Summary Dataset Information This dataset contains responses of voters who had verified their vote using Verify My Vote (VMV) system after participating in in Royal College of Nursing and College of Podiatrists elections in August and October 2019 respectively. The data is used in research paper “Verify My Vote: Voter Experience” by Mohammed Alsadi and Steve Schneider and published in the proceedings of E-VOTE-ID 2020. Dataset Characteristics Multivariate Number of Instances 196 Area E-voting Attribute Characteristics Categorical Number of Attributes 17 Missing Values Yes Questionnaire Information The questionnaire consisted of fourteen 6-point Likert scale statements about the VMV system, two categorical questions representing Gender and Age range and one open-ended question asking voters about their feedback or any further comments. The questionnaire statements are: I was pleased with the opportunity to check my vote. I don't see the point of checking my vote. It was easy to check my vote. If given the choice I would prefer to vote on paper rather than over the Internet. I wouldn't usually bother with checking my vote. Checking my vote gave me confidence that the election result is correct. All elections should offer the opportunity to vote electronically. It was difficult to check my vote. This checking system keeps my vote private. The vote checking system is quite complicated. I would check my vote next time if I could. With this system other people cannot tell which vote is mine. I think everyone should check their vote if the facility is available. With this system I can tell how a particular person has voted. Please provide any further comments you may have. For example, what do you think of the vote checking system? Do you have any suggestions for how it could be improved? How easy was it to use? Any other comments? What is your gender? (1 = Female; 2 = Male; 3 = Other; 4 = Prefer not to say) What is your age range? (1 = under 25; 2 = 25-34; 3 = 35-44; 4 = 45-54; 5 = 55-64; 6 = 65 or over; 7 = Prefer not to say) The agreement levels used in Likert scale are: 1 : Strongly Agree 2 : Agree 3 : Weakly Agree 4 : Weakly Disagree 5 : Disagree 6 : Strongly Disagree

This research was funded by EPSRC through the VOLT project EP/P031811/1, with support for development of VMV and integration with the CES system through the Surrey Impact Acceleration Account EP/R511791/1.