DEPRECATED: This data package was erroneously published and contains several issues. For limno run hole locations, refer to knb-lter-mcm.39.23 (or later). For lake level measurement locations, refer to knb-lter-mcm.68.14 (or later).

   These are data about the dive holes and lakes limno holes, dive holes, lake level measurement locations

In this dataset, for each measurement (a measuring instrument at one location), the indicators V50, V85, number of vehicles and infringement rate per direction are given. The individual journeys can be found in the data set Individual Measurements (https://data.bs.ch/explore/dataset/100097) Data are exclusively statistical surveys. These stand not in connection with fines or criminal charges Persecution.The statistical velocity measurements are used to: Cantonal Police Basel-Stadt to check the speed and the Road safety (e.g. safety on pedestrian strips) at the relevant Location. The results are used to decide in which locations There is a need for action in the form of speed controls. Each Statistical device has a single point geometry and is usually with two Directions (direction 1 and 2).Note: The Measurements are not necessarily representative for the whole year and must be Context of the survey date. In addition, certain Measurements during extraordinary traffic management (e.g. Traffic levied as a result of construction site activities, etc.). Tampering with devices can lead to incorrect measurements. To The following data sets are available for speed monitoringIndividual measurements from 2021: https://data.bs.ch/explore/dataset/100097Einzelmessungen to 2020: https://data.bs.ch/explore/dataset/100200Kennzahlen per measurement location (this dataset): https://data.bs.ch/explore/dataset/100112Die Measuring locations are also published on the Geoportal Basel-Stadt: https://map.geo.bs.ch/s/geschwindigkeit

The dataset contains both the robot's high-level tool center position (TCP) health data and controller-level components' information (i.e., joint positions, velocities, currents, temperatures, currents). The datasets can be used by users (e.g., software developers, data scientists) who work on robot health management (including accuracy) but have limited or no access to robots that can capture real data. The datasets can support the: Development of robot health monitoring algorithms and tools Research of technologies and tools to support robot monitoring, diagnostics, prognostics, and health management (collectively called PHM) Validation and verification of the industrial PHM implementation. For example, the verification of a robot's TCP accuracy after the work cell has been reconfigured, or whenever a manufacturer wants to determine if the robot arm has experienced a degradation. For data collection, a trajectory is programmed for the Universal Robot (UR5) approaching and stopping at randomly-selected locations in its workspace. The robot moves along this preprogrammed trajectory during different conditions of temperature, payload, and speed. The TCP (x,y,z) of the robot are measured by a 7-D measurement system developed at NIST. Differences are calculated between the measured positions from the 7-D measurement system and the nominal positions calculated by the nominal robot kinematic parameters. The results are recorded within the dataset. Controller level sensing data are also collected from each joint (direct output from the controller of the UR5), to understand the influences of position degradation from temperature, payload, and speed. Controller-level data can be used for the root cause analysis of the robot performance degradation, by providing joint positions, velocities, currents, accelerations, torques, and temperatures. For example, the cold-start temperatures of the six joints were approximately 25 degrees Celsius. After two hours of operation, the joint temperatures increased to approximately 35 degrees Celsius. Control variables are listed in the header file in the data set (UR5TestResult_header.xlsx). If you'd like to comment on this data and/or offer recommendations on future datasets, please email guixiu.qiao@nist.gov.

