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'ChatGPT & Me' Student Padlet Data With Reactions (2023)
Dataset
Drumm, L., Illingworth, S., Graham, C., Calabrese, P., Taylor, S., Dencer-Brown, I., & van Knippenberg, I. (2023). 'ChatGPT & Me' Student Padlet Data With Reactions. [Dataset]. https://doi.org/10.17869/enu.2023.3200728

These data are from a project which aimed to collect and analyse student attitudes to artificial intelligence (AI) and their own learning and assessment while they are studying with Edinburgh Napier University. AI tools such as ChatGPT make it easier... Read More about 'ChatGPT & Me' Student Padlet Data With Reactions.

Rawls in the mangrove: perceptions of justice in nature-based solutions projects (Dataset) (2023)
Dataset
Huxham, M. (2023). Rawls in the mangrove: perceptions of justice in nature-based solutions projects (Dataset). [Dataset]. https://doi.org/10.17869/ENU.2023.3090209

1. Adapting to and mitigating against climate change requires the protection and expansion of natural carbon sinks, especially ecosystems with exceptional carbon density such as mangrove forests (an example of ‘blue carbon’). Projects that do this ar... Read More about Rawls in the mangrove: perceptions of justice in nature-based solutions projects (Dataset).

Using Worker Position Data for Human-Driven Decision Support in Labour-intensive Manufacturing (2023)
Dataset
Aslan, A., El-Raoui, H., Hanson, J., Vasantha, G., Quigley, J., Corney, J., & Sherlock, A. (2023). Using Worker Position Data for Human-Driven Decision Support in Labour-intensive Manufacturing. [Dataset]. https://doi.org/10.17869/enu.2023.3100035

This data contains the worker position datasets (including the event logs) and the source codes of the discrete event simulation that are used in the research article titled "Using Worker Position Data for Human-Driven Decision Support in Labour-inte... Read More about Using Worker Position Data for Human-Driven Decision Support in Labour-intensive Manufacturing.

Where to fish in the forest? Tree characteristics and contiguous seagrass features predict mangrove forest quality for fishes and crustaceans (Dataset) (2023)
Dataset
Wanjiru, C., Nagelkerken, I., Rueckert, S., Harcourt, W., & Huxham, M. (2023). Where to fish in the forest? Tree characteristics and contiguous seagrass features predict mangrove forest quality for fishes and crustaceans (Dataset). [Dataset]. https://doi.org/10.17869/enu.2023.3069847

1) Mangroves often support rich fish and crustacean communities, although faunal abundance and diversity show strong spatio-temporal variability. Consistent patterns in mangrove animal communities might be dictated by forest characteristics, by seasc... Read More about Where to fish in the forest? Tree characteristics and contiguous seagrass features predict mangrove forest quality for fishes and crustaceans (Dataset).

SAtour: Sentiment analysis of Saudi Arabia Tourism Tweets (2023)
Dataset
Basabain, S. (2023). SAtour: Sentiment analysis of Saudi Arabia Tourism Tweets. [Dataset]. https://doi.org/10.17869/enu.2023.3036363

SAtour is a new dataset of Arabic tweets in the tourism domain for Arabic SA. The total corpus size is 2293 tweets, after manual annotation these tweets were labeled as either positive, negative, or neutral. We present the detailed process of collect... Read More about SAtour: Sentiment analysis of Saudi Arabia Tourism Tweets.

Transfer Learning-based Automatic Sentiment Annotation of a Twitter-based Arabic Mental Illness (AMI) Dataset (2023)
Dataset
Diwali, A. (2023). Transfer Learning-based Automatic Sentiment Annotation of a Twitter-based Arabic Mental Illness (AMI) Dataset. [Dataset]. https://doi.org/10.17869/enu.2023.3027591

[Abstract withheld.]

Lead time prediction with the Bosch production line dataset (2022)
Dataset
Aslan, A., Vasantha, G., El-Raoui, H., Quigley, J., Hanson, J., Corney, J., & Sherlock, A. Lead time prediction with the Bosch production line dataset. [Dataset]

Jisc OA Annual Report 2021-22 for Edinburgh Napier University (2022)
Dataset
Ramage, L., & Lawson, S. (2022). Jisc OA Annual Report 2021-22 for Edinburgh Napier University. [Dataset]. https://doi.org/10.17869/enu.2022.2896250

This dataset contains details of article processing charges (APCs) paid by Edinburgh Napier University to make publications open access during the academic year 2021-22. It has been completed using the Jisc APC template.

UMC-in-FP Dataset (2022)
Dataset
Chapman, P. UMC-in-FP Dataset. [Dataset]. https://doi.org/10.17869/enu.2023.3064076

This is the dataset which accompanies the paper "Experiences of Use-Modify-Create framework to teach functional programming"

DATASET: The impact of Covid-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland (2022)
Dataset
Downey, L., Fonzone, A., & Fountas, G. (2022). DATASET: The impact of Covid-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland. [Dataset]. https://doi.org/10.17869/enu.2022.2853752

In response to the COVID-19 pandemic, Edinburgh Napier University’s Transport Research Institute has been undertaking a study, funded by the Scottish Funding Council (SFC), into its impact on transport and travel in Scotland. As part of this research... Read More about DATASET: The impact of Covid-19 on travel behaviour, transport, lifestyles and residential location choices in Scotland.

The UK War Books Boom, 1926-33 (2021)
Dataset
Frayn, A., & Houston, F. (2021). The UK War Books Boom, 1926-33. [Dataset]. https://doi.org/10.17869/enu.2021.2810868

Data for article 'The War Books Boom in Britain, 1928–1930'. For submission to First World War Studies, Oct 2021. Data collected Jan 2020-Aug 2021 from various sources articulated in article.

The Task2Dial Dataset (2021)
Dataset
Gkatzia, D., & Strathearn, C. (2021). The Task2Dial Dataset. [Dataset]

URL: https://huggingface.co/datasets/cstrathe435/Task2Dial

Jisc OA Annual Report 2020-21 for Edinburgh Napier University (2021)
Dataset
Ramage, L. (2021). Jisc OA Annual Report 2020-21 for Edinburgh Napier University. [Dataset]. https://doi.org/10.17869/enu.2021.2830310

This dataset contains details of article processing charges (APCs) paid by Edinburgh Napier University to make publications open access during the academic year 2020-21. It has been completed using the Jisc APC template.

Calculation of detection rate for camera trap records of mountain hare Lepus timidus Scotland (S2) (2021)
Dataset
Gilchrist, J., Pettigrew, G., Di Vita, V., & Pettigrew, M. (2021). Calculation of detection rate for camera trap records of mountain hare Lepus timidus Scotland (S2). [Dataset]. https://doi.org/10.5061/dryad.4b8gthtc4

The research presented in this paper provides an insight into the behavioural ecology of mountain hares on heather moorland in the Lammermuir Hills of south east Scotland. We examine the seasonal and diel activity patterns using camera traps over a p... Read More about Calculation of detection rate for camera trap records of mountain hare Lepus timidus Scotland (S2).

Camera trap photographs of mountain hare Lepus timidus per month Scotland (S1A) (2021)
Dataset
Gilchrist, J., Pettigrew, G., Di Vita, V., & Pettigrew, M. (2021). Camera trap photographs of mountain hare Lepus timidus per month Scotland (S1A). [Dataset]. https://doi.org/10.5061/dryad.m0cfxpp3p

The research presented in this paper provides an insight into the behavioural ecology of mountain hares on heather moorland in the Lammermuir Hills of south east Scotland. We examine the seasonal and diel activity patterns using camera traps over a p... Read More about Camera trap photographs of mountain hare Lepus timidus per month Scotland (S1A).

Calculation of times relative to sunset and sunrise for mountain hare Lepus timidus camera trap records Scotland (S1b) (2021)
Dataset
Gilchrist, J., Pettigrew, G., Di Vita, V., & Pettigrew, M. (2021). Calculation of times relative to sunset and sunrise for mountain hare Lepus timidus camera trap records Scotland (S1b). [Dataset]. https://doi.org/10.5061/dryad.2bvq83bpx

The research presented in this paper provides an insight into the behavioural ecology of mountain hares on heather moorland in the Lammermuir Hills of south east Scotland. We examine the seasonal and diel activity patterns using camera traps over a p... Read More about Calculation of times relative to sunset and sunrise for mountain hare Lepus timidus camera trap records Scotland (S1b).

COVID-19 UK Social Media Dataset for Public Health Research (2021)
Dataset
Plant, R., Hussain, A., & Sheikh, A. (2021). COVID-19 UK Social Media Dataset for Public Health Research. [Dataset]. https://doi.org/10.17869/enu.2021.2755974

We present a benchmark database of public social media postings from the United Kingdom related to the Covid-19 pandemic for academic research purposes, along with some initial analysis, including a taxonomy of key themes organised by keyword. This r... Read More about COVID-19 UK Social Media Dataset for Public Health Research.

Interactivity In Linear Diagrams Materials [dataset] (2021)
Dataset
Chapman, P. (2021). Interactivity In Linear Diagrams Materials [dataset]. [Dataset]. https://doi.org/10.17869/enu.2021.2748492

This folder contains the: - study materials - participant responses - amalgamated dataset - analysis that form part of the paper: Chapman, Peter (2021) Interactivity in Linear Diagrams.

Drawing Algorithms For Linear Diagrams (Supplementary) (2020)
Dataset
Chapman, P., & Sim, K. (2021). Drawing Algorithms For Linear Diagrams (Supplementary). [Dataset]. https://doi.org/10.17869/enu.2021.2748170

This folder contains the material to go with the article: Peter Chapman, Kevin Sim, Huanghao Chen (2021) Drawing Algorithms for Linear Diagrams. The code, the benchmark set of diagrams, the dataset of algorithms applied to the benchmark set, an... Read More about Drawing Algorithms For Linear Diagrams (Supplementary).

ASPIRE - Real noisy audio-visual speech enhancement corpus (2020)
Dataset
Gogate, M., Dashtipour, K., Adeel, A., & Hussain, A. (2020). ASPIRE - Real noisy audio-visual speech enhancement corpus. [Dataset]. https://doi.org/10.5281/zenodo.4585619

ASPIRE is a a first of its kind, audiovisual speech corpus recorded in real noisy environment (such as cafe, restaurants) which can be used to support reliable evaluation of multi-modal Speech Filtering technologies. This dataset follows the same sen... Read More about ASPIRE - Real noisy audio-visual speech enhancement corpus.