READ ME File For 'Dataset for: Automatically evaluating the mobile web accessibility of Higher Education electronic texts for print impairments' Dataset DOI: 10.5258/SOTON/D1064 ReadMe Author: NEIL ROGERS, University of Southampton orcid.org/0000-0001-6159-9342 This dataset supports the thesis entitled: Automatically evaluating the mobile web accessibility of Higher Education electronic texts for print impairments AWARDED BY: Univeristy of Southampton DATE OF AWARD: 2019 ........................................................................ DESCRIPTIONS OF THE OPEN DATA SETS: CoreMappedAccessibilitySettings.xlsx: Device accessibility settings were mapped across the Android (Nexus 5), iPhone 6 (iOS 9.1) and the Nokia Lumia 1520 (Windows Phones 8.1). User Agent (UA) accessibility settings were mapped across 12 ereader applications (shortlisted to 10), three cross platform mobile browsers and three online readers. The majority of the ereader applications were deliberately chosen because they were compatible with all three of the above devices. The cross platform browsers included Chrome, Firefox and Opera whereas the online readers included Readium, Bureau Van Dijk and the Firefox PDF Cloud Viewer. The Google Drive PDF Viewer was also included and at the time of writing did not have any accessibility settings available. This dataset contains: the mapping between smartphone device and user agent accessibility features. Date of data collection: 2016 Licence: CC BY ........................................................................ ExpertReview1BackgroundMapping.xlsx: The comments made by individual experts in Expert Review One were mapped against the published research findings that related to mobile device control categories found in the background chapter of the thesis. The annonymised demographics data was used in order to determine which expert the comments related to. This dataset contains: anonymised data collected during Expert Review One that was mapped to control categories. Date of data collection: 2016 Licence: CC BY ........................................................................ ExpertReview1SurveyResults.xlsx: ERGO/FPSE/18699 This data was collected from each individual hand written response to a survey that collected both demographic and comments from individual expert participants. Each occurrence of an agreement between the individual expert particpants that occurred was recorded and analysed. Questions that were unanswered were also recorded. This dataset contains: the entire results and analysis for each individual expert including qualitative statements, demographic data and thematic coding of the statements for Expert Review One. Date of data collection: 2016 Licence: CC BY ........................................................................ ExpertReview2BackgroundMapping.xlsx: ERGO/FPSE/30291 The data taken from the Expert Review Two survey questions was streamlined and then mapped to the background published research findings. This inlcuded annoymising the statements by mapping each answer or comment to an expert particpant ID. This dataset contains: the mapping between the anonymised comments made by each individual expert participant and how they relate to the background published research findings. Date of data collection: 2017 Licence: CC BY ........................................................................ ExpertReview2SurveyResults.xlsx: ERGO/FPSE/30291 Each individual expert particpant was issued with a unique ID with both their demographic and expertise data. The outcome based on a five point Likert item was recorded for two questions in the survey, namely Q3.10 and Q3.12. Q3.10 related to the HEI library web portal prototype and walkthrough whereas Q3.12 related to the academic publishers website. This dataset contains: the quantitative analysis for the Expert Review Two results for two specific questions on the online survey. Date of data collection: 2017 Licence: CC BY ........................................................................ iSurveyID24151DATA.csv: ERGO/FPSE/30291 Each individual particpant was allocated a unique and anonymised particpant ID by iSurvey for Expert Review Two. The official tool, referred to as iSurvey, provides date a time stamps, including IP addresses. It also provides a complete breakdown of what questionnaires were answered and how long the particpant took to answer the survey. Both demographic, expertise and expert comments were gathered for each individual particpant. This dataset contains: The raw data taken from the University of Southampton official iSurvey for Expert Review Two. The reason for this is that the surveys are removed from iSurvey as per university policy. Date of data collection: 2017 Licence: CC BY ........................................................................ ReducingFeatures2CoreAccessibilitySettings.xlsx: The data was collected by undertaking physical testing of devices, ereader applications, mobile browsers and online readers. This provided a means to rank those feature that were more predominant on the Android device. This information was then used when undertaking the core accessibility features across the Android, iOS and Windows mobile devices. This was mapped to both WCAG 2.0 and UAAG 2.0 success criteria and print impairments. This also included a breakdown of potential tasks and accessibility features required by an academic or student user with a print impairment who is searching for, finding, downloading, navigating and reading an electronic text. This dataset contains: a breakdown of how the occurrence of accessibility features was determined across the Android mobile device. Date of data collection: 2016 Licence: CC BY ........................................................................ SelectingUserAgentsFinal.xlsx: The shortlist of ereader applications was determined by an exhaustive search of Google Play, iTunes and the Microsoft Store at the time of data collection. This also included an early search for online readers, at the time only Readium had been found. This dataset contains: a breakdown of how ereader applications were shortlisted based on the eformats and the mobile device OS they supported. Date of data collection: 2016 Licence: CC BY ........................................................................ ThesisBackgroundSearches.xlsx: Four sets of search terms were used with all possible permuations accounted for and duplicates were removed. A master list of search terms was created that was then used for two initial searches. These were then narrowed to two final searches that were undertaken across 11 academic databases within the date range 2010-2018. Miscellaneous searches were also undertaken. This dataset contains: the entire breakdown of search terms and searches undertaken for published research findings across 11 academic databases, including Google Scholar. Date of data collection: 2018 Licence: CC BY ........................................................................ Date that this file was created: September, 2019.