This dataset contains identifiers, metadata, and a map of the locations where field measurements have been conducted at the East River Community Observatory located in the Upper Colorado River Basin, United States. This is version 3.1 of the dataset and replaces the prior version 3.0 (see below for details on changes between the versions). Dataset description: The East River is the primary field site of the Watershed Function Scientific Focus Area (WFSFA) and the Rocky Mountain Biological Laboratory. Researchers from several institutions generate highly diverse hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data at the East River in collaboration with the WFSFA. Thus, the purpose of this dataset is to maintain an inventory of the field locations and instrumentation to provide information on the field activities in the East River and coordinate data collected across different locations, researchers, and institutions. The dataset contains (1) a README file with information on the various files, (2) three csv files describing the metadata collected for each surface point location, plot and region registered with the WFSFA, (3) csv files with metadata and contact information for each surface point location registered with the WFSFA, (4) a csv file with with metadata and contact information for plots, (5) a csv file with metadata for geographic regions and sub-regions within the watershed, (6) a compiled xlsx file with all the data and metadata which can be opened in Microsoft Excel, (7) a kml map of the locations plotted in the watershed which can be opened in Google Earth, (8) a jpeg image of the kml map which can be viewed in any photo viewer, and (9) a zipped file with the registration templates used by the SFA team to collect location metadata. The zipped template file contains two csv files with the blank templates (point and plot), two csv files with instructions for filling out the location templates, and one compiled xlsx file with the instructions and blank templates together. Additionally, the templates in the xlsx include drop down validation for any controlled metadata fields. Persistent location identifiers (Location_ID) are determined by the WFSFA data management team and are used to track data and samples across locations. Dataset uses: This location metadata is used to update the Watershed SFA’s publicly accessible Field Information Portal (an interactive field sampling metadata exploration tool; https://wfsfa-data.lbl.gov/watershed/), the kml map file included in this dataset, and other data management tools internal to the Watershed SFA team. Version Information: The latest version of this dataset publication is version 3.1. This version contains a total of 101 new point locations and 1 new geographic region. Overall, there are a total of 1111 point locations, 62 plots, and 36 geographic regions. Additionally, the kml map of locations and image now includes a Taylor River geographic region boundary and stream network. Refer to methods for further details on the version history. This dataset will be updated on a periodic basis with new measurement location information. Researchers interested in having their East River measurement locations added in this list should reach out to the WFSFA data management team at wfsfa-data@googlegroups.com. Acknowledgements: Please cite this dataset if using any of the location metadata in other publications or derived products. If using the location metadata for the NEON hyperspectral campaign, additionally cite Chadwick et al. (2020). doi:10.15485/1618130.

The dataset consists of site identification, location, temperature and CO2 flux from diffuse emission measurement at the Tiptop fire. A total of 40 CO2 flux measurements were made at 27 locations, including five points (seven measurements) outside of the active coal fire area.

1. This dataset describes the spatial locations of river flow observation stations managed by the Water Resources Agency, and is provided for use by government agencies, private organizations, groups commissioned by government agencies, and academic units. The field is displayed as the name of the discontinued observation station, and the geographic spatial data is in point form, with a total of 339 records. 2. All river flow stations under the Water Resources Agency have adopted automatic recording to observe water levels, and then converted them into flow rates according to the water level-flow rate curve. 3. This data only includes basic information of the observation stations, excluding the actual observation results of time series data. 4. When opening this file using Google Earth software, clicking on the point information will provide a link to the flow data, opening a separate browser window to the Water Resources Agency Geographic Information Repository website, which provides more functionality and queries, including spatial information, time series data, and environmental analysis. 5. Due to the base map imagery provided by Google not undergoing precise orthorectification, some errors may occur during layer stacking.

UWB Positioning and Tracking Data Set UWB positioning data set contains measurements from four different indoor environments. The data set contains measurements that can be used for range-based positioning evaluation in different indoor environments. # Measurement system The measurements were made using 9 DW1000 UWB transceivers (DWM1000 modules) connected to the networked RaspberryPi computer using in-house radio board SNPN_UWB. 8 nodes were used as positioning anchor nodes with fixed locations in individual indoor environment and one node was used as a mobile positioning tag. Each UWB node is designed arround the RaspberryPi computer and are wirelessly connected to the measurement controller (e.g. laptop) using Wi-Fi and MQTT communication technologies. All tag positions were generated beforehand to as closelly resemble the human walking path as possible. All walking path points are equally spaced to represent the equidistand samples of a walking path in a time-domain. The sampled walking path (measurement TAG positions) are included in a downloadable data set file under downloads section. # Folder structure Folder structure is represented below this text. Folder contains four subfolders named by the indoor environments measured during the measurement campaign and a folder raw_data where raw measurement data is saved. Each environment folder has a anchors.csv file with anchor names and locations, .json file data.json with measurements, file walking_path.csv file with tag positions and subfolder floorplan with floorplan.dxf (AutoCAD format), floorplan.png and floorplan_track.jpg. Subfolder raw_data contains raw data in subfolders named by the four indor environments where the measurements were taken. Each location subfolder contains a subfolder data where data from each tag position from the walking_path.csv is collected in a separate folder. There is exactly the same number of folders in data folder as is the number of measurement points in the walking_path.csv. Each measurement subfolder contains 48 .csv files named by communication channel and anchor used for those measurements. For example: ch1_A1.csv contains all measurements at selected tag location with anchor A1 on UWB channel ch1. The location folder contains also anchors.csv and walking_path.csv files which are identical to the files mentioned previously. The last folder in the data set is the technical_validation folder, where results of technical validation of the data set are collected. They are separated into 8 subfolders: - cir_min_max_mean - los_nlos - positioning_wls - range - range_error - range_error_A6 - range_error_histograms - rss The organization of the data set is the following: data_set + location0 - anchors.csv - data.json - walking_path.csv + floorplan - floorplan.dxf - floorplan.png - floorplan_track.jpg - walking_path.csv + location1 - ... + location2 - ... + location3 - ... + raw_data + location0 + data + 1.07_9.37_1.2 - ch1_A1.csv - ch7_A8.csv - ... + 1.37_9.34_1.2 - ... + ... + location1 + ... + location2 + ... + location3 + ... + technical validation + cir_min_max_mean + positioning_wls + range + range_error + range_error_histograms + rss - LICENSE - README # Data format Raw measurements are saved in .csv files. Each file starts with a header, where first line represents the version of the file and the second line represents the data column names. The column names have a missing column name. Actual column names included in the .csv files are: TAG_ID ANCHOR_ID X_TAG Y_TAG Z_TAG X_ANCHOR Y_ANCHOR Z_ANCHOR NLOS RANGE FP_INDEX RSS RSS_FP FP_POINT1 FP_POINT2 FP_POINT3 STDEV_NOISE CIR_POWER MAX_NOISE RXPACC CHANNEL_NUMBER FRAME_LENGTH PREAMBLE_LENGTH BITRATE PRFR PREAMBLE_CODE CIR (starts with this column; all columns until the end of the line represent the channel impulse response) # Availability of CODE Code for data analysis and preprocessing of all data available in this data set is published on GitHub: https://github.com/KlemenBr/uwb_positioning.git The code is licensed under the Apache License 2.0. # Authors and License Author of data set in this repository is Klemen Bregar, klemen.bregar@ijs.si. This work is licensed under a Creative Commons Attribution 4.0 International License. # Funding The research leading to the data collection has been partially funded from the European Horizon 2020 Programme project eWINE under grant agreement No. 688116, the Slovenian Research Agency under Grant numbers P2-0016, J2-2507 and bilateral project with Grant number BI-ME/21-22-007.

This data set is related to Traffic. History of traffic data since 2013, indicating the latter for each measurement point, the passing vehicles. The infrastructure of measurement points, available in the city of Madrid corresponds to: 7,360 vehicle detectors with the following characteristics: 71 include number plate reading devices 158 have optical machine vision systems with control from the Mobility Management Center 1,245 are specific to fast roads and access to the city and the rest of the 5,886, with basic traffic light control systems. More than 4,000 measuring points : 253 with systems for speed control, characterization of vehicles and double reading loop 70 of them make up the stations of taking specific seats of the city. Automatic control systems of all the information obtained from the detectors with continuous contrast with expected behavior patterns, as well as the follow-up of the instructions marked by the Technical Committee for Standardization AEN/CTN 199; and in particular SC3 specific applications relating to “Detectors and data collection stations” and SC15 relating to “Data quality”. In this same portal you can find other related data sets such as: Traffic. Real-time traffic data . With real-time information (updated every 5 minutes) Traffic. Map of traffic intensity plots, with the same information in KML format, and with the possibility of viewing it in Google Maps or Google Earth. And other traffic-related data sets. You can search for them by putting the word 'Traffic' in the search engine (top right).

Field measurements are physically measured values collected during a visit to the monitoring location. Field measurements consist of measurements of gage height and discharge, and readings of groundwater levels, and are primarily used as calibration readings for the automated sensors collecting continuous data. They are collected at a low frequency, and delivery of the data in WDFN may be delayed due to data processing time.

1. This dataset describes the spatial location data of the river flow observation stations established by the Water Resources Agency to provide government agencies and private organizations, groups, or academic units commissioned by government agencies with the information. The fields display the station name, and the spatial data is presented in point form, with a total of 104 data entries.2. All river flow stations under the Water Resources Agency have adopted automatic recording to observe water levels, and then convert them to flow rates based on the water level-flow rate curve.3. This data only includes basic station information and does not include the actual observation results over time.4. When opening this file using Google Earth software, clicking on the point information will provide a link to flow data, which will open in a new browser window to the Water Resources Agency's Geographic Information Storage Center website, offering more comprehensive functions and queries, including spatial information, temporal data, and environmental analysis.5. Due to the lack of precise ortho-rectification in the base map images provided by Google, there may be some errors when overlaying layers.

