University of Stirling
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Television framing of the 2014 Scottish independence referendum
No full textThis dataset contains the coding of the sources that appeared or were openly referenced in all news items about the 2014 Scottish independence referendum which were broadcast on BBC Reporting Scotland between 18 August and 18 September 2014. The file records the name of each source, the duration of their appearance or quotation, their gender, the side they supported in the referendum, the source category they belonged in (elite official; expert; non-elite official; unofficial; confidential; unaccounted), whether they were interviewed or paraphrased; whether they were identified by name or in generic terms; whether they were used once or multiple times in the same item; and whether they proposed new arguments or responded to someone else's. The news programmes themselves are available from the broadcaster.Source analysis.sav. Elite official sources: political and state institutions, official political campaigns, major corporate, business and economic organisations, major NGOs, celebrities, royalty, news agencies and other news media. Non-elite official sources: smaller non-profit and non-governmental organisations (charities, voluntary organisations, associations, societies, communities), interest, activist and pressure groups, trade unions, small businesses. Experts: academics and scientists, observers and specialists, analysts, think tanks, former politicians, former public officials. Unofficial sources: ordinary people, voters, workers (lower level staff), vox populi, survey respondents, protesters, demonstrators, rioters, hecklers, observers and participants in unusual activities. Confidential sources: unnamed, e.g. according to 'well-informed sources'
DAASE: Dynamic Adaptive Automated Software Engineering
No full textThe dataset contains landscape data for "Tunnelling Crossover Networks for the Asymmetric TSP", N. Veerapen, G. Ochoa, R. Tinós, D. Whitley, The 14th International Conference on Parallel Problem Solving from Nature, PPSN2016, 17-21 September 2016, Edinburgh, Scotland. The dataset describes the network structure of the local optima networks for the 25 Asymmetric Traveling Salesman Problem instances that are sampled in the paper according to two different methodologies: using an evolutionary algorithm based on the Generalized Partition Crossover, and using Chained Lin-Kernighan.The dataset contains landscape data for "Tunnelling Crossover Networks for the Asymmetric TSP", N. Veerapen, G. Ochoa, R. Tinós, D. Whitley, The 14th International Conference on Parallel Problem Solving from Nature, PPSN2016, 17-21 September 2016, Edinburgh, Scotland. The dataset describes the network structure of the local optima networks for the 25 Asymmetric Traveling Salesman Problem instances that are sampled in the paper according to two different methodologies: using an evolutionary algorithm based on the Generalized Partition Crossover, and using Chained Lin-Kernighan.
The data are organised into three zip files, one for each method and one for generated instances. These instances (C50.0, C100.0, C200.0, E50.0, E100.0, and E200.0) were generated using the DIMACS TSP instance generator (http://dimacs.rutgers.edu/Challenges/TSP/download.html) and the distance matrices were perturbed to obtained asymmetric instances. The rest of the instances are from TSPLIB (http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/). Additional details are provided in the readme.txt file
DILiGENt -Domain-Independent Language Generation
No full textOur interest is in people’s capacity to efficiently and effectively describe geographic objects in urban scenes.
The broader ambition is to develop spatial models capable of equivalent functionality able to construct such referring expressions. To that end we present a newly crowd-sourced data set of natural language references to objects anchored in complex urban scenes (In short: The REAL Corpus – Referring Expressions Anchored Language). The REAL corpus contains a collection of images of real-world urban scenes together with verbal descriptions of target objects generated by humans, paired with data on how successful other people were able to identify the same object based on these descriptions. In total, the corpus contains 32 images with on average 27 descriptions per image and 3 verifications for each description. In addition, the corpus is annotated with a variety of linguistically motivated features. The paper highlights issues posed by collecting data using crowd-sourcing with an unrestricted input format, as well as using real-world urban scenes.The dataset includes a set of SOURCE images of features in typical urban scenes. A target was indicated in each image and participants were asked to describe that target (these words/phrases were typed by the participant). A validation process then asked other participants to read the description and tag (click) the object on the corresponding image. A set of validation images were generated to show if the tagged location was correct.
