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This dataset is no longer updated regularly. Last update was on 6/29/23. For additional information contact MHDepi@minneapolismn.gov. The website will reflect the last time the data set was updated and the total count of rows. The grid on the “Data” tab will display the up to date data. However, in certain situations there is a delay in the refresh of the downloadable data file. Sometimes the downloadable file does not reflect the updates to the data in the portal. After a delay (duration has been variable; up to 30 minutes), the file will be updated on the server and then downloads will include the updated data.

This product has been archived in accordance with Federal Grant Compliance and is no longer actively updated. The site remains accessible for historical reference purposes.

Groundwater withdrawal estimates for 1913-2016 for the Death Valley regional groundwater flow system (DVRFS) are compiled in this Microsoft® Access database to support a regional, three-dimensional, transient groundwater flow model (Belcher and others, 2017; Halford and Jackson, 2020). This database (version 2) updates previously published databases that compiled estimates of groundwater withdrawals for 1913-1998 (Moreo and others, 2003), 1913-2003 (Moreo and Justet, 2008), and 1913-2010 (Elliott and Moreo, 2018; version 1 of this data release). Version 2 of this data release is the most current version of the database and supersedes all previous versions. A total of about 41,000 acre-ft of groundwater were withdrawn from DVRFS in 2016 of which 51 percent was used for irrigation, 20 percent for domestic, and 27 percent for public supply, commercial, and mining activities. The total groundwater withdrawals for Pahrump Valley (hydrographic area 162) increased from 17,000 acre-ft in ...

The September 2025 issue of the GIS Office Newsletter features updates about the GIS Office, a summary of the most recent GIS Advisory Council meeting, GIS resources, and more.

This dataset tracks the updates made on the dataset "MeSH 2023 Update - Merge Report" as a repository for previous versions of the data and metadata.

Dataset

This dataset was created by stpete_ishii

Contents

The machine-rate methodology provides a basis for estimating the total hourly costs to own and operate logging equipment and comprises fixed, variable, and labor costs. The calculations form a simple approach to estimate machine costs and evaluate new machine alternatives consistently. The methodology has been used extensively since its development in 1942 with periodic updates. The machine-rate method has been widely cited and is regularly used by researchers, logging contractors, harvest managers, and procurement foresters. Since the last update in 2002, machine manufacturers, purchase prices, operating costs, and data sources have changed significantly. Therefore, the objective of this study was to update and modernize the methodology using current machinery, assumptions, and inputs to improve its accuracy and usability. Machine-rate inputs including interest rates, purchase prices, economic life, repair and maintenance, fuel consumption, and lubrication cost were collected for 123 unique machines from whole-tree and cut-to-length equipment dealers in the southeastern United States. In addition, empirical data were used to provide estimates for variables that previously relied on rules of thumb. Finally, guidance was provided to enable users to update assumptions with publicly available information. Prospective users can view and download the updated costing approach spreadsheet in the Supplementary Material linked to this article online.

During the August 19, 2025 Modeling Advisory Group webinar as part of the CPUC’s Assumptions for the 2026-2027 TPP, CEC staff proposed a number of updates to the data used in CEC's environmental and land use evaluation for Busbar Mapping. Many of the data updates were transitioning to the latest available data versions of individual datasets that are compiled into the CEC Land Use Screens. These changes can be described in three categories:Updated data versions of components used to define higher implication land1 :High Landscape IntactnessCritical Habitat CEC Cropland Index Model High CategoryUpdated Protected Area Layer within California to consolidate datasets and to rely on the most recently available data.Expansion of the CEC Protected Area Layer to CAISO areas that are electrically within California but physically within southern Nevada and Western Arizona. More information is found in the CEC presentation from the August 19 webinar, as well as the 2023 Land Use Screens Staff Report in the CEC Energy Planning Library. 1. For more information on lower and higher implication land, especially in the context of IRP busbar mapping, see previous definitions and usages from past workshops, including the recent webinar slides.

This dataset tracks the updates made on the dataset "MeSH 2023 Update - Split Report" as a repository for previous versions of the data and metadata.

Lead in Drinking Water in Schools Test Results – Lacey Elementary

City of Austin Open Data Terms of Use https://data.austintexas.gov/stories/s/ranj-cccq

Updates and Comments related to CodeNext

The anion data for the East River Watershed, Colorado, consists of fluoride, chloride, sulfate, nitrate, and phosphate concentrations collected at multiple, long-term monitoring sites that include stream, groundwater, and spring sampling locations. These locations represent important and/or unique end-member locations for which solute concentrations can be diagnostic of the connection between terrestrial and aquatic systems. Such locations include drainages underlined entirely or largely by shale bedrock, land covered dominated by conifers, aspens, or meadows, and drainages impacted by historic mining activity and the presence of naturally mineralized rock. Developing a long-term record of solute concentrations from a diversity of environments is a critical component of quantifying the impacts of both climate change and discrete climate perturbations, such as drought, forest mortality, and wildfire, on the riverine export of multiple anionic species. Such data may be combined with stream gauging stations co-located at each monitoring site to directly quantify the seasonal and annual mass flux of these anionic species out of the watershed. This data package contains (1) a zip file (anion_data_2014-2024.zip) containing a total of 381 files: 380 data files of anion data from across the Lawrence Berkeley National Laboratory (LBNL) Watershed Function Scientific Focus Area (SFA) which is reported in .csv files per location and a locations.csv (1 file) with latitude and longitude for each location; (2) a file-level metadata (v6_20250515_flmd.csv) file that lists each file contained in the dataset with associated metadata; and (3) a data dictionary (v6_20250515_dd.csv) file that contains terms/column_headers used throughout the files along with a definition, units, and data type. Missing values within the anion data files are noted as either "-9999" or "0.0" for not detectable (N.D.) data. There are a total of 46 locations containing anion data.Update on 2022-06-10: versioned updates to this dataset was made along with these changes: (1) updated anion data for all locations up to 2021-12-31, (2) removal of units from column headers in datafiles, (3) added row underneath headers to contain units of variables, (4) restructure of units to comply with CSV reporting format requirements, and (5) the addition of the file-level metadata (flmd.csv) and data dictionary (dd.csv) were added to comply with the File-Level Metadata Reporting Format.Update on 2022-09-09: Updates were made to reporting format specific files (file-level metadata and data dictionary) to correct swapped file names, add additional details on metadata descriptions on both files, add a header_row column to enable parsing, and add version number and date to file names (v2_20220909_flmd.csv and v2_20220909_dd.csv).Update on 2022-12-20: Updates were made to both the data files and reporting format specific files. Conversion issues affecting ER-PLM locations for anion data was resolved for the data files. Additionally, the flmd and dd files were updated to reflect the updated versions of these files. Available data was added up until 2022-03-14.Update on 2023-08-08: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-05-19. The file level metadata and data dictionary files were updated to reflect the additional data added.Update on 2024-03-11: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until 2023-09-11. Further, revisions to the data files were made to remove incorrect data points (from 1970 and 2001). The reporting format specific files were updated to reflect the additional data added.Update on 2025-05-15: Updates were made to both the data files and reporting format specific files. New available anion data was added, up until the end of WY2024 (September 30, 2024). International Generic Sample Numbers (IGSNs), when registered, were added to the data files. The reporting format specific files were updated to reflect the additional data added.

[Update 04/16/2018]: We are still developing the automation for the new dataset. We do not have an updated publishing date at the moment. We have a target schema and have provided a crosswalk document attached to the existing dataset in advance of the changes. We will update this document if there's new information to share.

[Change Notice 03/13/2018]: By the end of this month, this dataset will become historical and a new one will be created starting with incident data in 2018. This one will remain here, but no longer be updated. The new one will have data coming from a new system, will not have a 2 week lag, and have updated districts among other quality improvements. We will attach a guide here with more detailed change updates as soon as we have them.

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As of July 19, 2015, the PD District boundaries have been updated through a redistricting process. These new boundaries are not reflected in the dataset yet so you cannot compare data from July 19, 2015 onward to official reports from PD with the Police District column. We are working on an update to the dataset to reflect the updated boundaries starting with data entered July 19 onward.

Incidents derived from SFPD Crime Incident Reporting system Updated daily, showing data from 1/1/2003 up until two weeks ago from current date. Please note: San Francisco police have implemented a new system for tracking crime. The dataset included here is still coming from the old system, which is in the process of being retired (a multi-year process). Data included here is no longer the official SFPD data.

This Dataset contains all India level fuel type, vehicle category and vehicle type wise total number of vehicles registered in India in each year

Notes: 1. The data is sourced from the Vahan Portal and reflects the last update done by us. Data is updated/refreshed once every month. Any mismatches are due to frequent updates on the Vahan dashboard. 2. For datasets with year-wise data, the data of the previous years is as of 31 March of that fiscal year whereas the data of the current fiscal year is as of date.

Deprecated report. This report was created early in the response to the COVID-19 pandemic. Increased reporting and quality in hospital data have rendered the estimated datasets obsolete. Updates to this report will be discontinued on July 29, 2021. The following dataset provides state-aggregated data for estimated patient impact and hospital utilization. The source data for estimation is derived from reports with facility-level granularity across two main sources: (1) HHS TeleTracking, and (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities. Estimates Basis: These files are representative estimates for each state and are updated weekly. These projections are based on the information we have from those who reported. As more hospitals report more frequently our projections become more accurate. The actual data for these data points are updated every day, once a day on healthdata.gov and these are the downloadable data sets.

The Economic Indicator Service (EIS) aims to deliver economic content to financial institutions on both buy and sell-side and service providers. This new service currently covers 34,351 recurring macro-economic indicators from 135 countries ( as of December 16, 2019 ) such as GDP data, unemployment releases, PMI numbers etc.

Economic Indicator Service gathers the major economic events from a variety of regions and countries around the globe and provides an Economic Events Data feed and Economic Calendar service to our clients. This service includes all previous historic data on economic indicators that are currently available on the database.

Depending on availability, information regarding economic indicators, including the details of the issuing agency as well as historical data series can be made accessible for the client. Key information about EIS: • Cloud-based service for Live Calendar – delivered via HTML/JavaScript application formats, which can then be embedded onto any website using iFrames • Alternatives methods available – such as API and JSON feed for the economic calendar that can be integrated into the company’s system • Live data – updated 24/5, immediately after the data has been released • Historical data – includes a feed of all previous economic indicators available We are currently adding additional indicators/countries from Africa as well as expanding our coverage of Indicators in G20. The calendar includes the following. • Recurring & Non-recurring indicators covering 136 countries across 21 regions. • Indicators showing high, medium, and low impact data. • Indicators showing actual, previous, and forecast data. • Indicators can be filtered across 16 subtypes. • News generation for selected high-impact data. • Indicator description and historical data up to the latest eight historical points with a chart.

Update Fashions Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

This dataset contains 1935-2021 daily air temperature recorded by the National Weather Service maximum/minimum thermometers at the main climate station (CS01) at Coweeta Hydrologic Laboratory in Macon County, North Carolina, USA. The station is operated by the Southern Research Station, USDA Forest Service, but is also a cooperative station with the National Weather Service.The Coweeta Hydrologic Laboratory was established in 1934 and is world-renowned for its research in forest hydrology. Coweeta was established to determine the fundamental effects of forest management on soil and water resources and to serve as a testing ground for theories in forest hydrology. To facilitate this, a network of climate and precipitation stations was established across the site. The research program has since expanded its focus to encompass watershed ecosystem science. The original climate and precipitation network continues to facilitate these studies and serves as the foundation of the long-term data record.Original metadata date 12/07/2015. On 01/19/2016 data updated to include measurements through 2015. Minor metadata updates on 12/15/2016. On 02/28/2017 data updated to include measurements through 2016. On 02/13/2018 data updated to include measurements through 2017, and on 02/13/2019 data through 2018 were added. Additional minor metadata updates were made on 09/06/2019. On 01/27/2020 data were updated to include 2019 measurements. On 03/02/2021 data for 2020 were added. Data for 2021 were added on 03/03/2022.

For more information about Coweeta: https://www.srs.fs.usda.gov/coweeta/research/lter/.