This is a link to the United States Federal Government's Open Data Portal. Here you will find data, tools, and resources to conduct research, develop web and mobile applications, design data visualizations.

Check out the attachment in the metadata detailing all the Opioid Related datasets contained in this portal.

Data.gov is the federal government’s open data site, and aims to make government more open and accountable. Opening government data increases citizen participation in government, creates opportunities for economic development, and informs decision making in both the private and public sectors.

Links included for Center for Disease Control and Prevention both the business website and their Data and Statistics website.

The AmeriCorps Office of Research and Evaluation provides grants to researchers, scholars, and dissertators at institutions of higher education, enabling them to engage in comprehensive studies on civic engagement, volunteering, and national service. Studies include a variety of populations and ranges from local to organizational, and national contexts throughout the United States. This AmeriCorps Research Grantee dataset provides comprehensive information about the grantees and their studies. For each award, we identify the: 1) study title; 2) background; 3) cohort year; 4) principal investigators and their affiliated university; 5) study location(s) associated with each grant; 6) civic engagement topic areas; and 7) the research approach. Please be aware that there may be multiple rows corresponding to a single research grantee study, reflecting the various study sites where the grantee is actively involved. Each study was thematically coded to identify their civic engagement topic areas. An individual study can be categorized into more than one group. The topic areas include: • Arts & Culture, • Community Development, • Education Across the Life Course, • Youth Development, • Environmental Stewardship, • Health & Social Wellbeing, • New Americans, • Economic Opportunity and Employment, • Social Capital, • Senior Development, and • Volunteering, Nonprofit Studies, and National Service. Additionally, the research grantees’ studies were categorized into two distinct research approaches: traditional research and participatory research. To learn more about the studies’ civic engagement topic areas and research approaches, please refer to the AmeriCorps Research Grantee Data Dictionary under Attachments. For up-to-date information surrounding the AmeriCorps Research Grantees please see: • AmeriCorps Research Grantee Activities and Insights: https://americorps.gov/grantees-sponsors/research-evaluation/grantee-profiles • Participatory Research: https://americorps.gov/sites/default/files/document/2021_07_20_ParticipatoryResearchOnePager_ORE.pdf

A 2020 research revealed that most G -20 government websites installed one or more cookies without the users' permission. Out of all government websites examined in Saudi Arabia and Indonesia, 100 percent created one or more cookies. Russia followed, with 99.7 percent of government websites using cookies. The research also found that these websites often add third-party cookies.

This dataset contains data collected during a study ("Towards High-Value Datasets determination for data-driven development: a systematic literature review") conducted by Anastasija Nikiforova (University of Tartu), Nina Rizun, Magdalena Ciesielska (Gdańsk University of Technology), Charalampos Alexopoulos (University of the Aegean) and Andrea Miletič (University of Zagreb)
It being made public both to act as supplementary data for "Towards High-Value Datasets determination for data-driven development: a systematic literature review" paper (pre-print is available in Open Access here -> https://arxiv.org/abs/2305.10234) and in order for other researchers to use these data in their own work.

The protocol is intended for the Systematic Literature review on the topic of High-value Datasets with the aim to gather information on how the topic of High-value datasets (HVD) and their determination has been reflected in the literature over the years and what has been found by these studies to date, incl. the indicators used in them, involved stakeholders, data-related aspects, and frameworks. The data in this dataset were collected in the result of the SLR over Scopus, Web of Science, and Digital Government Research library (DGRL) in 2023.

***Methodology***

To understand how HVD determination has been reflected in the literature over the years and what has been found by these studies to date, all relevant literature covering this topic has been studied. To this end, the SLR was carried out to by searching digital libraries covered by Scopus, Web of Science (WoS), Digital Government Research library (DGRL).

These databases were queried for keywords ("open data" OR "open government data") AND ("high-value data*" OR "high value data*"), which were applied to the article title, keywords, and abstract to limit the number of papers to those, where these objects were primary research objects rather than mentioned in the body, e.g., as a future work. After deduplication, 11 articles were found unique and were further checked for relevance. As a result, a total of 9 articles were further examined. Each study was independently examined by at least two authors.

To attain the objective of our study, we developed the protocol, where the information on each selected study was collected in four categories: (1) descriptive information, (2) approach- and research design- related information, (3) quality-related information, (4) HVD determination-related information.

***Test procedure***
Each study was independently examined by at least two authors, where after the in-depth examination of the full-text of the article, the structured protocol has been filled for each study.
The structure of the survey is available in the supplementary file available (see Protocol_HVD_SLR.odt, Protocol_HVD_SLR.docx)
The data collected for each study by two researchers were then synthesized in one final version by the third researcher.

***Description of the data in this data set***

Protocol_HVD_SLR provides the structure of the protocol
Spreadsheets #1 provides the filled protocol for relevant studies.
Spreadsheet#2 provides the list of results after the search over three indexing databases, i.e. before filtering out irrelevant studies

The information on each selected study was collected in four categories:
(1) descriptive information,
(2) approach- and research design- related information,
(3) quality-related information,
(4) HVD determination-related information

Descriptive information
1) Article number - a study number, corresponding to the study number assigned in an Excel worksheet
2) Complete reference - the complete source information to refer to the study
3) Year of publication - the year in which the study was published
4) Journal article / conference paper / book chapter - the type of the paper -{journal article, conference paper, book chapter}
5) DOI / Website- a link to the website where the study can be found
6) Number of citations - the number of citations of the article in Google Scholar, Scopus, Web of Science
7) Availability in OA - availability of an article in the Open Access
8) Keywords - keywords of the paper as indicated by the authors
9) Relevance for this study - what is the relevance level of the article for this study? {high / medium / low}

Approach- and research design-related information
10) Objective / RQ - the research objective / aim, established research questions
11) Research method (including unit of analysis) - the methods used to collect data, including the unit of analy-sis (country, organisation, specific unit that has been ana-lysed, e.g., the number of use-cases, scope of the SLR etc.)
12) Contributions - the contributions of the study
13) Method - whether the study uses a qualitative, quantitative, or mixed methods approach?
14) Availability of the underlying research data- whether there is a reference to the publicly available underly-ing research data e.g., transcriptions of interviews, collected data, or explanation why these data are not shared?
15) Period under investigation - period (or moment) in which the study was conducted
16) Use of theory / theoretical concepts / approaches - does the study mention any theory / theoretical concepts / approaches? If any theory is mentioned, how is theory used in the study?

Quality- and relevance- related information
17) Quality concerns - whether there are any quality concerns (e.g., limited infor-mation about the research methods used)?
18) Primary research object - is the HVD a primary research object in the study? (primary - the paper is focused around the HVD determination, sec-ondary - mentioned but not studied (e.g., as part of discus-sion, future work etc.))

HVD determination-related information
19) HVD definition and type of value - how is the HVD defined in the article and / or any other equivalent term?
20) HVD indicators - what are the indicators to identify HVD? How were they identified? (components & relationships, “input -> output")
21) A framework for HVD determination - is there a framework presented for HVD identification? What components does it consist of and what are the rela-tionships between these components? (detailed description)
22) Stakeholders and their roles - what stakeholders or actors does HVD determination in-volve? What are their roles?
23) Data - what data do HVD cover?
24) Level (if relevant) - what is the level of the HVD determination covered in the article? (e.g., city, regional, national, international)

***Format of the file***
.xls, .csv (for the first spreadsheet only), .odt, .docx

***Licenses or restrictions***
CC-BY

For more info, see README.txt

The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Water quality data can be downloaded in Excel, CSV, TSV, and KML formats. Fourteen site types are found in the WQP: aggregate groundwater use, aggregate surface water use, atmosphere, estuary, facility, glacier, lake, land, ocean, spring, stream, subsurface, well, and wetland. Water quality characteristic groups include physical conditions, chemical and bacteriological water analyses, chemical analyses of fish tissue, taxon abundance data, toxicity data, habitat assessment scores, and biological index scores, among others. Within these groups, thousands of water quality variables registered in the EPA Substance Registry Service (https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do) and the Integrated Taxonomic Information System (https://www.itis.gov/) are represented. Across all site types, physical characteristics (e.g., temperature and water level) are the most common water quality result type in the system. The Water Quality Exchange data model (WQX; http://www.exchangenetwork.net/data-exchange/wqx/), initially developed by the Environmental Information Exchange Network, was adapted by EPA to support submission of water quality records to the EPA STORET Data Warehouse [USEPA, 2016], and has subsequently become the standard data model for the WQP. Contributing organizations: ACWI The Advisory Committee on Water Information (ACWI) represents the interests of water information users and professionals in advising the federal government on federal water information programs and their effectiveness in meeting the nation's water information needs. ARS The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief in-house scientific research agency, whose job is finding solutions to agricultural problems that affect Americans every day, from field to table. ARS conducts research to develop and transfer solutions to agricultural problems of high national priority and provide information access and dissemination to, among other topics, enhance the natural resource base and the environment. Water quality data from STEWARDS, the primary database for the USDA/ARS Conservation Effects Assessment Project (CEAP) are ingested into WQP via a web service. EPA The Environmental Protection Agency (EPA) gathers and distributes water quality monitoring data collected by states, tribes, watershed groups, other federal agencies, volunteer groups, and universities through the Water Quality Exchange framework in the STORET Warehouse. NWQMC The National Water Quality Monitoring Council (NWQMC) provides a national forum for coordination of comparable and scientifically defensible methods and strategies to improve water quality monitoring, assessment, and reporting. It also promotes partnerships to foster collaboration, advance the science, and improve management within all elements of the water quality monitoring community. USGS The United States Geological Survey (USGS) investigates the occurrence, quantity, quality, distribution, and movement of surface waters and ground waters and disseminates the data to the public, state, and local governments, public and private utilities, and other federal agencies involved with managing the United States' water resources. Resources in this dataset:Resource Title: Website Pointer for Water Quality Portal. File Name: Web Page, url: https://www.waterqualitydata.us/ The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Links to Download Data, User Guide, Contributing Organizations, National coverage by state.