Source Images – these are presented at two resolutions – the high quality 3000by2000 pixel version and a lower 825by550 pixel version of the same image.
- source images are given a filename imgN.jpg and a corresponding version of the image with the designated target indicated is saved as imgNt.jpg
- the participant saw the source version of the image but could toggle to see the target version briefly to know which object to describe in the scene
Validation Images – these images are 825 x 550 pixels and have superimposed GREEN (correct target) and RED (incorrect) dots for where the validators have clicked. This gives an indication of how well the description worked and other features that were confused with the intended
The data collected from the web based experiments are available in 2 formats (XL and TXT).
ReferringExpressionsData_withValidationDetails.xlsx – userid (an integer number), age (range value – check look up table supplied for details), gender (male,female), photoid (links to the source images),x(coordinate x value where clicked),y(coordinate y value where clicked), annotation shown, status of validator (correct, incorrect, cantfind, ambiguous), validator_userid,validator_age(see lookup table), validator_gender(male,female)
ReferringExpressionsData_withValidationDetails-TAB_delimited.txt
Lookup table – age - this indicated the age ranges recorded in the results table. (e.g. class 4 = 41yr-50yr)1.
GABON: maintain long-standing scientific profile
No full textData to accompany manuscript Bush et al. Accepted in Methods in Ecology and Evolution October 2016. Fourier analysis to detect phenological cycles using tropical field data and simulations. Abstract for the publication is: 1.Changes in phenology are an inevitable result of climate change, and will have wide-reaching impacts on species, ecosystems, human society and even feedback onto climate. Accurate understanding of phenology is important to adapt to and mitigate such changes. However, analysis of phenology globally has been constrained by lack of data, dependence on geographically limited, non-circular indicators and lack of power in statistical analyses.
2. To address these challenges, especially for the study of tropical phenology, we developed a flexible and robust analytical approach - using Fourier analysis with confidence intervals - to objectively and quantitatively describe long-term observational phenology data even when data may be noisy. We then tested the power of this approach to detect regular cycles under different scenarios of data noise and length using both simulated and field data.
3. We use Fourier analysis to quantify flowering phenology from newly available data for 856 individual plants of 70 species observed monthly since 1986 at Lopé National Park, Gabon. After applying a confidence test, we find that 59% of the individuals have regular flowering cycles, and 88% species flower annually. We find time series length to be a significant predictor of the likelihood of confidently detecting a regular cycle from the data. Using simulated data we find that cycle regularity has a greater impact on detecting phenology than event detectability. Power analysis of the Lopé field data shows that at least six years of data are needed for confident detection of the least noisy species, but this varies and is often greater than 20 years for the most noisy species.
4. There are now a number of large phenology datasets from the tropics, from which insights into current regional and global changes may be gained, if flexible and quantitative analytical approaches are used. However consistent long-term data collection is costly and requires much effort. We provide support for the importance of such research and give suggestions as to how to avoid erroneous interpretation of shorter length datasets and maximize returns from long-term observational studies.(1.) Fourier_outputs_for_each_individual_tree.csv - Spreadsheet of Fourier outputs for each individual tree
(2.) Fourier_outputs_for_each_individual_tree_metadata.csv - Spreadsheet with metadata for 'Fourier_outputs_for_each_individual_tree.csv'
(3.) Fourier_outputs_summarised_for_each_species.csv - Spreadsheet of Fourier outputs summarised for each species
(4.) Fourier_outputs_summarised_for_each_species_metadata.csv - Spreadsheet with metadata for 'Fourier_outputs_summarised_for_each_species.csv
Towards visually-driven speech enhancement for cognitively-inspired multi-modal hearing-aid devices (AV-COGHEAR)
