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68 results for “Chicago”
Model America - Chicago Archetype extract from ORNL's AutoBEM
<p>Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (<a href="https://bit.ly/AutoBEM">bit.ly/AutoBEM</a>).</p> <p><strong>Critical note: Building multipliers and models will be updated soon.</strong></p> <p>Archetype metadata, models, and multipliers are provided for 93 building <strong>archetypes</strong> located within the city of Chicago (United States):</p> <p> </p> <ol> <li><strong>Data (12KB *.csv) - minimalist list of each building (rows) for the following fields (columns)</strong> <ol> <li>ID - unique building ID</li> <li>Area - estimate of total conditioned floor area (ft<sup>2</sup>)</li> <li>CZ - ASHRAE Climate Zone designation</li> <li>Height - building height (ft)</li> <li>NumFloors - number of floors (above-grade) (IECC = Residential)</li> <li>BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards</li> <li>Standard - building vintage</li> <li>WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings)</li> <li>Area2D - footprint area (ft<sup>2</sup>)</li> <li>Num_build_per_zone - Number of this building type/vintage in WRF zone</li> <li>Total_zone_area - Total area of this building type/vintage in WRF zone (ft<sup>2</sup>)</li> <li>Area_multiplier - Scaling factor for building type/vintage for building in WRF zone</li> </ol> </li> <li><strong>Models (7.69MB *.zip) - EnergyPlus building energy models named according to ID</strong> <ul> <li>Each model has approximately 3,000 building input descriptors that can be extracted. Please see the EnergyPlus (v9.4) 2,784-page <a href="https://energyplus.net/sites/all/modules/custom/nrel_custom/pdfs/pdfs_v9.4.0/InputOutputReference.pdf">Input/Output Reference Guide </a>for everything that can be retrieved or simulated from these models.</li> </ul> </li> </ol>
How to cite & reference in Chicago (footnote) style
<p>This video shows how to cite and reference a book and a journal article in Chicago style, using style guide Cite Them Right.</p>
Dataset: Chicago Atlantic Real Estate Finance, Inc. (REFI) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Fig. 2. Neighbor-joining phylogenetic tree for a 219 in Prevalence of filarioid nematodes and trypanosomes in American robins and house sparrows, Chicago USA
Fig. 2. Neighbor-joining phylogenetic tree for a 219 bp region of the trypanosome 18s rRNA gene. Underlined sequences are from this study. Sequences for additional Trypanosoma spp. were downloaded from NCBI Genbank for comparison and Bodo caudatus was used as an outgroup. Numbers by branches indicate statistical bootstrap support of À50%.
Fig. 1. Neighbor-joining phylogenetic trees for a 475 in Prevalence of filarioid nematodes and trypanosomes in American robins and house sparrows, Chicago USA
Fig. 1. Neighbor-joining phylogenetic trees for a 475 bp region of the 18S rRNA gene for filarioid nematodes (A) and a 529 bp region of the filarial nematode mitochondrial cytochrome c oxidase subunit I gene (B). Sequences were obtained from bird blood clots, bird tissues, or adult nematodes recovered from birds. Underlined sequences are from this study. Additional sequences for filarial nematode species were downloaded from NCBI Genbank for comparison and Thelazia lacrimalis and Caenorhabditis elegans were used as outgroups. Numbers by branches indicate statistical bootstrap support of À50%.
Crimes Dataset Chicago
<p>Crimes in and around Chicago from the years 2001 - 2018 from data.gov</p> <p><a href="http://data.cityofchicago.org">original publisher</a></p> <p><a href="https://data.cityofchicago.org/api/views/ijzp-q8t2">metadata</a></p> <p><a href="https://catalog.data.gov/dataset/crimes-2001-to-present-398a4">dataset and description</a></p> <p> </p> <p> </p>
Crimes in Chicago from 2001 - 2018 summarized per year
<p>Crimes in and around Chicago from the years 2001 - 2018 from data.gov - summarized to an annual sum</p> <p><a href="https://data.cityofchicago.org/">original publisher</a></p> <p><a href="https://data.cityofchicago.org/api/views/ijzp-q8t2">metadata</a></p> <p><a href="https://catalog.data.gov/dataset/crimes-2001-to-present-398a4">original dataset and description</a></p> <p> </p>
Forest patch histories in the Chicago Region
<p>This layer used forest patch layers from three time periods: 2010 (Darling <em>et al.</em> 2023), 1939 (Fahey and Casali 2017), and 1830 (McBride and Halsey 2015) to quantify the disturbance history of forest patches. We classified patch history by assessing the overlap of current patches with the 1939 and 1830 layers. History types were defined as: remnant (forested in all three time periods), regrowth (forested in 2010 and 1830 but not 1939) and novel (currently forested but not forested in the pre-colonial era). It also differentiates between forest cores and edges, with edges being forested area that is within 15 m of the patch edge. This layer was created as part of the paper "Ecological and developmental history impacts the equitable distribution of services".</p>
Crime in Chicago: 2001 to 2019
<p>A complete list of crimes committed in Chicago between the years 2001 – 2019 (inclusive), and was studied by Sainsbury-Dale et al. (2023). The data were provided by the Chicago Police Department and originally downloaded from the now retired open data source website, Plenario.</p><p>Before pre-processing, the data set contained 7,138,725 observations. However, 68,904 observations did not have a location recorded and were removed. A further 163 observations were removed as they were recorded at coordinates (36.619446395, -91.686565684), which is on the border of Missouri and Arkansas (certainly not in Chicago, Illinois). This left 7,069,658 valid observations. </p><p>The data contains the following fields:</p><ul><li>id : An identifier unique to each crime.</li><li>case_number : The case number of each crime.</li><li>date : The date and time at which each crime took place.</li><li>block : The neighbourhood block at which each crime occurred.</li><li>primary_type : A factor indicating the type of each crime (e.g., burgulary, theft, etc.).</li><li>description : A brief description of each crime.</li><li>location_description : A brief description of the location at which each crime occurred.</li><li>arrest : Logical indicating whether or not an arrest was made for each associated crime.</li><li>district : The district at which each crime occurred.</li><li>community_area : The community_area at which each crime occurred.</li><li>fbi_code : Federal Bureau of Investigation (FBI) code of each crime.</li><li>year : The year in which the crime occurred.</li><li>longitude : Latitude location of each.</li><li>latitute : Longitude location of each crime.</li><li>location : Latitude and Longitude (in that order) of each crime.</li></ul><p> </p><p><strong>References </strong></p><p>Sainsbury-Dale, M., Zammit-Mangion, A., and Cressie, N. (2023). Modelling big, heterogeneous, non-Gaussian spatial and spatio-temporal data using FRK. <i>Journal of Statistical Software</i>, to appear. </p>
Machine Learning applied to the Crime scenario in the city of Chicago
<ul> <li> <pre><span>This set of databases is acquired through public data from the city of Chicago, <br>and with this, several pre-processing processes were developed to result in an <br>analysis to study security patterns and social behavior in the city.</span></pre> </li> <li> <p><code>CPD_Parks.csv</code>:Contains detailed information about Chicago Park District parks, including geographic location, dimensions, and types of facilities available.</p> </li> <li> <p><code>Crimes_-_2001_to_Present.csv</code>:<span>Record of crimes reported in the city of Chicago from 2001 to the present, including data on the nature of the crime, place and time of occurrence, and other information.</span></p> </li> <li> <p><code>Sex_Offenders.csv</code>: <span>Contains data relating to registered sex offenders, with information about the individuals and their locations.</span></p> </li> <li> <p><code>alterado.csv</code>: It represents a set of data derived from previous ones, which has undergone a transformation and cleaning process to adapt it to specific analyses.</p> </li> <li><code>ParaClasificacao.csv</code>: <span>A database prepared for classification, containing selected and processed variables ready for clustering</span></li> <li> </li> </ul>
2024 Chicago Marathon Results
<p>This dataset includes the published results for the 2024 Chicago Marathon. These results were collected from the <a href="https://results.chicagomarathon.com/2024/">2024 Chicago Marathon website</a>.</p> <p>The data for each finisher includes:</p> <ul> <li>Their name</li> <li>Their bib number</li> <li>Their gender</li> <li>Their age group</li> <li>Their country</li> <li>Their overall place</li> <li>Their gender place</li> <li>Their age group place</li> <li>Their split at the halfway mark, in HH:MM:SS and seconds</li> <li>Their net finish time, in HH:MM:SS and seconds</li> <li>The difference, in seconds, of their time for the first and second halves</li> <li>The difference in the first and the second half, calculated as a percentage of the time to complete the first half</li> </ul> <p>A few runners have a 0 for their split at the halfway mark. This indicates an error with their timing chip, and no split was recorded. These runners only have an official finish time.</p> <p>This data was used as the basis for the following articles:</p> <ul> <li><a href="https://runningwithrock.com/2024-chicago-marathon-data/">The Chicago Marathon By the Numbers</a></li> <li><a href="https://runningwithrock.com/chicago-gender-distribution/">How Does the Gender Distribution of Finishers at the Chicago Marathon Vary by Country?</a></li> <li>Marathon Pacing Strategy for Boston Qualifying Hopefuls</li> </ul> <p>This data was also used as the basis for the following Tableau Public dashboards:</p> <ul> <li><a href="https://public.tableau.com/views/2024ChicagoMarathon/2024ChicagoMarathon?:language=en-US&amp;:sid=&amp;:redirect=auth&amp;:display_count=n&amp;:origin=viz_share_link">Explore the Results of the 2024 Chicago Marathon</a></li> </ul> <p> </p>
Dataset Chart Hours Television Digital Social Intervention Chicago & Los Angeles Research PhD
<p>Dataset chart Quantitative Information Social Issues Racial Mental Emotional PhD Dr.David Render Solving Categorizing Identifying Social Issues Human Impact In Part National Case Studies Chicagoland Business & Los Angeles Economic Territories </p>
Chicago Policing Data
<p>Repository for code and data related to policing in the City of Chicago based primarily on Freedom of Information Act requests.</p>
İstanbul, Rüstem Paşa Camii, tiles from the south door, now in the Art Institute of Chicago.