This data set is one of many developed in support of The High Plains Groundwater Availability Project and the U.S. Geological Survey Data Series Report: Geodatabase Compilation of Hydrogeologic, Remote Sensing, and Water-Budget-Component data for the High Plains aquifer, 2011 (ds777). This dataset contains point vector data of 20,759 wells with 327,129 water-level measurement records located in areas overlying the northern High Plains aquifer in the United States. The northern High Plains aquifer underlies 61.7 million acres (96,400 square miles) in Colorado, Kansas, Nebraska, South Dakota, and Wyoming. These data were acquired from the U.S. Geological Survey National Water Information System (NWIS) and the High Plains water-level monitoring network maintained by Virginia McGuire. Included in this dataset is a point feature class (pts_WaterLevel_development) of water-level measurements in the northern High Plains aquifer for the northern High Plains groundwater-flow model development period October 1, 1940 to May 31, 2009 in 138 stress periods.

These are data about the dive holes and lakes limno holes, dive holes, lake level measurement locations

1. This dataset describes the spatial locations of 25 central river level observation stations set up by the Water Resources Agency to provide government agencies and private organizations, groups, or academic units commissioned by government agencies with the names of decommissioned observation stations. The geographical spatial data is in point format, with a total of 168 records.2. The water level stations belonging to the Water Resources Agency have all adopted automatic recording for observation. This dataset only includes basic station information and does not include the actual observational time-series data.3. Open this file using Google Earth software, click on the point information, and there will be a link to provide water level data. It will open another browser window to the Water Resources Agency Geographic Information Storage Center website, which provides more functions and queries, including spatial information, time-series data, and environmental analysis.4. Because the base map images provided by Google have not undergone precise orthorectification, some errors may occur when overlaying layers.

Traffic measurements taken on 10 April 2025. It collected data about the number of vehicles, pedestrians - children and adults, and cyclists, nearby school that is Warsaw's 2nd pilot location in REALLOCATE.

This map shows the measurement locations used to derive the temporary background value of PFAS in soil. The measurement locations are in unsuspected areas. The measurement values ​​of the various PFAS substances are also available for each location.

This data set is related to Traffic. History of traffic data since 2013, indicating the latter for each measurement point, the passing vehicles. The infrastructure of measurement points, available in the city of Madrid corresponds to: 7,360 vehicle detectors with the following characteristics: 71 include number plate reading devices 158 have optical machine vision systems with control from the Mobility Management Center 1,245 are specific to fast roads and access to the city and the rest of the 5,886, with basic traffic light control systems. More than 4,000 measuring points : 253 with systems for speed control, characterization of vehicles and double reading loop 70 of them make up the stations of taking specific seats of the city. Automatic control systems of all the information obtained from the detectors with continuous contrast with expected behavior patterns, as well as the follow-up of the instructions marked by the Technical Committee for Standardization AEN/CTN 199; and in particular SC3 specific applications relating to “Detectors and data collection stations” and SC15 relating to “Data quality”. In this same portal you can find other related data sets such as: Traffic. Real-time traffic data . With real-time information (updated every 5 minutes) Traffic. Map of traffic intensity plots, with the same information in KML format, and with the possibility of viewing it in Google Maps or Google Earth. And other traffic-related data sets. You can search for them by putting the word 'Traffic' in the search engine (top right).

Location of broadband radiometers for irradiance measurement (W/m²)

This map shows the measurement locations used for the distraction of the temporary background value PFAS in landbed. The measurement locations are located in unsuspected areas. The measurements of the various PFAS substances are also available for each location.

A Garmin GPSmap 62sc device was taken to each snowpit event to get the location measurement. If no GPS file is found, further GPS details can be retrieved from the SMP device and the NIR camera. The event metadata also has location information in the form of a location name for each event. This location name indicates a site of interest and can be used to track repetitive measurements in the moving absolute location on the floe. Please direct inquiries to; David Wagner (PS122/1), Martin Schneebeli (PS122/2), Amy Macfarlane (PS122/3 and PS122/4), Ruzica Dadic (PS122/5).

The datasets in this directory are coordinated based on data sources from the municipalities.

There are four types of data sets that belong together.

• Location: Describes a location (usually a building) that has energy data.
• MeasurementPoint: Describes a measurement point with a unique id, what it is and the unit measurements are performed in.
• LocationMeasurementPoint: Connects a measurement point with a location and assigns a local namee for the measurement point. Some measurement points are used by multiple locations, e.g. for temperature measurements from official measurement stations from met.no.
• Measurements: Timestamped measurements from measurement points.

Follow this link for a description of each dataset with their attributes:

https://github.com/opendatalab-no/open-municipal-data/blob/main/coordinated-data/README_en.md