both the data used and the data generated.

 
description: Information Visualization is a field in computer sciences that is mainly focused on how to visually map abstract data. Information Visualization are visual representations of the semantics, or meaning, of information. In contrast to scientific visualization, which deals with physically-based data, information visualization typically deals with nonnumeric, nonspatial, and high-dimensional data.

In many application domains, data involves a large number of attributes and categories. In industrial manufacturing, for example, numerous quality indicators are measured for each produced item along with process information such as the order ID, the used machinery, and much more. For such complex data, manually searching for visualizations that reveal interesting patterns such as correlations, trends, and outliers may become very tedious and time-consuming.

The goal of this research is to extend well known views such as scatterplots, histograms, or categorical views by integrating recommendations on demand of view parameterizations which may be worth looking at. Typical examples could include “list all scatterplots showing correlations between data attributes for any data subset”, or “rank all time-series plots by the amount of showing a clear trend over the past weeks”.

In order to experiment on Task-Oriented Guidance for Information Visualization Recommendation. We will use complex datasets from different fields to experiment in different use-cases. The datasets used are the following : 



Jacopo Vitale. (2021). Single and combined effect of acute sleep restriction and mental fatigue on basketball free-throw performance [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5742821

re3data.org: Maddison Project; editing status 2024-07-03; re3data.org - Registry of Research Data Repositories. http://doi.org/10.17616/R3TH25 last accessed: 2024-10-25 

Jan C. Minx, William F. Lamb, Robbie M. Andrew, Josep G. Canadell, Monica Crippa, Niklas Döbbeling, Piers Forster, Diego Guizzardi, Jos Olivier, Julia Pongratz, Andy Reisinger, Matthew Rigby, Glen Peters, Marielle Saunois, Steven J. Smith, Efisio Solazzo, & Hanqin Tian. (2022). A comprehensive and synthetic dataset for global, regional and national greenhouse gas emissions by sector 1970-2018 with an extension to 2019 [Data set]. Zenodo.https://doi.org/10.5281/zenodo.6483002


The datasets will be used to produce interactive visualizations using the JavaScript D3 library as well as a recommendation system for such visualizations. A React app will be implemented and hosted on a public GitHub repository. Its latest version will also be hosted on a GitHub Pages to allow the public to test the implementation. 

The development of this app as well as the process behind it, are the basis of a research paper that will also be hosted in the GitHub repository as well as in the TU Wien Research Data base once it is published.