Advanced Visualizations Tools for CERN Institutional Data

Project Specification: The aim of this openlab summer student project is to provide intuitive and powerful visualisation tools for key institutional data about CERN, including budgets and contracts. The project will be done in collaboration with the Open Knowledge Foundation under the framework of CERN's open data policy regarding scientific results from LHC. The student will use the model-view-controller web development framework with Flask/HTML5/jQuery/TwitterBootstrap technologies for the user interface and SQLAlchemy ORM for database persistence. Abstract: CERN’s Open Access Policy says that “all results of its experimental and theoretical work shall be published or otherwise made generally available”. Following that, CERN has reached a collaboration agreement with the Open Knowledge Foundation in order for CERN to publish and visualize institutional data. As part of this collaboration, we will develop a module for showing this data in a graphical way in the CERN side and a tool in the Open Knowledge Foundation site for automatizing the input of data

A tool for subjective and interactive visual data exploration

We present SIDE, a tool for Subjective and Interactive Visual Data Exploration, which lets users explore high dimensional data via subjectively informative 2D data visualizations. Many existing visual analytics tools are either restricted to specific problems and domains or they aim to find visualizations that align with user’s belief about the data. In contrast, our generic tool computes data visualizations that are surprising given a user’s current understanding of the data. The user’s belief state is represented as a set of projection tiles. Hence, this user-awareness offers users an efficient way to interactively explore yet-unknown features of complex high dimensional datasets

08. Data Visualizations

This module introduces pivot tables, Plotly, and following up on FOIA data, serving as an introduction to digital data visualizations. In addition, students will be able to apply their data filtering skills learned from last module on their FOIA data

Visualizing Fantasy Fiction: Design of a Class in Digital Scholarship and Visualization, including Research, Organization and Digital Visualization, that Does Not Require Programming or IT support

This paper outlines a course to integrate digital visualizations into undergraduate research. These visualizations will include mapping and timelines of events, and the ability to hyperlink the events, characters, and story lines in a fantasy fiction story such as Lord of the Rings or A Game of Thrones. The digital scholarship will involve the methodology for collecting, organizing, and representing the data for the visualizations. The topic for the visualizations in this paper is fantasy fiction; however the methods to develop these visualizations will be applicable to many academic disciplines, including the humanities and social sciences. The paper outlines the justification for this class, the appropriate audience for this class, and the tools needed. Types of projects and homework assignments to implement the visualizations are suggested. It concludes with a syllabus outlining a typical schedule for this class

Learning Visual Importance for Graphic Designs and Data Visualizations

Knowing where people look and click on visual designs can provide clues about how the designs are perceived, and where the most important or relevant content lies. The most important content of a visual design can be used for effective summarization or to facilitate retrieval from a database. We present automated models that predict the relative importance of different elements in data visualizations and graphic designs. Our models are neural networks trained on human clicks and importance annotations on hundreds of designs. We collected a new dataset of crowdsourced importance, and analyzed the predictions of our models with respect to ground truth importance and human eye movements. We demonstrate how such predictions of importance can be used for automatic design retargeting and thumbnailing. User studies with hundreds of MTurk participants validate that, with limited post-processing, our importance-driven applications are on par with, or outperform, current state-of-the-art methods, including natural image saliency. We also provide a demonstration of how our importance predictions can be built into interactive design tools to offer immediate feedback during the design process

Create Interactive Data Visualizations

This project put data in the hands of the decision makers in a timely, secure manner. We focused on course and attrition analysis. Tableau (the business intelligence / data visualization tool) was used to create the visualizations