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The SNAP Policy Database provides a central data source for information on State policy options in the Supplemental Nutrition Assistance Program (SNAP). The database includes information on State-level SNAP policies relating to eligibility criteria, recertification and reporting requirements, benefit issuance methods, availability of online applications, use of biometric technology (such as fingerprinting), and coordination with other low-income assistance programs. Data are provided for all 50 States and the District of Columbia for each month from January 1996 through December 2011.
The information in this database can facilitate research on factors that influence SNAP participation and on SNAP's effects on a variety of outcomes, such as health and dietary intake. More specifically, the database can be used to:
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. Yet there has been limited work to systematically evaluate the substantial variation in local COVID-19-related policies in the U.S. The objective of the U.S. COVID-19 County Policy (UCCP) Database is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies. The current data upload represents the first wave of data collection, which includes data on over 20 policies gathered across 171 counties in 7 states during January-March 2021. These include county-level COVID-19-related policies within 3 policy domains that are likely to affect a variety of health outcomes: (1) containment/closure, (2) economic support, and (3) public health. In ongoing work, we are conducting retrospective longitudinal weekly data collection for the period 2020-2021 from a larger swath of 300+ U.S. counties in all 50 states and Washington D.C. The current database will be updated with new data as it becomes available, in late 2023 or early 2024.Researchers who use this database for their studies should acknowledge the funders below in all publications.
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
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The Climate Policy Database collects information on currently adopted policies related to climate change mitigation from countries worldwide. The objective of the website is to provide an open, collaborative platform for information access, policy analysis and good-practice sharing. All data can be downloaded via the policies page.
Database compiling statistical data on national policies in USSR and Russia, collected by Ronald F. Inglehart Laboratory for Comparative Social Research at HSE University.
Sensitive Regulated Data: Permitted and Restricted UsesPurposeScope and AuthorityStandardViolation of the Standard - Misuse of InformationDefinitionsReferencesAppendix A: Personally Identifiable Information (PII)Appendix B: Security of Personally Owned Devices that Access or Maintain Sensitive Restricted DataAppendix C: Sensitive Security Information (SSI)
https://data.gov.tw/licensehttps://data.gov.tw/license
PRIDE is a numerical database, oriented to serve science and technology policy research. It collects and integrates indicator numerical data from Eurostat, OECD, WEF, World Bank and other international organizations and institutions, as well as domestic government agencies and other sources, to provide researchers with one - Convenient service of stop service.
Public Domain Mark 1.0https://creativecommons.org/publicdomain/mark/1.0/
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This dataset contains templates of policies and MoU's on data sharing. You can download the Word-templates and adapt the documents to your national context.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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A new database of 6124 policies at the intersection of agriculture and the environment. Implemented between 1960 and 2022 in over 200 countries. Comprises a wide range of types of policies (e.g., ranging from legislative changes to payments for ecosystem services), as well as a wide range of goals (e.g., from pesticide regulations to forest conservation). It allows to e.g. count such policies per country, filter to select specific policies, and to create policy indices, e.g. weighting countries' policies with contextual factors that enhance to hinder policy performance (e.g. policy budgets, enforcement, stringency, corruption).
The main database comes in the formats CSV, EXCEL, and DTA, country averages are provided in CSV and DTA, the dataset for the soil erosion policy analysis is provided in DTA and the code for the analysis is a DO-file.
A comprehensive data policy for the District of Columbia government. The data created and managed by the District government are valuable assets and are independent of the information systems in which the data reside.
