Like every year since 2017, Reddit has seen the devoted participation of its more committed user base to the annual April's fool project on the subreddit r/places. In 2022's r/places collaborative effort, over 10.4 million Reddit users placed a 'tile' or pixels in the collective artwork effort of the year, reaching more than 1.1 billion views. The resulting artwork, which saw almost six million "tiles" placed at the height of Redditors' activity, ended up containing more than 160 million pixels.

This child item describes R code used to determine whether public-supply water systems buy water, sell water, both buy and sell water, or are neutral (meaning the system has only local water supplies) using water source information from a proprietary dataset from the U.S. Environmental Protection Agency. This information was needed to better understand public-supply water use and where water buying and selling were likely to occur. Buying or selling of water may result in per capita rates that are not representative of the population within the water service area. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature variable in the public supply water use machine learning model. This page includes the following files: ID_WSA_04062022_Buyers_Sellers_DR.R - an R script used to determine whether a public-supply water service area buys water, sells water, or is neutral BuySell_readme.txt - a README text file describing the script

This dataset provides information about the number of properties, residents, and average property values for R Place cross streets in Auburn, WA.

This is a complete list of Kids 'R' Kids learning academies locations. Kids 'R' Kids are fully accredited daycare for infants and preschoolers as well as elementary aged children. Kids R Kids relies on the whole child approach to strengthen each child emotionally, intellectually, socially, and physically. Locations are throughout the US. Data includes phone numbers and geographical coordinates for each location.

This dataset provides information about the number of properties, residents, and average property values for Open R Place cross streets in Tucson, AZ.

On official posts made by the Reddit admin u/reddit_irl during r/place 2023, I collected 8573 comments by downloading the discussions as html files and collecting the text using Python. The files for web scraping can be found on my Github repository at https://github.com/lukelike1001/PlaceAnalysis, and a write-up on this report can be found at https://lukelike1001.github.io/place.html.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple datasets. The source dataset is identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

The dataset consists of an excel spreadsheet and shapefile representing the locations of simulation nodes used in the AWRA-R model. Some of the nodes correspond to gauging station locations or dam locations whereas other locations represent river confluences or catchment outlets which have no gauging. These are marked as "Dummy".

Purpose

Locations are used as pour points in oder to define reach areas for river system modelling.

Dataset History

Subset of data for the Hunter that was extracted from the Bureau of Meteorology's hydstra system and includes all gauges where data has been received from the lead water agency of each jurisdiction. Simulation nodes were added in locations in which the model will provide simulated streamflow.

There are 3 files that have been extracted from the Hydstra database to aid in identifying sites in each bioregion and the type of data collected from each on. These data were used to determine the simulation node locations where model outputs were generated.

The 3 files contained within the source dataset used for this determination are:

Site - lists all sites available in Hydstra from data providers. The data provider is listed in the #Station as _xxx. For example, sites in NSW are _77, QLD are _66.

Some sites do not have locational information and will not be able to be plotted.

Period - the period table lists all the variables that are recorded at each site and the period of record.

Variable - the variable table shows variable codes and names which can be linked to the period table.

Relevant location information and other data were extracted to construct the spreadsheet and shapefile within this dataset.

Dataset Citation

Bioregional Assessment Programme (XXXX) HUN AWRA-R simulation nodes v01. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/fda20928-d486-49d2-b362-e860c1918b06.

