This EnviroAtlas web service includes maps that illustrate factors affecting transit accessibility, and indicators of accessibility. Accessibility measures how easily people can reach destinations such as their workplaces and can be measured in terms of both time and distance. It is affected by factors such as the proximity of housing to jobs, transit stops, stores, and services; the availability of various transit modes; and land use patterns. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

As of January 2024, around 331.1 million people in the United States accessed the internet, making it one of the largest online markets worldwide. The country currently ranks third after China and India by the online audience size. Overview of internet usage in the United States The digital population in the United States has constantly increased in recent years. Among the most common reasons is the growing accessibility of broadband internet. A big part of the country's digital audience accesses the web via mobile phones. In 2024, the country saw an estimated 97.1 percent mobile internet user penetration. According to a 2024 survey, over 51 percent of U.S. women and 43 percent of men said it is important to them to have mobile internet access anywhere, at any time. Another 41 percent of respondents could not imagine their everyday life without the internet. Google and YouTube are the most visited websites in the country, while music, food, and drinks were the most discussed online topics. Internet usage demographics in the United States While some users can no longer imagine their life without the internet, others do not use it at all. According to 2021 data, 25 percent of U.S. adults 65 and older reported not using the internet. Despite this, online usage was strong across other age groups, especially young adults aged 18 to 49. This age group also reported the highest percentage of smartphone usage in the country as of 2023. Due to a persistent lack of connectivity in rural areas, more online users were based in urban areas of the U.S. than in the countryside.

The global number of internet users in was forecast to continuously increase between 2024 and 2029 by in total 1.3 billion users (+23.66 percent). After the fifteenth consecutive increasing year, the number of users is estimated to reach 7 billion users and therefore a new peak in 2029. Notably, the number of internet users of was continuously increasing over the past years.Depicted is the estimated number of individuals in the country or region at hand, that use the internet. As the datasource clarifies, connection quality and usage frequency are distinct aspects, not taken into account here.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of internet users in countries like the Americas and Asia.

Per the Federal Digital Government Strategy, the Department of Homeland Security Metrics Plan, and the Open FEMA Initiative, FEMA is providing the following web performance metrics with regards to FEMA.gov.rnrnInformation in this dataset includes total visits, avg visit duration, pageviews, unique visitors, avg pages/visit, avg time/page, bounce ratevisits by source, visits by Social Media Platform, and metrics on new vs returning visitors.rnrnExternal Affairs strives to make all communications accessible. If you have any challenges accessing this information, please contact FEMAWebTeam@fema.dhs.gov.

Dataset

This dataset was created by Mike Gifford

Contents

Analysis of ‘2019 NYC Open Data Plan: FOIL Summary Statistics’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/51923e05-70be-4a4c-acb6-8094a9d79e2e on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Local Law 7 of 2016 requires agencies to “review responses to freedom of information law [FOIL] requests that include the release of data to determine if such responses consist of or include public data sets that have not yet been included on the single web portal or the inclusion” on the Open Data Portal. Additionally, each City agency shall disclose “the total number, since the last update, of such agency’s freedom of information law responses that included the release of data, the total number of such responses determined to consist of or include a public data set that had not yet been included on the single web portal and the name of such public data set, where applicable, and the total number of such responses that resulted in voluntarily disclosed information being made accessible through the single web portal.”

--- Original source retains full ownership of the source dataset ---

The USGS National Hydrography Dataset (NHD) Downloadable Data Collection from The National Map (TNM) is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. For additional information on NHD, go to https://www.usgs.gov/core-science-systems/ngp/national-hydrography.

DWR was the steward for NHD and Watershed Boundary Dataset (WBD) in California. We worked with other organizations to edit and improve NHD and WBD, using the business rules for California. California's NHD improvements were sent to USGS for incorporation into the national database. The most up-to-date products are accessible from the USGS website. Please note that the California portion of the National Hydrography Dataset is appropriate for use at the 1:24,000 scale.

For additional derivative products and resources, including the major features in geopackage format, please go to this page: https://data.cnra.ca.gov/dataset/nhd-major-features Archives of previous statewide extracts of the NHD going back to 2018 may be found at https://data.cnra.ca.gov/dataset/nhd-archive.

In September 2022, USGS officially notified DWR that the NHD would become static as USGS resources will be devoted to the transition to the new 3D Hydrography Program (3DHP). 3DHP will consist of LiDAR-derived hydrography at a higher resolution than NHD. Upon completion, 3DHP data will be easier to maintain, based on a modern data model and architecture, and better meet the requirements of users that were documented in the Hydrography Requirements and Benefits Study (2016). The initial releases of 3DHP will be the NHD data cross-walked into the 3DHP data model. It will take several years for the 3DHP to be built out for California. Please refer to the resources on this page for more information.

