Objectives (20%) The visualisation failed to meet the design objectives: Form vs. function, justification, accessibility and no deception. The visualisation had some issues with the design objectives: Form vs. function, justification, accessibility and no deception. The visualisation met most of the design objectives: Form vs. function, justification, accessibility and no deception. Form and function were well balanced, decisions were justified, the design was intuitive and accessible, and did not deceive. Video (20%) No video/unacceptable video quality. Video presentation was included, but there was room for improvement. A good quality video presentation was included. Only minor improvements were needed. A high quality video presentation was included. There was little that could be faulted.

Options and Method (20%) The visualisation demonstrated inappropriate choices in data representation, presentation and method. The visualisation did not demonstrate the best choices in data representation, presentation and method. Better choices and methods could be used. The visualisation demonstrated good choices in data representation, presentation and method. Only minor adjustments were needed or other alternate methods could be explored. The visualisation demonstrated best practice in data representation, presentation and method. Insight (20%) The visualisation did not demonstrate insight into the data. The visualisation demonstrated some insight into the data. The visualisation demonstrated a high degree of insight into the data. The visualisation demonstrated original and important insight into the data.

Marking Rubric Please refer to Andy Kirk's Visual Design Process described in Module 1. Criteria Not acceptable (0) Needs Improvement (2) Meets Expectation (3) Exemplar (4) Purpose and Focus (20%) There was no apparent purpose to the data visualisation. The visualisation lacked an apparent focus. The purpose of the data visualisation was not entirely clear. The focus of the visualisation could be improved by drawing better attention to key features or looking at the data from another angle. The purpose of the data visualisation was clear. The focus of the visualisation drew attention to key features and provided insight, however, the focus could be narrowed or broadened to improve insight. The purpose of the data visualisation was obvious. The focus of the data visualisation was very effective in conveying insight into the data.

Late Submissions Late submissions will be marked in accordance with the late submission policy. Please see the course information sheet. Collaboration versus Collusion and Plagiarism You are permitted to discuss and collaborate on the assignment with your classmates. However, the assignment must be an individual effort. Assignments will be submitted through Turnitin, so if you've copied code and data from a fellow classmate, it will be detected. It is your responsibility to ensure you do not copy or do not allow another classmate to copy your work. If plagiarism is detected, both the copier and the student copied from will be responsible. It is good practice to never share assignment files with other students. You should ensure you understand your responsibilities by reading the RMIT University website on academic integrity. Ignorance is no excuse.