CIO defines IT processes and policies. The CIO defines the development processes, milestones, review gates, and the overall policies for all capital planning, enterprise architecture, and project management and reporting for IT resources. At a minimum, these processes shall ensure that the CIO certifies that IT resources are adequately implementing incremental development (as defined in the below definitions). The CIO should ensure that such processes and policies address each category of IT resources appropriately—for example, it may not be appropriate to apply the same process or policy to highly customized mission-specific applications and back office enterprise IT systems depending on the agency environment.

The documents contained in this dataset reflect NASA's comprehensive IT policy in compliance with Federal Government laws and regulations.

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.

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.

A manually curated registry of data policies from research funders, journal publishers, societies, and other organisations. These are linked to the databases and standards that they recommend for use

This data corresponds to the article "Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies" and covers 206 US universities classified as Carnegie "High" and "Very High" research levels. The dataset includes the following information for each school: basic demographics, basic information on library data services, existence of university data policy by type, and general information on policy contents where policy exists. Please see the data dictionary and the article for a full description of the dataset and its use.

As of December 2019, ** percent of adults in the United States do not want political campaigns to be able to micro-target them through digital ads. Respondents to a survey of U.S. adults reported that internet companies should make no information about its users available to political campaigns in order to target certain voters with online advertisements. Additionally, * percent of U.S. adults say that any information should be made available for a campaign's use.

Data supporting a paper titled "Do data management policies become more open over time?"The data includes three matrices created as part of a framework analysis. The Reasons and Adjectives data show a binary coding of whether a policy contains the term or idea. The Policies matrix contains values from 0 - 4 with 0 representing a very closed policy type and 4 representing a very open policy type. The details of these policies can be found in https://doi.org/10.31235/osf.io/gd4hp_v2Associated code can be found at: 10.25418/crick.28788704

By encouraging and requiring that authors share their data in order to publish articles, scholarly journals have become an important actor in the movement to improve the openness of data and the reproducibility of research. But how many social science journals encourage or mandate that authors share the data supporting their research findings? How does the share of journal data policies vary by discipline? What influences these journals’ decisions to adopt such policies and instructions? And what do those policies and instructions look like? We discuss the results of our analysis of the instructions and policies of 291 highly-ranked journals publishing social science research, where we studied the contents of journal data policies and instructions across 14 variables, such as when and how authors are asked to share their data, and what role journal ranking and age play in the existence and quality of data policies and instructions. We also attempt to compare our results to the results of other studies that have analyzed the policies of social science journals, although differences in the journals chosen and how each study defines what constitutes a data policy limit this comparison. We conclude that a little more than half of the journals in our study have data policies. A greater share of the economics journals have data policies and mandate sharing, followed by political science/international relations and psychology journals. Finally, we use our findings to make several recommendations: Policies should include the terms “data”, “dataset” or more specific terms that make it clear what to make available; policies should include the benefits of data sharing; journals, publishers, and associations need to collaborate more to clarify data policies; and policies should explicitly ask for qualitative data.

Mayor's Order 2017-115. District of Columbia Data Policy. Originating Agency: Office of the Mayor. 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.

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

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.

As of 2022, more than ** percent of countries in the WHO European region reported having legislation to protect the privacy of an individual's health-related data in electronic format in an electronic health record (EHR). Moreover, ** percent of countries have legislation allowing individuals electronic access to their health data in their EHRs.

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:

• Describe the differences in the State-level administration of SNAP and trends in the adoption of specific State-level SNAP policies,
• Examine how State policies affect household-level participation in SNAP, and
• Estimate the effect of SNAP participation on outcomes such as health and food spending by combining this data with nationally representative survey data. The SNAP Policy Database provides a potentially exogenous source of variation in program participation and can be used in instrumental variables estimation techniques.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: SNAP Policy Data Sets For complete information, please visit https://data.gov.

The Town of Dumfries' