This data represents police response activity. Each row is a record of a Call for Service (CfS) logged with the Seattle Police Department (SPD) Communications Center. Calls originated from the community and range from in progress or active emergencies to requests for problem solving. Additionally, officers will log calls from their observations of the field.

Previous versions of this data set have withheld approximately 40% of calls. This updated process will release more than 95% of all calls but we will no longer provide latitude and longitude specific location data. In an effort to safeguard the privacy of our community, calls will only be located to the “beat” level. Beats are the most granular unit of management used for patrol deployment. To learn more about patrol deployment, please visit: https://www.seattle.gov/police/about-us/about-policing/precinct-and-patrol-boundaries.

As with any data, certain conditions and qualifications apply:

1) These data are queried from the Data Analytics Platform (DAP), and updated incrementally on a daily basis. A full refresh will occur twice a year and is intended to reconcile minor changes.

2) This data set only contains records of police response. If a call is queued in the system but cleared before an officer can respond, it will not be included.

3) These data contain administrative call types. Use the “Initial” and “Final” call type to identify the calls you wish to include in your analysis.

We invite you to engage these data, ask questions and explore.

Records from operating a customer call center or service center providing services to the public. Services may address a wide variety of topics such as understanding agency mission-specific functions or how to resolve technical difficulties with external-facing systems or programs. Includes:rn- incoming requests and responsesrn- trouble tickets and tracking logs rn- recordings of call center phone conversations with customers used for quality control and customer service trainingrn- system data, including customer ticket numbers and visit tracking rn- evaluations and feedback about customer servicesrn- information about customer services, such as “Frequently Asked Questions” (FAQs) and user guidesrn- reports generated from customer management datarn- complaints and commendation records; customer feedback and satisfaction surveys, including survey instruments, data, background materials, and reports.

This data set contains wait times experienced by individuals who request an interpreter during their calls to 311.

For more data about 311 calls, please refer to the 311 Call Center Inquiry dataset.

For more information on NYC311 Language Access, please refer to https://portal.311.nyc.gov/article/?kanumber=KA-03541.

G. Patlewicz, P. Karamertzanis, K. Paul Friedman, M. Sannicola, I. Shah, A systematic analysis of read-across within REACH registration dossiers, Computational Toxicology, Volume 30, 2024, 100304, ISSN 2468-1113, https://doi.org/10.1016/j.comtox.2024.100304

This dataset has been developed by the Australian Government as an authoritative source of indigenous location names across Australia. It is sponsored by the Spatial Policy Branch within the Department of Communications and managed solely by the Department of Human Services.

The dataset is designed to support the accurate positioning, consistent reporting, and effective delivery of Australian Government programs and services to indigenous locations.

The dataset contains Preferred and Alternate names for indigenous locations where Australian Government programs and services have been, are being, or may be provided. The Preferred name will always default to a State or Territory jurisdiction's gazetted name so the term 'preferred' does not infer that this is the locally known name for the location. Similarly, locational details are aligned, where possible, with those published in State and Territory registers.

This dataset is NOT a complete listing of all locations at which indigenous people reside. Town and city names are not included in the dataset. The dataset contains names that represent indigenous communities, outstations, defined indigenous areas within a town or city or locations where services have been provided.

This survey was undertaken to learn more about how often and under what circumstances police-public contact becomes problematic. The Bureau of Justice Statistics (BJS) initiated surveys of the public on their interactions with police in 1996 with the first Police-Public Contact Survey, a pretest among a nationally representative sample of 6,421 persons aged 12 or older. That initial version of the questionnaire revealed that about 20 percent of the public had direct, face-to-face contact with a police officer at least once during the year preceding the survey. At that time, the principal investigator estimated that about 1 in 500 residents, or about a half million people, who had an encounter with a police officer also experienced either a threat of force or the actual use of force by the officer. The current survey, an improved version of the 1996 Police-Public Contact Survey, was fielded as a supplement to the National Crime Victimization Survey (ICPSR 6406) during the last six months of 1999. A national sample nearly 15 times as large as the pretest sample in 1996 was used. The 1999 survey yielded nearly identical estimates of the prevalence and nature of contacts between the public and the police. This survey, because of its much larger sample size, permits more extensive analysis of demographic differences in police contacts than the 1996 pretest. In addition, it added a new and more detailed set of questions about traffic stops by police, the most frequent reason given for contact with police. Variables in the dataset cover type of contact with police, including whether it was face-to-face, initiated by the police or the citizen, whether an injury to the officer or the citizen resulted from the contact, crimes reported, and police use of force. Demographic variables supplied for the citizens include gender, race, and Hispanic origin.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

This is a graphic representation of the data stewards based on PLSS Townships in PLSS areas. In non-PLSS areas the metadata at a glance is based on a data steward defined polygons such as a city or county or other units. The identification of the data steward is a general indication of the agency that will be responsible for updates and providing the authoritative data sources. In other implementations this may have been termed the alternate source, meaning alternate to the BLM. But in the shared environment of the NSDI the data steward for an area is the primary coordinator or agency responsible for making updates or causing updates to be made. The data stewardship polygons are defined and provided by the data steward.

For more information contact us at blm_id_stateoffice@blm.gov.

Crop year 2014 US map at the county level shows designations across the country under USDA's amended rule. The faster, more efficient process will immediately expand assistance to more than 1,000 counties in 26 states.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Crop Year 2014 Disaster Map For complete information, please visit https://data.gov.

From the abstract of the attached paper:

Underwater calling behaviour between breathing bouts of a single adult male Weddell seal (Leptonychotes weddellii) was examined with respect to call type and timing late in the breeding season at Davis Station, Antarctica. Underwater calls and breathing sounds were recorded on 1 and 8 December 1997. Thirty-seven sequences of calls prior to surfacing to breathe and 36 post-submerging sets of calls were analysed with respect to probability of call type occurrence and timing. Dives were 461 plus or minus 259 seconds (mean plus or minus standard deviation). The seal called every 29.7 plus or minus 56.2 seconds throughout a dive. The first call after submerging was usually (n = 29 of 36) a low frequency (less than 0.8 kHz) growl. Three patterns of three- to five-call type sequences were made following 28 of 36 breathing bouts. Call type patterns after submerging exhibited fewer different sequences than those before surfacing (chi-squared = 61.42, DF = 4, p less than 0.000001). The call usage patterns before surfacing were diverse and did not indicate when the seal was going to surface, a time when he would be vulnerable to attack from below. Our findings suggest the hypotheses that territorial male Weddell seals call throughout each dive and use stereotyped call patterns to identify themselves while vocally asserting dominance.

This work was completed as part of ASAC project 2122 (ASAC_2122).

The fields in this dataset are:

Tape number Sequence per tape Sequence entire data Call types Count since last breath Last breathing bout number Count prior to next breath Time in tape (seconds) End time of last breath Start time of next breath Time since dive

The 'sequence' relates to the sequence of call types that are given between the end of the last breath of a breathing bout and the beginning of the first breath the next time the seal surfaces to breathe. Essentially the report relates to the stereotyped nature of the call types, especially just after the dominant male dives after finishing breathing.

Each time the animal surfaced, that was identified as a breathing bout. They are numbered sequentially. At the very start of the data set the seal had to surface before the breathing bout could be counted (as number 1). This procedure enabled us to identify the order and timing of the calls that occurred immediately before and immediately after each breathing bout. Thus, the 'count prior to the next breath' gives the order of the calls before the seal surfaced to breathe again (third last, second last, last,).

The call types were analysed with respect to the following pattern:

third last, second last, last, breathing bout, first, second, third, etc. to third last, second last, last, next breathing bout.

This data is no longer being actively updated. The dataset is deprecated and will be removed from the Portal within the next three months. If you have any questions, please reach out to the Open Data team by filling out the following Contact Us form: https://louisvilleky.wufoo.com/forms/open-data-contact-form/ The Community Services division encompasses the client-based services including Neighborhood Place, Community Action Partnership, Self-Sufficiency Services, and Outreach & Advocacy.

To describe calling activity of Pseudacris crucifer in relation to temperature, precipitation, and wetland water levels, we programmed an acoustic recorder (Wildlife Acoustics) to sample seasonal amphibian calls remotely at study site SC4DAI2 in the St. Croix National Scenic Riverway from 2008 to 2012. We programmed the recorder to sample for five minutes at the top of every hour of every day from late winter/early spring through late summer. We used the Songscape option in Songscope software to generate annual summaries of all of our acoustic samples from SC4DAI2. These summaries included a median dB level for each prescribed frequency within each recording. Pseudacris crucifer, the spring peeper, inhabited SC4DAI2 and typically called over several weeks each year, depending upon weather conditions and surface-water availability. Most of the energy in their individual calls occurred between 2900 and 3200 Hz, which provided a unique acoustic signature compared with the other anurans that called from the site. We used this information as part of a case study to better understand how the daily calling activity of P. crucifer varied relative to air temperature, precipitation, and water depth at SC4DAI2 across years. We first determined the daily median dB levels for frequencies across 2900 to 3200 Hz during 2100 to 2300 h, a time period during which P. crucifer typically called throughout their calling season. We did this for each day from the date when P. crucifer first called each year to the date when they last called each year and considered any day in this range as one during which they potentially could call. Because calling activity could vary from one hour to the next, we integrated the area under the curve for the daily median dB levels from 2900 to 3200 Hz during 2100 to 2300 h. We removed dates when overlapping sounds from storms or other sources rendered comparisons to calls of P. crucifer inaccurate. We used the resultant set of integrands to represent the relative sound intensity (as an indicator of calling activity) for P. crucifer across those hours for each date. Those integrands are contained in this data set. These data enabled us to then compare daily integrand values with daily measurements of air temperature, precipitation totals, and water depth.

LinkNYC is the City’s program to provide free high-speed Wi-Fi, nationwide calling, a dedicated 911 button, charging ports for mobile devices, and access to social services. The City has recently begun to roll out a new and improved design of the original LinkNYC kiosk: Link5G. This new design will provide all of the amenities of LinkNYC kiosks, with the added benefit of 4G and 5G connectivity to enhance mobile telecommunications networks. This dataset lists locations for LinkNYC kiosks plus four public payphones in the five boroughs.

This dataset was created to assess the status of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) habitat. Surveys were conducted within occupied Lahontan cutthroat trout habitat, as designated by the U.S. Fish and Wildlife Service. Data represent reach-based surveys conducted in accordance with the Lahontan cutthroat trout habitat status assessment (LCTHSA) protocol (USGS). LCTHSA uses a probabalistic sampling design (i.e., Generalized Random Tessellation Stratified), standardized collection of habitat attributes, electronic data capture and management, and integration with remote sensing and geospatially-derived data products. Data were collected and managed by the U.S. Geological Survey and U.S. Fish and Wildlife Service, and/or affiliated field crews with support from the U.S. Geological Survey, U.S. Fish and Wildlife Service. U.S. Forest Service, and Nevada Department of Wildlife. Data are stored in a centralized database (LCT Conservation Efforts Database: https://conservationefforts.org/cutr/home/).

This data is no longer being actively updated. The dataset is deprecated and will be removed from the Portal within the next three months. If you have any questions, please reach out to the Open Data team by filling out the following Contact Us form: https://louisvilleky.wufoo.com/forms/open-data-contact-form/ The Community Services division encompasses the client-based services including Neighborhood Place, Community Action Partnership, Self-Sufficiency Services, and Outreach & Advocacy.

The data are images of tissue cultures of Valencia sweet orange nonembryogenic callus cells taken in 2006 at the U.S. Horticultural Research Laboratory, Ft. Pierce, Florida, USA to photo document treatments from an experiment designed to determine how well a model developed from a 5-factor response surface methodology (RSM) design predicted callus growth. Growth predictions for thirteen formulations are listed in the spreadsheet file 5 factor RSM Design_Predicted.xlsx. Six culture dishes were used to estimate growth for each formulation. A culture dish representative of the growth of each formulation was photographed. Each image is named to match the formulation. For example, the jpg image labeled 5-factor RSM_MS prediction 21.JPG is an image of the callus grown on MS formulation #21. This dataset includes 15 files – 14 image files and 1 Excel spreadsheet. Images were captured in JPEG (EXIF 2.2) format with a Nikon Coolpix 5400 digital camera equipped with a 1/1.8” (7.2 x 5.3 mm) CCD sensor at a resolution of 2592 x 1944 pixels. Each image is of a single culture plate with the top lid removed and photographed under cool white, fluorescent lighting.The experimental setup for the 5-factor response surface design is described in - Niedz, R. P. and T. J. Evens (2007). "Regulating plant tissue growth by mineral nutrition." In Vitro Cellular & Developmental Biology - Plant 43(4): 370-381.

This tabular data describes the average of annual maximum duration of consecutive dry and wet days per event, where precipitation totals are 0 or equal and exceeds 1 millimeters respectively, during the 30-year period 1981 – 2010 for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. A wet event is defined as a period when the number of consecutive days with precipitation equals or exceeds 1 millimeter. A dry event is defined as a period when the number of consecutive days with precipitation equals 0 millimeters. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data for 30 year (1981-2010) average of annual maximum duration of consecutive dry and wet days per event was a 1-kilometer resolution GeoTIFF file that was produced and acquired from DAYMET (2018). Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).

These data were collected under a cooperative mapping program between the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration Office for Coastal Management (NOAA\OCM), and the Apalachicola National Estuarine Research Reserve (NERR). The primary objectives of this program were to collect marine geophysical data to develop a suite of seafloor maps to better define the extent of oyster habitats, the overall seafloor geology of the bay and provide updated information for management of this resource. In addition to their value for management of the bay's oyster resources, the maps also provide a geologic framework for scientific research and the public. High-resolution bathymetry, backscatter intensity, and seismic profile data were collected over 230 square kilometers of the floor of the bay. The study focused on the Apalachicola Bay and Western St. George Sound portions of the estuary mostly in depths > 2.0 meters. Original contact information: Contact Name: Brian Andrews Contact Org: U.S. Geological Survey Title: Geographer Phone: 508-548-8700 x2348 Email: bandrews@usgs.gov