The DPW Point of Collection datasets provide comprehensive information essential for managing waste and recycling services. These datasets include detailed geographic locations of trash and recycling collection points, such as street and alley collection sites, as well as the specific routes and scheduled collection days. By offering a digital map representation, the data allows the Department of Public Works to visualize and analyze the distribution of waste management resources. This enables efficient planning and coordination of collection activities, ensuring that waste is picked up in a timely, organized manner while optimizing operational effectiveness.

During a late 2023 survey among working-age consumers in the United Kingdom, **** percent of respondents stated that they preferred for their data to be collected via interactive surveys. Meanwhile, **** percent of respondents mentioned loyalty cards/programs as their favored data collection method.

The global data collector market is experiencing robust growth, driven by increasing automation across diverse sectors and the escalating demand for real-time data analysis. This market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching an estimated value of $25 billion by 2033. Key drivers include the expanding adoption of data analytics in precision agriculture, the rising prevalence of IoT devices generating massive datasets in industrial settings, and the growing need for advanced security systems relying on real-time data capture. The market is segmented by data collector type (portable and desktop) and application (agriculture, healthcare, security, industrial, communication, and others). The portable segment holds a significant market share due to its flexibility and ease of use in diverse field applications. North America and Europe currently dominate the market, but the Asia-Pacific region is poised for substantial growth fueled by increasing industrialization and technological advancements. However, factors such as high initial investment costs for advanced data collection systems and the need for skilled professionals to operate and interpret the data could act as market restraints. The competitive landscape features a mix of established technology giants like Microsoft and IBM alongside specialized data collector manufacturers like LUDECA, Inc., and PANalytical. These companies are actively engaged in research and development, focusing on improving data accuracy, speed, and integration capabilities. The increasing convergence of data collection with cloud computing and artificial intelligence is further shaping the market, creating opportunities for innovative solutions that enhance data analysis and decision-making across sectors. The market's future trajectory is closely tied to technological advancements in sensor technology, data storage, and communication networks, promising continued expansion and innovation throughout the forecast period.

Point coverage of bathymetry target points for Lake Darling in Washington Co., Iowa. The U.S. Geological Survey conducted a bathymetric survey of Lake Darling in 2004.

Data from December 2011

As of March 2021, YouTube was the video and streaming app found to collect the largest amount of data from global iOS users. The app collected a total of ** data points from each of the examined data types, respectively. The mobile app of video streaming service Amazon Prime Video followed, with ** data points collected across all the examined data types.

Point coverage of bathymetry target points upstream of the siltation dam at Prairie Rose Lake in Shelby Co., Iowa. The U.S. Geological Survey conducted a bathymetric survey of Prairie Rose Lake in 2004.

A geo-spatial layer depicting the approximate location of waste collection points as of November 2015

Please note that as part of the attribution of this data under the CC BY licence terms with which it is supplied, users should include the following statement: 'The information is provided to assist in field investigations. All locations, dimensions and depths shown are to be confirmed on site'.

The City of Gold Coast is not a professional information provider and makes no representations or warranties about the accuracy, reliability, completeness or suitability for any particular purpose of the Data provided here. This Data is not provided with the intent that any person will rely on it for the purpose of making decisions with financial or legal implications. Persons who place such reliance on the Data do so at their own risk.

Atmospheric data collection stations layer created from water management information system (WMIS) sites data. This service is for the Open Data Download application for the Southwest Florida Water Management District.

Point coverage of bathymetry data for Nine Eagles Lake in Decatur Co., Iowa. The U.S. Geological Survey conducted a bathymetric survey of Nine Eagles Lake in 2004.

Standard regional data collection forms used in the Pacific

The dataset collection in question is comprised of a series of related tables, which are organized in a systematic manner with rows and columns for the ease of data interpretation. These tables are part of a larger dataset collection that is primarily sourced from the website of Lantmäteriet (The Land Survey of Sweden), located in Sweden. Each table within this collection contains a variety of information and data points, providing a comprehensive overview of the subject matter at hand. The dataset collection as a whole serves as a valuable resource for comprehensive data analysis and interpretation.

Ever need to help a researcher share and archive their research data? Would you know how to advise them on managing their data so it can be easily shared and re-used? This workshop will cover best practices for collecting and organizing research data related to the goal of data preservation and sharing. We will focus on best practices and tips for collecting data, including file naming, documentation/metadata, quality control, and versioning, as well as access and control/security, backup and storage, and licensing. We will discuss the library’s role in data management, and the opportunities and challenges around supporting data sharing efforts. Through case studies we will explore a typical research data scenario and propose solutions and services by the library and institutional partners. Finally, we discuss methods to stay up to date with data management related topics.

As of March 2021, Facebook Messenger was the mobile messaging and video calls app found to collect the largest amount of data from global iOS users, with over 30 data points collected across 14 segments. Line ranked second with 26 data points, while WeChat collected a total number of 23 data points from iOS users. The most collected data segments for messaging and video call apps were users' contact information and user content.

This data set provides the date and location of seeds collected for germination and planting as part of the larger experiment in the technical report, "Facilitating Adaptation in Montane Plants to Changing Precipitation along an Elevation Gradient." The species name provided is the Hawaiian name, with the scientific name provided in the column description. The rest of the date is date and time, with elevation and land management area names. Data are provided in shapefile format (.shp) and can be used with ESRI or other spatial mapping software.

As of ********, Etsy collected around ** unique data points from global iOS users, ranking as the least data-hungry app within the shopping and food delivery category. Finance and crypto app Binance collected a total of **** unique data points from its global iOS users, while Khan Academy, an app used by children and students for homework and classes, collected a total of ***** unique data points.

Characteristics of data collection, abstraction, and management at audit sites A–G.

Abstract

The FAO has developed a monitoring system in 26 food crisis countries to better understand the impacts of various shocks on agricultural livelihoods, food security and local value chains. The Monitoring System consists of primary data collected from households on a periodic basis (more or less every four months, depending on seasonality). This third-round survey was representative at national level, covering Liberia’s 15 counties. Data were collected through face-to-face interviews conducted between 9 September and 4 October 2021. The sampling approach was based on random sampling for household questionnaires. For more information, please go to https://data-in-emergencies.fao.org/pages/monitoring

Geographic coverage

National coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

This round 3 survey was representative at national level, covering Liberia's 15 counties. Data were collected through face-to-face interviews conducted between 9 September and 4 October 2021. The sampling approach was based on random sampling for household questionnaires. The overall sampling included 1 800 households, 45 key informants, 45 agro-input vendors and 45 agri-input traders, totalling 1 935 interviews.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

A link to the questionnaire has been provided in the documentations tab.

Cleaning operations

The datasets have been edited and processed for analysis by the Needs Assessment team at the Office of Emergencies and Resilience, FAO, with some dashboards and visualizations produced. For more information, see https://data-in-emergencies.fao.org/pages/countries

The Building Strong Families (BSF) project examined the effectiveness of programs designed to improve child well-being and strengthen the relationships of low-income couples through relationship skills education. It surveyed couples 15 months and 36 months after having applied to and been accepted into a Building Stronger Families (BSF) program at one of eight locations offering services to unwed couples expecting, or having recently had a baby. Major topics included family structure, parental involvement with children, relationships, personal and parental well-being, utilization of services such as workshops to help their relationship and parenting skills, paternity and child support, and family self-sufficiency. Respondents were asked for information on recently born children and relationship status, how much time they spent with their children, their level of satisfaction with their current relationship, substance use, if they had attended relationship and parental counseling, whether they were legally required to provide child support, employment, and family background. Additional information was asked about domestic violence and child abuse, legal trouble, past sexual history, and child development. The 36-month data collection effort also included direct assessments of parenting and child development. The quality of the parenting relationship was assessed for both mothers and fathers and was based on a semi-structured play activity, "the two-bag task." This interaction was videotaped and later coded by trained assessors on multiple dimensions of parenting. During assessments with mothers, the focal child's language development was also assessed using the Peabody Picture Vocabulary Test. Demographic data includes race, education level, age, income, and marital status. The data collection is comprised of seven parts. Part 1: the BSF Eligibility and Baseline Survey Data file; Part 2: the BSF 15-Month Follow-up Survey Data file; Part 3: the program participation data file; Part 4: the BSF 15-month follow-up analysis file; Part 5: the BSF 36-Month Follow-up Survey Data file; Part 6: the mother-child in-home assessment; and Part 7: the BSF 36-Month Follow-up analysis file.

The dataset collection in question is a compilation of related data tables sourced from the website of Tilastokeskus (Statistics Finland) in Finland. The data present in the collection is organized in a tabular format comprising of rows and columns, each holding related data. The collection includes several tables, each of which represents different years, providing a temporal view of the data. The description provided by the data source, Tilastokeskuksen palvelurajapinta (Statistics Finland's service interface), suggests that the data is likely to be statistical in nature and could be related to regional statistics, given the nature of the source. This dataset is licensed under CC BY 4.0 (Creative Commons Attribution 4.0, https://creativecommons.org/licenses/by/4.0/deed.fi).