Dataset Ancestors

• Derived From National Surface Water sites Hydstra

P R stands for Parking and Travel and is the smartest parking space for visitors to Amsterdam. These are cheap parking places on the outskirts of the city where you can easily transfer to public transport. In the JSON file below (Locations.json) these are included as parking locations with type "P R". In addition, P R routes are also shown in the table below. file 'p_r_routes.json'. This concerns line segment data for building a route information map associated with P R locations. This dataset is not exhaustive in connection options but contains a selection of the public transport network to reach the city center from P R locations. All line segments together form the network. Per line segment in the geojson, the field "Transport type" (tram, metro, bus, train) and "title" (GVB line number, or in the case of train an optional route description) indicate which of the (selected for display) Public transport lines use this line segment as part of their route. The "P_R" field refers to the name of one or more of the PR locations, as found in the locations.json file, that are connected through this route. N.B. 1: This dataset has been set up for the schematic representation of municipal PR information on a map and is not a representation of the actual entire public transport network in Amsterdam. information is oriented to the display of selective information and texts, is not suitable for public transport planning, and partly contains non-coded data but fields with public texts.N.B. 2: The Transport type field once contains a different type "Centre zone" that contains the polygon data of the P R Center area. N.B. This dataset has been set up for the schematic representation of municipal P R information on a map and is not a representation of the actual entire public transport network in Amsterdam.

This child item describes R code used to determine water source fractions (groundwater (GW), surface water (SW), or spring (SP)) for public-supply water service areas, counties, and 12-digit hydrologic unit codes (HUC12) using information from a proprietary dataset from the U.S. Environmental Protection Agency. Water-use volumes per source were not available from public-supply systems so water source fractions were calculated by the number of withdrawal source types (GW/SW). For example, for a public supply system with three SW intakes and one GW well, the fractions would be 0.75 SW and 0.25 GW. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used to calculate groundwater and surface water volumes by HUC12 for public supply. This page includes the following files: FCL_Data_Water_Sources_Flagged_wHUC_DR.R - an R script used to determine water source fractions by public-supply water service areas, counties, and HUC12s WaterSource_readme.txt - a README text file describing the script County_SourceFrac.csv - a csv file with estimated water source fractions by county HUC12_SourceFrac.csv - a csv file with estimated water source fractions by HUC12 WSA_AGIDF_SourceFrac.csv - a csv file with estimated water source fractions by public-supply water service area

This is a script showing the analysis used in a paper submitted for review in Landscape and Urban Planning, titled "Seeing through their eyes: Revealing recreationists’ landscape preferences through viewshed analysis and machine learning", by Carl Lehto, Marcus Hedblom, Anna Filyushkina and Thomas Ranius.

The zip file contains an R script, data saved in .rds format and a R workspace.

Key Biodiversity Areas (KBAs) represent the largest global network of sites critical to the persistence of biodiversity, which have been identified against standardised quantitative criteria. Sites that hold very high biodiversity value or potential are given specific attention on site-based conservation targets of the Kunming-Montreal Global Biodiversity Framework (GBF), and KBAs are already used in indicators for the GBF and the Sustainable Development Goals. However, most of the species that trigger KBA status are birds and to maximise benefits for biodiversity under the actions taken to fulfil the GBF, countries need to update their KBAs to represent important sites across multiple taxa. Here we introduce KBAscope, an R package to identify potential KBAs using multiple taxonomic groups. KBAscope provides flexible, user-friendly functions to edit species data (population, range maps, area of occupancy, area of habitat and localities); apply KBA criteria; and generate outputs to suppo..., , , # KBAscope application to Greece

https://doi.org/10.5061/dryad.1ns1rn90h

KBAscope is an R package to identify potential Key Biodiverity Areas (KBAs) using multiple taxonomic groups. KBAscope provides flexible, user-friendly functions to edit species data (population, range maps, area of occupancy, area of habitat and localities); apply KBA criteria; and generate outputs to support the delineation and validation of KBAs. Here, we use KBAscope to demonstrate its functionality by identifying potential KBAs in Greece based on multiple terrestrial taxonomic groups and four sizes of grid cells (4 km2, 25 km2, 100 km2, 225 km2).

Description of the data and file structure

The data include a) range maps for 1,853 terrestrial species from the IUCN Red List (IUCN, 2023), representing all available maps for terrestrial species in Greece, regardless of the threat category; b) localities for 189 endemic species (amphibia, reptiles, orthoptera, odonata...