Tempe Open Data Change Management and Data Retention Policies includes:Assess the extent of the changePrepare updated metadata and data dictionary
Use this guide to find information on Tempe data policy and standards.Open Data PolicyEthical Artificial Intelligence (AI) PolicyEvaluation PolicyExpedited Data Sharing PolicyData Sharing Agreement (General)Data Sharing Agreement (GIS)Data Quality Standard and ChecklistDisaggregated Data StandardsData and Analytics Service Standard
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
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About KEPD The KAPSARC Energy Policy Database (KEPD) is an open source policy database available to anyone interested in China's energy economy. It is intended to enable the researcher to quickly identify, summarize, and digest policy documents and specific policy measures. The KEPD captures a wide range of information about each individual policy contained within a single policy document enabling a variety of analyses. The database will be made available through an on-line portal at http://kepd.kapsarc.org
https://www.icpsr.umich.edu/web/ICPSR/studies/38908/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/38908/terms
The Child Care and Development Fund (CCDF) provides federal money to states and territories to provide assistance to low-income families, to obtain quality child care so they can work, attend training, or receive education. Within the broad federal parameters, States and Territories set the detailed policies. Those details determine whether a particular family will or will not be eligible for subsidies, how much the family will have to pay for the care, how families apply for and retain subsidies, the maximum amounts that child care providers will be reimbursed, and the administrative procedures that providers must follow. Thus, while CCDF is a single program from the perspective of federal law, it is in practice a different program in every state and territory. The CCDF Policies Database project is a comprehensive, up-to-date database of CCDF policy information that supports the needs of a variety of audiences through (1) analytic data files, (2) a project website and search tool, and (3) an annual report (Book of Tables). These resources are made available to researchers, administrators, and policymakers with the goal of addressing important questions concerning the effects of child care subsidy policies and practices on the children and families served. A description of the data files, project website and search tool, and Book of Tables is provided below: 1. Detailed, longitudinal analytic data files provide CCDF policy information for all 50 states, the District of Columbia, and the United States territories and outlying areas that capture the policies actually in effect at a point in time, rather than proposals or legislation. They capture changes throughout each year, allowing users to access the policies in place at any point in time between October 2009 and the most recent data release. The data are organized into 32 categories with each category of variables separated into its own dataset. The categories span five general areas of policy including: Eligibility Requirements for Families and Children (Datasets 1-5) Family Application, Terms of Authorization, and Redetermination (Datasets 6-13) Family Payments (Datasets 14-18) Policies for Providers, Including Maximum Reimbursement Rates (Datasets 19-27) Overall Administrative and Quality Information Plans (Datasets 28-32) The information in the data files is based primarily on the documents that caseworkers use as they work with families and providers (often termed "caseworker manuals"). The caseworker manuals generally provide much more detailed information on eligibility, family payments, and provider-related policies than the CCDF Plans submitted by states and territories to the federal government. The caseworker manuals also provide ongoing detail for periods in between CCDF Plan dates. Each dataset contains a series of variables designed to capture the intricacies of the rules covered in the category. The variables include a mix of categorical, numeric, and text variables. Most variables have a corresponding notes field to capture additional details related to that particular variable. In addition, each category has an additional notes field to capture any information regarding the rules that is not already outlined in the category's variables. Beginning with the 2020 files, the analytic data files are supplemented by four additional data files containing select policy information featured in the annual reports (prior to 2020, the full detail of the annual reports was reproduced as data files). The supplemental data files are available as 4 datasets (Datasets 33-36) and present key aspects of the differences in CCDF-funded programs across all states and territories as of October 1 of each year (2009-2022). The files include variables that are calculated using several variables from the analytic data files (Datasets 1-32) (such as copayment amounts for example family situations) and information that is part of the annual project reports (the annual Book of Tables) but not stored in the full database (such as summary market rate survey information from the CCDF plans). 2. The project website and search tool provide access to a point-and-click user interface. Users can select from the full set of public data to create custom tables. The website also provides access to the full range of reports and products released under the CCDF Policies Data
U.S. Government Workshttps://www.usa.gov/government-works
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The specifications and guidelines in this Data Management Plan will improve data consistency and availability of information. It will ensure that all levels of government and the public have access to the most up-to-date information; reduce or eliminate overlapping data requests and redundant data maintenance; ensure metadata is consistently created; and ensure that data services can be displayed by the consumer with the output of its choice.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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Following April 7, 2014 Executive Order from Mayor Walsh, an Open and Protected Data Policy was drafted to guide the City in defining, protecting, and ultimately making Open Data available and useful to the public. The policy provides working definitions for Open Data, along with information on how it is to be published, reviewed, and licensed.
(1) This is the dataset simulated by high resolution atmospheric model of which horizontal resolution is 60km-mesh over the globe (GCM), and 20km over Japan and surroundings (RCM), respetively. The climate of the latter half of the 20th century is simulated for 6000 years (3000 years for the Japan area), and the climates 1.5 K (*2), 2 K (*1) and 4 K warmer than the pre-industrial climate are simulated for 1566, 3240 and 5400 years, respectivley, to see the effect of global warming. (2) Huge number of ensembles enable not only with statistics but also with high accuracy to estimate the future change of extreme events such as typoons and localized torrential downpours. In addtion, this dataset provides the highly reliable information on the impact of natural disasters due to climate change on future societies. (3) This dataset provides the climate projections which adaptations against global warming are based on in various fields, for example, disaster prevention, urban planning, environmetal protection, and so on. It would realize the global warming adaptations consistent not only among issues but also among regions. (4) Total size of this dataset is 3 PB (3 x the 15th power of 10 bytes).
