Spatial distribution of temporary development in Bristol and Liverpool, 2000-15 (1,261 cases)

Reviews addressing how temporary uses have been mobilised over time within specific conurbations or sets of conurbations have remained a rarity (bar extended research on Berlin). A number of studies have highlighted the limited use of spatial data to inform decision-making about contemporary urban issues. With temporary use increasingly visible as a regeneration technique in England, there is a need to study its related spatial properties, as with any other form of land-use. Maps, being graphic representations of various aspects of reality, are indispensable to the effort of understanding and visualising the existing as well as the future urban environment. The purpose of this dataset was to create a spatial account of temporary development in British cities. Two cities were selected for this analysis, Bristol and Liverpool

Planning applications for temporary development in England's core cities 2000-15 (5,890 cases)

Planning applications data, derived from each core city local authority, provided a record of all applied for development activity over a prolonged period of time. In England, all local authorities have a legal duty to make available certain details relating to planning applications (as a public register) on the internet (PARSOL, 2006). A wide range of information and documentation are made available across a range of data fields. Eight data fields were extracted for our analysis, these included, ‘application number’, ‘status’, ‘application address’, ‘postcode’, ‘development description’, ‘date received’, ‘decision’ as well as ‘appeal decision’ (see PARSOL, 2006: 21). Habitually some data fields were empty requiring a more thorough analysis of the supplied documentation to obtain missing information. Similar to applications for traditional development, applications for almost all forms of temporary use are subject to an application for planning permission. Seven key terms/concepts associated with temporary urbanism were employed to search for and extract applications for temporary development within each core city, these included, ‘temporary’, ‘temporary use’, ‘period of’, ‘use of land’, ‘short term/short-term’, ‘interim’ and ‘meanwhile’. The systematic collection and collation of planning applications data resulted in an end dataset of 5,890 applications for temporary use across the eight core cities over the fifteen-year period of 2000-15. The 5,890 cases were then coded across a range of structural variables associated with the discourse on temporary use to amass city datasets capable of looking in depth at the characteristics of temporary development in the core cities

Open4Citizens Hack1 Evaluation Template

PDF'ed version of the PowerPoint template used by all 5 Open4Citizens project pilots to gather evaluation material from their project cycle 1 hackathon in 2016

tcherry: Learning the structure of tcherry trees

Learning the structure of the type of graphical models called t-cherry trees from data. Determines the structure either directly from data or by increasing the order of a t-cherry tree with lower order

On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement

Audio samples related to the experiments conducted in the paper M. Kolbæk et al. “On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement” 2019 (https://arxiv.org/abs/1909.01019

Images and videos_Experiment_% plastics waste in municipal mixed solid waste in the Municipality of Aalborg

These images were taken as part of the sample collection, preparation and critical observations for an experiment with municipal mixed solid waste in the Municipality of Aalbor

Area and Population Estimates from Sentinel Data - Ghana and Mediterranean Egypt

This dataset contains the area and population predictions made in the paper "A Method for Creating Globally Applicable Models for Population Estimates from Sentinel Data". The predictions are made using Sentinel 1 and 2 data and the newest available census data and population forecasts. The individual datasets are: ghana_area_float32.tif & egypt_area_float32.tif The predicted area of structures per pixel. Spatial Resolution: 10x10m Data format: float32 Valid for: 2021 Q3 Ghana, 2021 Q4 Egypt Nodata: -9999.0 ghana_area_uint8.tif & egypt_area_uint8.tif The predicted area of structures per pixel. Each pixel is 10x10m. The data format is uint8, rounded to the nearest integer from float32. Spatial Resolution: 10x10m Data format: uint8 Valid for: 2021 Q3 Ghana, 2021 Q4 Egypt Nodata: 255 ghana_population_unweighted.tif & egypt_population_unweighted.tif These are the unweighted population predictions for Ghana and Egypt. Unweighted means that daytime and nighttime population has not been taken into account, and each m2 of structure is weighted equally. Spatial Resolution: 10x10m Data format: float32 Valid for: 2021 Q3 Ghana, 2020 Q4 Egypt Nodata: -9999.0 ghana_population_unweighted_100m.tif & egypt_population_unweighted_100m.tif These are the same as ghana_population_unweighted.tif & egypt_population_unweighted.tif, but resampled to 100x100m using the SUM. Spatial Resolution: 100x100m Data format: float32 Valid for: 2021 Q3 Ghana, 2020 Q4 Egypt Nodata: -9999.0 ghana_area_residential.tif & ghana_area_non-residential.tif & ghana_area_residential_selforganised.tif This is the predicted area in m2 of the three classes: Residential, non-residential, and self-organised. It can be used to convert the area to a temporally adjusted population estimate as described in the paper. Spatial Resolution: 10x10m Data format: float32 Valid for: 2021 Q3 Ghana Nodata: -9999.9 ghana_m2_pr_person_conversion_layer.tif & egypt_m2_pr_person_conversion_layer.tif This is the predicted area pr person according to the most recent census and forecasts for each country. It can be used to convert from area to population. The Ghana numbers are based on ghana_area_float32 and the Ghana census 2021. Egypt's numbers are based on egypt_area_float32 and Egypt's 2017 census and UN population forecasts. The borders are smoothed with a 2km round kernel, but the sum is adjusted to remain the same. Spatial Resolution: 10x10m Data format: float32 Valid for: 2021 Q3 Ghana, 2020 Q4 Egypt Nodata: -9999.

How Scrum Adds Value to Achieving Software Quality?

39 interviews with Scrum practitioners on the topic of how Scrum as a method contribute to achieving software quality. Data analysis documentation also available with the dataset. Two validation focus groups transcript also available with the data