Contents\r This Dataset contains the following maps:\r \r 1. Identified Places of Interest\r \r Schedule 3 includes a list of identified places of interest.\r \r Data made available under CC-BY-ND terms.\r Data updated on changes to Scheme.

Source

This dataset is the official Reddit CSV Dataset from this post: https://www.reddit.com/r/place/comments/txvk2d/rplace_datasets_april_fools_2022/

Tile Placement Data

The good stuff; all tile placement data for the entire duration of r/place.

The data is available as a CSV file with the following format:

timestamp, userid, pixelcolor, coordinate

Timestamp - the UTC time of the tile placement

Userid - a hashed identifier for each user placing the tile. These are not reddit userids, but instead a hashed identifier to allow correlating tiles placed by the same user.

Pixel_color - the hex color code of the tile placedCoordinate - the “x,y” coordinate of the tile placement. 0,0 is the top left corner. 1999,0 is the top right corner. 0,1999 is the bottom left corner of the fully expanded canvas. 1999,1999 is the bottom right corner of the fully expanded canvas.

example row:

2022-04-03 17:38:22.252 UTC,yTrYCd4LUpBn4rIyNXkkW2+Fac5cQHK2lsDpNghkq0oPu9o//8oPZPlLM4CXQeEIId7l011MbHcAaLyqfhSRoA==,#FF3881,"0,0"

Shows the first recorded placement on the position 0,0.

Inside the dataset there are instances of moderators using a rectangle drawing tool to handle inappropriate content. These rows differ in the coordinate tuple which contain four values instead of two–“x1,y1,x2,y2” corresponding to the upper left x1, y1 coordinate and the lower right x2, y2 coordinate of the moderation rect. These events apply the specified color to all tiles within those two points, inclusive.

SA Heritage Places indicates the spatial location of State Heritage Places from the South Australian Heritage Register (see http://www.environment.sa.gov.au/our-places/Heritage/SA_Heritage_Register) and Local Heritage Places in the Planning and Design Code (see https://code.plan.sa.gov.au). Information about each heritage place includes:\r \r - the land parcel associated with each heritage place/item\r \r - description, criteria for listing\r \r - address, plan/parcel/title, Local Government Area.\r \r SA Heritage Places is available as spatial layers in point (centroid of the heritage place) and polygon (indicative footprint of the heritage place) format.

Comprehensive dataset containing 55 verified R-Store locations in United States with complete contact information, ratings, reviews, and location data.

This is a complete list of R/C Theatres locations along with their geographical coordinates. R/C Theatres is a chain of movie theatres located in New England. They also offer private rentals for meetings and parties.

This dataset provides information about the number of properties, residents, and average property values for Tumbling R Ranch Place cross streets in Vail, AZ.

Variables are transformed (see statistical analyses).Significance levels:****P

This dataset contains photographs of a sub-set of Heritages Places listed on the SA Heritage Register published for Unleashed 2015. The first five digits of the image name can be linked to the State Heritage ID in the Heritage Places dataset\r \r This dataset is now superseded by http://data.sa.gov.au/data/dataset/sa-heritage-places-images which contains over 7000 photographs.

This study aims to determine "the effect of conflict on employee performance at Giant Pekanbaru". In this study, a sample of 90 people was used. Data collection was carried out through questionnaires and data analysis techniques used with a significance level of 0.05 were validity test, reliability test with crobanchalpha, simple linear regression and t test analysis and analysis of determination R Square (R2). The results of the analysis and data of this study using the help of SPSS Version 16.0, the results of the simple linear regression equation are Y = 45.561 + 0.256X. Based on the results of the research on the t-test showed results, Tcount> Ttable or 2,250> 1,987. So it can be concluded that there is a significant influence between conflict on performance. Based on the data obtained from the variable Y (performance), obtained R Square (R2) of 0.597 or 59.7%. R Square is used to determine the percentage of the influence of the Independent variable (conflict) on the Dependent variable (performance) is 59.7% while the remaining 40.3% is influenced by other variables not examined.