No full textThis dataset contains a range of joint audiovisual vectors, in the form of 2D-DCT visual features, and the equivalent audio log-filterbank vector. All visual vectors were extracted by tracking and cropping the lip region of a range of Grid videos (1000 videos from five speakers, giving a total of 5000 videos), and then transforming the region with 2D-DCT. The audio vector was extracted by windowing the audio signal, and transforming each frame into a log-filterbank vector. The visual signal was then interpolated to match the audio, and a number of large datasets were created, with the frames shuffled randomly to prevent bias, and with different pairings, including multiple visual frames to estimate a single audio frame (from one visual to one audio pairings, to 28 visual to one audio pairings). The aim of this dataset was to evaluate how well audio speech could be estimated using visual information, and is in a format that can be input into a machine learning approach such as a neural network. The dataset was created by Andrew Abel and Amir Hussain, original data taken from the Grid Corpus, recorded by Cooke, Barker, Cunningham and Shao (see: An audio-visual corpus for speech perception and automatic speech recognition, 2006).The contents of the files are detailed in contents.xls
Television framing of the 2014 Scottish independence referendum
No full textThe frames identified in the coverage of the 2014 Scottish referendum are here applied to analyse the coverage of the 2016 EU referendum coverage of BBC's Reporting Scotland daily bulletin. This dataset contains the coding of the frames that appeared in all news items about the 2016 EU referendum that were broadcast on BBC Reporting Scotland between 23 May and 23 June 2016. The file records the date, duration, and type of each item in this coverage and whether or not the following frames were present: policy, strategic game, relationship between England and Scotland, divorce, constitutional change, national division, self determination, and national identity. The programmes themselves are available from the broadcaster. The purpose of this analysis is to allow a comparison between the framing of the Scottish referendum in 2014 (in https://datastorre.stir.ac.uk/handle/11667/79) and a small sample of equivalent coverage of the 2016 EU referendum, particularly in relation to the relative prominence of the strategic game and policy frames in the two samples. The 2016 sample contains all coverage of the EU referendum on the specific BBC news bulletin in the final month of the campaign.EU ref on BBC Reporting Scotland.sav. Indicators of game frame: emphasis on political strategy; war, game and horse-race metaphors; emphasis on who is winning or losing; reports of how the two sides are doing in polls; analyses of politicians’ performance. Indicators of policy frame: focus on policy problems, politicians’ proposals for their solution and/or their implications for the public. Indicators of identity frame: references to British distinctiveness; references to the common features and history that British people share with Europe. Indicators of self-determination frame: references to the UK making decisions separately from the EU (not specifying what decisions); references to the UK running its own affairs. Indicators of divorce frame: marriage, relationship and/or breaking up metaphors; representation of the UK and the EU as human partners or friends falling out. Indicators of national division frame: reports on division within the UK, emphasis on conflictive nature of the referendum. Indicators of Anglo-Scottish relationship frame: references to how the referendum outcome may influence the relationship between Scotland and England, speculations about what may happen if the two nations vote differently or similarly. Indicators of constitutional change frame: references to changing the status of the UK within the EU. .SAV is a file extension used for saved data of SPSS (Statistical Package for the Social Sciences). SPSS is used for statistical analysis. SAV files contain binary data which can only be used on the platform that created the file. If migrating the file to another platform, it would have to be converted into the appropriate format. SPSS Version 21.0 use
DAASE: Dynamic Adaptive Automated Software Engineering
No full textThe dataset contains landscape data for "Deconstructing the Big Valley Search Space Hypothesis", G. Ochoa, N. Veerapen. The 16th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP 2016), 30 March - 1 April 2016, Porto, Portugal. The dataset describes the network structure of the local optima networks for the four TSPLIB Traveling Salesman Problem instances that are sampled in the paper.The dataset is described in the README.txt file.
Wester Hailes Community Connections: Past, Present, Future
No full textoai:datastorre.stir.ac.uk:11667/69This is a video of a poetry reading at Wester Hailes library which was part of the AHRC Connected Communities "Connecting Communities Festival" in June 2015. This event included the exhibition of photos depicting a timeline of Wester Hailes and its development, featuring archive photos through to modern day. ‘Our Place In Time’ represents a partnership between community organisations, universities, and research institutions that harnesses and develops new technology and social media to explore the past, present, and possible future in a neighbourhood.This is a video of a poetry reading at Wester Hailes library which was part of the AHRC Connected Communities "Connecting Communities Festival" in June 2015 - One QuickTime Vide