The latest municipal news on the official website of the Taoyuan City Government

This list contains the government API cases collected, cleaned and analysed in the APIs4DGov study "Web API landscape: relevant general purpose ICT standards, technical specifications and terms".

The list does not represent a complete list of all government cases in Europe, as it is built to support the goals of the study and is limited to the analysis and data gathered from the following sources:

• The EU open data portal

• The European data portal

• The INSPIRE catalogue

• JoinUp: The API cases collected from the European Commission JoinUp platform

• Literature-document review: the API cases gathered from the research activities of the study performed till the end of 2019

• ProgrammableWeb: the ProgrammableWeb API directory

• Smart 2015/0041: the database of 395 cases created by the study ‘The project Towards faster implementation and uptake of open government’ (SMART 2015/0041).

• Workshops/meetings/interviews: a list of API cases collected in the workshops, surveys and interviews organised within the APIs4DGov

Each API case is classified accordingly to the following rationale:

• Unique id: a unique key of each case, obtained by concatenating the following fields: (Country Code) + (Governmental level) + (Name Id) + (Type of API)

• API Country or type of provider: the country in which the API case has been published

• API provider: the specific provider that published and maintain the API case

• Name Id: an acronym of the name of the API case (it can be not unique)

• Short description

• Type of API: (i) API registry, a set, catalogue, registry or directory of APIs; (ii) API platform: a platform that supports the use of APIs; (iii) API tool: a tool used to manage APIs; (iv) API standard: a set of standards related to government APIs; (v) Data catalogue, an API published to access metadata of datasets, normally published by a data catalogue; (vi) Specific API, a unique (can have many endpoints) API built for a specific purpose

• Number of APIs: normally only one, in the case of API registry, the number of APIs published by the registry at the 31/12/2019

• Theme: list of domains related to the API case (controlled vocabulary)

• Governmental level: the geographical scope of the API (city, regional, national or international)

• Country code: the country two letters internal code

• Source: the source (among the ones listed in the previous) from where the API case has been gathered

The NIST RDaF is a map of the research data space that uses a lifecycle approach with six high-level lifecycle stages to organize key information concerning research data management (RDM) and research data dissemination. Through a community-driven and in-depth process, stakeholders identified topics and subtopics?programmatic and operational activities, concepts, and other important factors relevant to RDM. All elements of the RDaF framework foundation?the lifecycle stages and their associated topics and subtopics?are defined. Most subtopics have several informative references, which are resources such as guidelines, standards, and policies that assist stakeholders in addressing that subtopic. Further, the NIST RDaF team identified 14 Overarching Themes which are pervasive throughout the framework. The Framework foundation enables organizations and individual researchers to use the RDaF for self-assessment of their RDM status. The RDaF includes sample ?profiles? for various job functions or roles, each containing topics and subtopics that an individual in the given role is encouraged to consider in fulfilling their RDM responsibilities. Individual researchers and organizations involved in the research data lifecycle can tailor these profiles for their specific job function using a tool available on the RDaF website. The methodologies used to generate all features of the RDaF are described in detail in the publication NIST SP 1500-8.This database version of the NIST RDaF is designed so that users can readily navigate the various lifecycle stages, topics, subtopics, and overarching themes from numerous locations. In addition, unlike the published text version, links are included for the definitions of most topics and subtopics and for informative references for most subtopics. For more information on the database, please see the FAQ page.

This dataset is the result of a full-population crawl of the .gov.uk web domain, aiming to capture a full picture of the scope of public-facing government activity online and the links between different government bodies.