<p>İstanbul, <a href="https://en.wikipedia.org/wiki/R%C3%BCstem_Pasha_Mosque">Rüstem Paşa Camii</a>, tiles from the south door, now in the Art Institute of Chicago.</p>
TC25/Chicago_COMPASS: Present-day heat-related estimates for Chicago community areas [COMPASS-GLM]
<p>Chicago_COMPASS</p> <p>Community area summaries for Chicago and related scripts. Specifics below:</p> <p>Data</p> <p>Each CSV file provides summaries for 77 community areas in Chicago from WRF simulations, satellites, and socioeconomic surveys.</p> <p>The spatial polygons for the community areas and the socioeconomic data were accessed through the Chicago Data Portal: <a href="https://data.cityofchicago.org/">https://data.cityofchicago.org/</a></p> <p>The WRF code is open source and can be found at: <a href="https://github.com/wrf-model/WRF">https://github.com/wrf-model/WRF</a></p> <p>Chicago_control, Chicago_no_urb, and Chicago_no_lake have the maximum and minimum average variables of interest for the control, no urban, and no lake simulations. These are for the BEM/BEP runs with the YSU boundary layer scheme and are used for the main results of the paper.</p> <p>The WRF_BEM_MYJ files are for the BEM/BEP control runs with the MYJ boundary layer scheme. The WRF_Noah files are the control runs using just the Unified Noah land surface model (no urban canopy). The WRF_nested file is for a control run using 3-way nested domains, with the inner domain over Chicago at 1.333 km using BEM/BEP and the YSU boundary layer scheme.</p> <p>Chicago_perc_control, Chicago_perc_no_urb, and Chicago_perc_no_lake have the 95th and 98th percentiles of hourly variables of interest for the control, no urban, and no lake simulations.</p> <p>Chicago_MODIStime_control has the daytime and nighttime variables of interest (corresponding to MODIS Aqua overpass) for the control simulations.</p> <p>en01, en02, en03, and so on represent the ensembles for each model configuration.</p> <p>Chicago_geo_socioeconomic includes the socioeconomic variables (median income per capita and Hardship Index), spatial metrics (area and distance from the coast), and satellite-derived estimates (daytime and nighttime land surface temperature (LST), and normalized different vegetation index (NDVI).</p> <p>Scripts</p> <p>WRF_to_tabular.R converts the WRF simulations into tabular data to be injested into Google Earth Engine.<br> Rasterize.js converts the tabular WRF results into a raster with separate bands for each variable on Google Earth Engine.<br> Summarize.js processeses satellite observations and summarizes the satellite and WRF outputs into regions of interest on Google Earth Engine.</p>
Coordinated Oral Health Promotion (CO-OP) Chicago
ClinicalTrials.gov study NCT03397589. IPD Sharing: YES. Countries: 1. Publications: 2.
Islet Transplantation in Type 1 Diabetic Patients Using the University of Illinois at Chicago (UIC) Protocol
ClinicalTrials.gov study NCT00679042. IPD Sharing: NO. Countries: 1. Publications: 2.
Chicago Parent Program for Foster and Kinship Caregivers
ClinicalTrials.gov study NCT06170047. IPD Sharing: YES. Countries: 1. Publications: 5.
Data from: Pollination deficits increase with urbanization in Chicago
Open the record for dataset details and reuse information.
Larval salamander retinal population data in response to natural movies from the Chicago Motion Database
Open the record for dataset details and reuse information.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.