The FINAL,STATIC version of the National Hydrography Dataset for California was published for download by USGS on December 27, 2023. This dataset can no longer be edited by the state stewards.

The first public release of the 3D Hydrography Program map service may be accessed at https://hydro.nationalmap.gov/arcgis/rest/services/3DHP_all/MapServer.

Questions about the California stewardship of these datasets may be directed to nhd_stewardship@water.ca.gov.

A collection of 22 data set of 50+ requirements each, expressed as user stories.

The dataset has been created by gathering data from web sources and we are not aware of license agreements or intellectual property rights on the requirements / user stories. The curator took utmost diligence in minimizing the risks of copyright infringement by using non-recent data that is less likely to be critical, by sampling a subset of the original requirements collection, and by qualitatively analyzing the requirements. In case of copyright infringement, please contact the dataset curator (Fabiano Dalpiaz, f.dalpiaz@uu.nl) to discuss the possibility of removal of that dataset [see Zenodo's policies]

The data sets have been originally used to conduct experiments about ambiguity detection with the REVV-Light tool: https://github.com/RELabUU/revv-light

This collection has been originally published in Mendeley data: https://data.mendeley.com/datasets/7zbk8zsd8y/1

Overview of the datasets [data and links added in December 2024]

The following text provides a description of the datasets, including links to the systems and websites, when available. The datasets are organized by macro-category and then by identifier.

Public administration and transparency

g02-federalspending.txt (2018) originates from early data in the Federal Spending Transparency project, which pertain to the website that is used to share publicly the spending data for the U.S. government. The website was created because of the Digital Accountability and Transparency Act of 2014 (DATA Act). The specific dataset pertains a system called DAIMS or Data Broker, which stands for DATA Act Information Model Schema. The sample that was gathered refers to a sub-project related to allowing the government to act as a data broker, thereby providing data to third parties. The data for the Data Broker project is currently not available online, although the backend seems to be hosted in GitHub under a CC0 1.0 Universal license. Current and recent snapshots of federal spending related websites, including many more projects than the one described in the shared collection, can be found here.

g03-loudoun.txt (2018) is a set of extracted requirements from a document, by the Loudoun County Virginia, that describes the to-be user stories and use cases about a system for land management readiness assessment called Loudoun County LandMARC. The source document can be found here and it is part of the Electronic Land Management System and EPlan Review Project - RFP RFQ issued in March 2018. More information about the overall LandMARC system and services can be found here.

g04-recycling.txt(2017) concerns a web application where recycling and waste disposal facilities can be searched and located. The application operates through the visualization of a map that the user can interact with. The dataset has obtained from a GitHub website and it is at the basis of a students' project on web site design; the code is available (no license).

g05-openspending.txt (2018) is about the OpenSpending project (www), a project of the Open Knowledge foundation which aims at transparency about how local governments spend money. At the time of the collection, the data was retrieved from a Trello board that is currently unavailable. The sample focuses on publishing, importing and editing datasets, and how the data should be presented. Currently, OpenSpending is managed via a GitHub repository which contains multiple sub-projects with unknown license.

g11-nsf.txt (2018) refers to a collection of user stories referring to the NSF Site Redesign & Content Discovery project, which originates from a publicly accessible GitHub repository (GPL 2.0 license). In particular, the user stories refer to an early version of the NSF's website. The user stories can be found as closed Issues.

(Research) data and meta-data management

g08-frictionless.txt (2016) regards the Frictionless Data project, which offers an open source dataset for building data infrastructures, to be used by researchers, data scientists, and data engineers. Links to the many projects within the Frictionless Data project are on GitHub (with a mix of Unlicense and MIT license) and web. The specific set of user stories has been collected in 2016 by GitHub user @danfowler and are stored in a Trello board.

g14-datahub.txt (2013) concerns the open source project DataHub, which is currently developed via a GitHub repository (the code has Apache License 2.0). DataHub is a data discovery platform which has been developed over multiple years. The specific data set is an initial set of user stories, which we can date back to 2013 thanks to a comment therein.

g16-mis.txt (2015) is a collection of user stories that pertains a repository for researchers and archivists. The source of the dataset is a public Trello repository. Although the user stories do not have explicit links to projects, it can be inferred that the stories originate from some project related to the library of Duke University.

g17-cask.txt (2016) refers to the Cask Data Application Platform (CDAP). CDAP is an open source application platform (GitHub, under Apache License 2.0) that can be used to develop applications within the Apache Hadoop ecosystem, an open-source framework which can be used for distributed processing of large datasets. The user stories are extracted from a document that includes requirements regarding dataset management for Cask 4.0, which includes the scenarios, user stories and a design for the implementation of these user stories. The raw data is available in the following environment.

g18-neurohub.txt (2012) is concerned with the NeuroHub platform, a neuroscience data management, analysis and collaboration platform for researchers in neuroscience to collect, store, and share data with colleagues or with the research community. The user stories were collected at a time NeuroHub was still a research project sponsored by the UK Joint Information Systems Committee (JISC). For information about the research project from which the requirements were collected, see the following record.

g22-rdadmp.txt (2018) is a collection of user stories from the Research Data Alliance's working group on DMP Common Standards. Their GitHub repository contains a collection of user stories that were created by asking the community to suggest functionality that should part of a website that manages data management plans. Each user story is stored as an issue on the GitHub's page.

g23-archivesspace.txt (2012-2013) refers to ArchivesSpace: an open source, web application for managing archives information. The application is designed to support core functions in archives administration such as accessioning; description and arrangement of processed materials including analog, hybrid, and
born digital content; management of authorities and rights; and reference service. The application supports collection management through collection management records, tracking of events, and a growing number of administrative reports. ArchivesSpace is open source and its

The Exhibit of Datasets was an experimental project with the aim of providing concise introductions to research datasets in the humanities and social sciences deposited in a trusted repository and thus made accessible for the long term. The Exhibit consists of so-called 'showcases', short webpages summarizing and supplementing the corresponding data papers, published in the Research Data Journal for the Humanities and Social Sciences. The showcase is a quick introduction to such a dataset, a bit longer than an abstract, with illustrations, interactive graphs and other multimedia (if available). As a rule it also offers the option to get acquainted with the data itself, through an interactive online spreadsheet, a data sample or link to the online database of a research project. Usually, access to these datasets requires several time consuming actions, such as downloading data, installing the appropriate software and correctly uploading the data into these programs. This makes it difficult for interested parties to quickly assess the possibilities for reuse in other projects.

The Exhibit aimed to help visitors of the website to get the right information at a glance by: - Attracting attention to (recently) acquired deposits: showing why data are interesting. - Providing a concise overview of the dataset's scope and research background; more details are to be found, for example, in the associated data paper in the Research Data Journal (RDJ). - Bringing together references to the location of the dataset and to more detailed information elsewhere, such as the project website of the data producers. - Allowing visitors to explore (a sample of) the data without downloading and installing associated software at first (see below). - Publishing related multimedia content, such as videos, animated maps, slideshows etc., which are currently difficult to include in online journals as RDJ. - Making it easier to review the dataset. The Exhibit would also have been the right place to publish these reviews in the same way as a webshop publishes consumer reviews of a product, but this could not yet be achieved within the limited duration of the project.

Note (1) The text of the showcase is a summary of the corresponding data paper in RDJ, and as such a compilation made by the Exhibit editor. In some cases a section 'Quick start in Reusing Data' is added, whose text is written entirely by the editor. (2) Various hyperlinks such as those to pages within the Exhibit website will no longer work. The interactive Zoho spreadsheets are also no longer available because this facility has been discontinued.

When asked about "Attitudes towards the internet", most Mexican respondents pick "It is important to me to have mobile internet access in any place at any time" as an answer. 55 percent did so in our online survey in 2024. Looking to gain valuable insights about users of internet providers worldwide? Check out our

This number measures how many City services are completely online and accessible for Austin residents. This measure is part of the City's effort to ensure residents can find services, understand them, access and use them, and provide feedback to the City -- across languages and all levels of ability.

When asked about "Attitudes towards the internet", most Chinese respondents pick "It is important to me to have mobile internet access in any place at any time" as an answer. 49 percent did so in our online survey in 2024. Looking to gain valuable insights about users of internet providers worldwide? Check out our

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when members of the public in states and territories were subject to state and territorial executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require them to wear masks in public. “Members of the public” are defined as individuals operating in a personal capacity. “In public” is defined to mean either (1) anywhere outside the home or (2) both in retail businesses and in restaurants/food establishments. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level. These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require individuals to wear masks in public found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program, and Max Gakh, Assistant Professor, School of Public Health, University of Nevada, Las Vegas from April 10, 2020 through July 20, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the dates provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not include data on counties that have opted out of their state mask mandate pursuant to state law. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require or recommend people stay in their homes. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level. These data are derived from the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require or recommend individuals stay at home found by the CDC, COVID-19 Community Intervention and At-Risk Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 15, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. These data do not include mandatory business closures, curfews, or limitations on public or private gatherings. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

Product Review Datasets: Uncover user sentiment

Harness the power of Product Review Datasets to understand user sentiment and insights deeply. These datasets are designed to elevate your brand and product feature analysis, help you evaluate your competitive stance, and assess investment risks.

Data sources:

• Trustpilot: datasets encompassing general consumer reviews and ratings across various businesses, products, and services.

Leave the data collection challenges to us and dive straight into market insights with clean, structured, and actionable data, including:

• Product name;
• Product category;
• Number of ratings;
• Ratings average;
• Review title;
• Review body;

Choose from multiple data delivery options to suit your needs:

1. Receive data in easy-to-read formats like spreadsheets or structured JSON files.
2. Select your preferred data storage solutions, including SFTP, Webhooks, Google Cloud Storage, AWS S3, and Microsoft Azure Storage.
3. Tailor data delivery frequencies, whether on-demand or per your agreed schedule.

Why choose Oxylabs?

1. Fresh and accurate data: Access organized, structured, and comprehensive data collected by our leading web scraping professionals.

2. Time and resource savings: Concentrate on your core business goals while we efficiently handle the data extraction process at an affordable cost.

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4. Legal compliance: Partner with a trusted leader in ethical data collection. Oxylabs is a founding member of the Ethical Web Data Collection Initiative, aligning with GDPR and CCPA standards.

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Join the ranks of satisfied customers who appreciate our meticulous attention to detail and personalized support. Experience the power of Product Review Datasets today to uncover valuable insights and enhance decision-making.

This dataset contains all state and territorial vaccine mandates that were issued from July 26, 2021 to _, regardless of whether the law has been superseded by a subsequent law, postponed by subsequent law, or otherwise modified. State and territorial laws are collected from publicly available government websites and cataloged and coded using HHS Protect by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when certain groups were subject to vaccine mandates. Data can be used to determine when states announced and required different groups to be vaccinated. These data are derived from publicly available state and territorial laws and official policy documents found by CDC’s COVID-19 Mitigation Policy Analysis Unit, and CDC’s Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from July 26, 2021 through _. These data will be updated as new laws are collected. Any orders not available through publicly accessible websites are not included in this dataset. Recommendations not included in a law are not included in these data. Effective and expiration dates were coded using only the date provided in the law. These data do not necessarily represent the official position of the Centers for Disease Control and Prevention.

The Sea Around Us is a research initiative at The University of British Columbia (located at the Institute for the Oceans and Fisheries, formerly Fisheries Centre) that assesses the impact of fisheries on the marine ecosystems of the world, and offers mitigating solutions to a range of stakeholders.

The Sea Around Us was initiated in collaboration with The Pew Charitable Trusts in 1999, and in 2014, the Sea Around Us also began a collaboration with The Paul G. Allen Family Foundation to provide African and Asian countries with more accurate and comprehensive fisheries data.

The Sea Around Us provides data and analyses through View Data, articles in peer-reviewed journals, and other media (News). The Sea Around Us regularly update products at the scale of countries’ Exclusive Economic Zones, Large Marine Ecosystems, the High Seas and other spatial scales, and as global maps and summaries.

The Sea Around Us emphasizes catch time series starting in 1950, and related series (e.g., landed value and catch by flag state, fishing sector and catch type), and fisheries-related information on every maritime country (e.g., government subsidies, marine biodiversity). Information is also offered on sub-projects, e.g., the historic expansion of fisheries, the performance of Regional Fisheries Management Organizations, or the likely impact of climate change on fisheries.

The information and data presented on their website is freely available to any user, granted that its source is acknowledged. The Sea Around Us is aware that this information may be incomplete. Please let them know about this via the feedback options available on this website.

If you cite or display any content from the Site, or reference the Sea Around Us, the Sea Around Us – Indian Ocean, the University of British Columbia or the University of Western Australia, in any format, written or otherwise, including print or web publications, presentations, grant applications, websites, other online applications such as blogs, or other works, you must provide appropriate acknowledgement using a citation consistent with the following standard:

When referring to various datasets downloaded from the website, and/or its concept or design, or to several datasets extracted from its underlying databases, cite its architects. Example: Pauly D., Zeller D., Palomares M.L.D. (Editors), 2020. Sea Around Us Concepts, Design and Data (seaaroundus.org).

When referring to a set of values extracted for a given country, EEZ or territory, cite the most recent catch reconstruction report or paper (available on the website) for that country, EEZ or territory. Example: For the Mexican Pacific EEZ, the citation should be “Cisneros-Montemayor AM, Cisneros-Mata MA, Harper S and Pauly D (2015) Unreported marine fisheries catch in Mexico, 1950-2010. Fisheries Centre Working Paper #2015-22, University of British Columbia, Vancouver. 9 p.”, which is accessible on the EEZ page for Mexico (Pacific) on seaaroundus.org.

To help us track the use of Sea Around Us data, we would appreciate you also citing Pauly, Zeller, and Palomares (2020) as the source of the information in an appropriate part of your text;

When using data from our website that are not part of a typical catch reconstruction (e.g., catches by LME or other spatial entity, subsidies given to fisheries, the estuaries in a given country, or the surface area of a given EEZ), cite both the website and the study that generated the underlying database. Many of these can be derived from the ’methods’ texts associated with data pages on seaaroundus.org. Example: Sumaila et al. (2010) for subsides, Alder (2003) for estuaries and Claus et al. (2014) for EEZ delineations, respectively.

The Sea Around Us data are (where not otherwise regulated) under a Creative Commons Attribution Non-Commercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/). Notices regarding copyrights (© The University of British Columbia), license and disclaimer can be found under http://www.seaaroundus.org/terms-and-conditions/. References:

Alder J (2003) Putting the coast in the Sea Around Us Project. The Sea Around Us Newsletter (15): 1-2.

Cisneros-Montemayor AM, Cisneros-Mata MA, Harper S and Pauly D (2015) Unreported marine fisheries catch in Mexico, 1950-2010. Fisheries Centre Working Paper #2015-22, University of British Columbia, Vancouver. 9 p.

Pauly D, Zeller D, and Palomares M.L.D. (Editors) (2020) Sea Around Us Concepts, Design and Data (www.seaaroundus.org)

Claus S, De Hauwere N, Vanhoorne B, Deckers P, Souza Dias F, Hernandez F and Mees J (2014) Marine Regions: Towards a global standard for georeferenced marine names and boundaries. Marine Geodesy 37(2): 99-125.

Sumaila UR, Khan A, Dyck A, Watson R, Munro R, Tydemers P and Pauly D (2010) A bottom-up re-estimation of global fisheries subsidies. Journal of Bioeconomics 12: 201-225.

When asked about "Attitudes towards the internet", most Australian respondents pick "It is important to me to have mobile internet access in any place at any time" as an answer. 53 percent did so in our online survey in 2024. Looking to gain valuable insights about users of internet providers worldwide? Check out our

This dataset contains state and territorial vaccine mandates currently in effect as of _ that require the group listed to be fully vaccinated. State and territorial laws are collected from publicly available government websites and cataloged and coded using HHS Protect by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when certain groups were subject to vaccine mandates. Data can be used to determine the status of state-issued vaccine requirements for certain groups as of the date of last update. These data are derived from publicly available state and territorial laws and official policy documents found by CDC’s Mitigation Policy Analysis Unit, and CDC’s Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from July 26, 2021 through _. These data will be updated as new laws are collected. Any orders not available through publicly accessible websites are not included in this dataset. Recommendations not included in a law are not included in these data. Effective and expiration dates were coded using only the date provided in the law. These data do not necessarily represent the official position of the Centers for Disease Control and Prevention.

These datasets represent management units within in-force floodplain management plans across the northern valleys of the Murray-Darling Basin in NSW. The data includes the floodplain boundaries, management zones and ecological assets derived from plans gazetted under the NSW Water Management Act 2000. The areas covered by the floodplain boundaries are declared to be floodplains under the Water Management (General) Regulation 2018. The management zones are used to define areas in which specific management rules apply. As such, this data may be used to understand which floodplain management plan rules apply to a specific location. Ecological assets, including flood-dependent ecological assets, are identified in each plan area and are required to be considered in the rules in each floodplain management plan. The plans are in place for 10 years but may be amended within this time. Any updates to the management zones as a result of a plan being amended during, or replaced following its 10 year term will be made available at that time.

PLEASE NOTE: In the case of any discrepancy between this digital dataset and the published Floodplain Management Plan (accessible on the department’s website) the instrument as made by the Minister remains the authoritative source and should be used to both interpret the intent of the Plan and in subsequent decision making. Best endeavours have been made in collating relevant Floodplain Management Plan boundary and attribution contained in this dataset. However, no warranty is provided as to the accuracy or currency of this representation. The department does not warrant and is not liable for the use of this material as per the licenced sharing conditions CC-BY 4.0.

The datasets were originally developed by the NSW Office of Environment and Heritage as part of the NSW Healthy Floodplains Project.

Note: If you would like to ask a question, make any suggestions, or tell us how you are using this dataset, please visit the NSW Water Hub which has an online forum you can join.

Spatial web services—better data sharing for better outcomes