Local governments have been developing online services, aiming to better serve the public and reduce administrative costs. However, the impact of this work, and the links between governments’ online and offline activities, remain uncertain. The overall research question for this research examines whether local e-government has met these expectations, of Digital Era Governance and of its practitioners. Aim was to directly analyse the structure and content of government online. It shows that recent digital-centric public administration theories, typified by the Digital Era Governance quasi-paradigm, are not empirically supported by the UK local government experience.

The data consist of a file of individual Uniform Resource Locators (URLs) fetched during the crawl, and a further file containing pairs of URLs reflecting the Hypertext Markup Language (HTML) links between them. In addition, a GraphML format file is presented for a version of the data reduced to third-level-domains, with accompanying attribute data for the publishing government organisations and calculated webometric statistics based on the third-level-domain link network.

This project engages with the Digital Era Governance (DEG) work of Dunleavy et. al. and draws upon new empirical methods to explore local government and its use of Internet-related technology. It challenges the existing literature, arguing that e-government benefits have been oversold, particularly for transactional services; it updates DEG with insights from local government.

The distinctive methodological approach is to use full-population datasets and large-scale web data to provide an empirical foundation for theoretical development, and to test existing theorists’ claims. A new full-population web crawl of .gov.uk is used to analyse the shape and structure of online government using webometrics. Tools from computer science, such as automated classification, are used to enrich our understanding of the dataset. A new full-population panel dataset is constructed covering council performance, cost, web quality, and satisfaction.

The local government web shows a wide scope of provision but only limited evidence in support of the existing rhetorics of Internet-enabled service delivery. In addition, no evidence is found of a link between web development and performance, cost, or satisfaction. DEG is challenged and developed in light of these findings.

The project adds value by developing new methods for the use of big data in public administration, by empirically challenging long-held assumptions on the value of the web for government, and by building a foundation of knowledge about local government online to be built on by further research.

This is an ESRC-funded DPhil research project.

This product consists of 29 datasets of tabular data and associated metadata for watershed characteristics of 1,530 study sites of the Surface Water Trends (SWT) project of the U.S. Geological Survey’s (USGS) National Water Quality Program (NWQP). The project is conducting national studies of trends in water quality of streams and rivers for periods ranging from 10 to 40 years, between 1972 and 2012. The data here include both static and time-series characteristics. Static data include primarily physical characteristics which have changed little over this period, such as geology, soils, and topography. Time-series data represent characteristics which may or may not have changed over time, such as land use, agricultural practices, precipitation, hydrologic modifications, atmospheric deposition, and population changes.

The National Survey of Research Commercialisation (NSRC), which has been conducted since 2000, collects data on the commercialisation activities of publicly funded research organisations such as …Show full descriptionThe National Survey of Research Commercialisation (NSRC), which has been conducted since 2000, collects data on the commercialisation activities of publicly funded research organisations such as universities, medical research institutes and government research agencies. The survey includes data relating to research expenditure, licensing, research contracts and consultancies and research training. Further information about the survey (including other data sets and notes on the survey methodology) is available from the National Survey of Research Commercialisation page of the Department of Industry, Science, Energy and Resources website: http://industry.gov.au/innovation/NSRC/Pages/default.aspx.

This data was collected by the Office of the National Coordinator for Health IT in coordination with Clinovations and the George Washington University Milken Institute of Public Health. ONC and its partners collected the data through research of state government and health information organization websites. The dataset provides policy and law details for four distinct policies or laws, and, where available, hyperlinks to official state records or websites. These four policies or laws are: 1) State Health Information Exchange (HIE) Consent Policies; 2) State-Sponsored HIE Consent Policies; 3) State Laws Requiring Authorization to Disclose Mental Health Information for Treatment, Payment, and Health Care Operations (TPO); and 4) State Laws that Apply a Minimum Necessary Standard to Treatment Disclosures of Mental Health Information.

The National Survey of Research Commercialisation (NSRC), which has been conducted since 2000, collects data on the commercialisation activities of publicly funded research organisations such as …Show full descriptionThe National Survey of Research Commercialisation (NSRC), which has been conducted since 2000, collects data on the commercialisation activities of publicly funded research organisations such as universities, medical research institutes and government research agencies. The survey includes data relating to research expenditure, licensing, research contracts and consultancies and research training. Further information about the survey (including other data sets and notes on the survey methodology) is available from the National Survey of Research Commercialisation page of the Department of Industry, Innovation and Science website: http://industry.gov.au/innovation/NSRC/Pages/default.aspx.

The Nuclear Medicine National HQ System database is a series of MS Excel spreadsheets and Access Database Tables by fiscal year. They consist of information from all Veterans Affairs Medical Centers (VAMCs) performing or contracting nuclear medicine services in Veterans Affairs medical facilities. The medical centers are required to complete questionnaires annually (RCS 10-0010-Nuclear Medicine Service Annual Report). The information is then manually entered into the Access Tables, which includes: * Distribution and cost of in-house VA - Contract Physician Services, whether contracted services are made via sharing agreement (with another VA medical facility or other government medical providers) or with private providers. * Workload data for the performance and/or purchase of PET/CT studies. * Organizational structure of services. * Updated changes in key imaging service personnel (chiefs, chief technicians, radiation safety officers). * Workload data on the number and type of studies (scans) performed, including Medicare Relative Value Units (RVUs), also referred to as Weighted Work Units (WWUs). WWUs are a workload measure calculated as the product of a study's Current Procedural Terminology (CPT) code, which consists of total work costs (the cost of physician medical expertise and time), and total practice costs (the costs of running a practice, such as equipment, supplies, salaries, utilities etc). Medicare combines WWUs together with one other parameter to derive RVUs, a workload measure widely used in the health care industry. WWUs allow Nuclear Medicine to account for the complexity of each study in assessing workload, that some studies are more time consuming and require higher levels of expertise. This gives a more accurate picture of workload; productivity etc than using just 'total studies' would yield. * A detailed Full-Time Equivalent Employee (FTEE) grid, and staffing distributions of FTEEs across nuclear medicine services. * Information on Radiation Safety Committees and Radiation Safety Officers (RSOs). Beginning in 2011 this will include data collection on part-time and non VA (contract) RSOs; other affiliations they may have and if so to whom they report (supervision) at their VA medical center.Collection of data on nuclear medicine services' progress in meeting the special needs of our female veterans. Revolving documentation of all major VA-owned gamma cameras (by type) and computer systems, their specifications and ages. * Revolving data collection for PET/CT cameras owned or leased by VA; and the numbers and types of PET/CT studies performed on VA patients whether produced on-site, via mobile PET/CT contract or from non-VA providers in the community. Types of educational training/certification programs available at VA sites * Ongoing funded research projects by Nuclear Medicine (NM) staff, identified by source of funding and research purpose. * Data on physician-specific quality indicators at each nuclear medicine service. Academic achievements by NM staff, including published books/chapters, journals and abstracts. * Information from polling field sites re: relevant issues and programs Headquarters needs to address. * Results of a Congressionally mandated contracted quality assessment exercise, also known as a Proficiency study. Study results are analyzed for comparison within VA facilities (for example by mission or size), and against participating private sector health care groups. * Information collected on current issues in nuclear medicine as they arise. Radiation Safety Committee structures and membership, Radiation Safety Officer information and information on how nuclear medicine services provided for female Veterans are examples of current issues.The database is now stored completely within MS Access Database Tables with output still presented in the form of Excel graphs and tables.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Location of Terrestrial Ecosystem Research Network Monitoring Sites. TERN aims to connect and enable ecosystem scientists to collect, contribute, store, share and integrate data across disciplines.

Purpose

To locate Terrestrial Ecosystem Research Network Monitoring Sites.

Dataset History

TERN AusPlots sites downloaded from the AEKOS data portal 15/11/13 Citation: TERN AusPlots, ( 2015 ) Terrestrial Ecosystem Research Network AusPlots - Ausplots Rangelands Survey Program (biodiversity mapping supplement/subset). Adelaide, South Australia. AEKOS - TERN Ecoinformatics. , DOI: 10.4227/05/54C1B45A4CF2F see http://portal.aekos.org.au/dataset/172373

Dataset Citation

SA Department of Environment, Water and Natural Resources (2015) Terrestrial Ecosystem Research Network Monitoring Sites - PED. Bioregional Assessment Source Dataset. Viewed 12 October 2016, http://data.bioregionalassessments.gov.au/dataset/f5bd990d-f6b1-4264-972f-6662ed236981.

The National Estuarine Research Reserve System (NERRS) is a network of coastal sites designated to protect and study estuarine systems. Established through the Coastal Zone Management Act, the reserves represent a partnership program between NOAA and the coastal states. NOAA provides funding and national guidance, and each site is managed on a daily basis by a lead state agency or university with input from local partners.Direct data download | MetadataThis item is curated by the MarineCadastre.gov team. Find more information at marinecadastre.gov.