(*1) Datasets of the climates 2K warmer than the pre-industorial climate is available on 10th August, 2018. (*2) Datasets of the climates 1.5K warmer than the pre-industorial climate is available on 8th February, 2022.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The Global Welfare Dataset (GLOW) is a cross-national panel dataset that aims at facilitating comparative social policy research on the Global North and Global South. The database includes 381 variables on 61 countries from years between 1989 and 2015. The database has four main categories of data: welfare, development, economy and politics.The data is the result of an original data compilation assembled by using information from several international and domestic sources. Missing data was supplemented by domestic sources where available. We sourced data primarily from these international databases:Atlas of Social Protection Indicators of Resilience and Equity – ASPIRE (World Bank)Government Finance Statistics (International Monetary Fund)Social Expenditure Database – SOCX (Organisation for Economic Co-operation and Development)Social Protection Statistics – ESPROSS (Eurostat)Social Security Inquiry (International Labour Organization)Social Security Programs Throughout the World (Social Security Administration)Statistics on Income and Living Conditions – EU-SILC (European Union)World Development Indicators (World Bank)However, much of the welfare data from these sources are not compatible between all country cases. We conducted an extensive review of the compatibility of the data and computed compatible figures where possible. Since the heart of this database is the provision of social assistance across a global sample, we applied the ASPIRE methodology in order to build comparable indicators across European and Emerging Market economies. Specifically, we constructed indicators of average per capita transfers and coverage rates for social assistance programs for all the country cases not included in the World Bank’s ASPIRE dataset (Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, Netherlands, Norway, Poland, Portugal, Romania, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, and United Kingdom.)For details, please see:https://glow.ku.edu.tr/about
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
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The SPID data include information on the year of adoption for over 700 policies in the American states. For each policy we document the year of first adoption for each state. Adoption dates range from 1691 to 2017 and includes all fifty states. Policies are adopted by anywhere from 1 to 50 states, with an average of 25 adoptions. The data were assembled from a variety of sources, including academic publications and policy advocacy/information groups. Policies were coded according to the Policy Agendas Project major topic code. Version 1.2 includes a small number of corrections to the previous version. These are summarized in the documentation and listed in the changes spreadsheet.
Users can view brief descriptions of laws and policies pertaining to the health of students Topics include: wellness policy, health education curriculum, school meal programs, physical activity, emergency response, bullying, and facility safety, among others. Background The State School Health Policy Database was developed by the National Association of State Boards of Education and is supported by the Division of Adolescent and School Health of the Centers (DASH) of the Centers for Disease Control and Prevention (CDC) and the Robert Wood Johnson Foundation. This database is useful for school policymakers interested in viewing strategies and policies across states and researchers and policy evaluators seeking to track changes in polici es across the United States. Topics include: wellness policies, health education curriculum; school meal programs, school food environment, physical activity, drug-free schools, bullying, emergency response, tobacco use, air quality, pesticide use, and facility safety. User Functionality Users can view brief descriptions of laws and policies pertaining to the health of students. When possible, hyperlinks to full written policies are included. Data Notes The data base is updated regularly with new and revised laws and policies from across the United States.
This dataset provides a central data source for information on State policy options in the Supplemental Nutrition Assistance Program (SNAP). SNAP (Supplemental Nutrition Assistance Program) offers nutrition assistance to millions of eligible, low-income individuals and families and provides economic benefits to communities. FNS (Food and Nutrition Service) also works with State partners and the retail community to improve program administration and ensure program integrity.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The SNAP Policy Database provides a central data source for information on State policy options in the Supplemental Nutrition Assistance Program (SNAP). The database includes information on State-level SNAP policies relating to eligibility criteria, recertification and reporting requirements, benefit issuance methods, availability of online applications, use of biometric technology (such as fingerprinting), and coordination with other low-income assistance programs. Data are provided for all 50 States and the District of Columbia for each month from January 1996 through December 2011.
The information in this database can facilitate research on factors that influence SNAP participation and on SNAP's effects on a variety of outcomes, such as health and dietary intake. More specifically, the database can be used to: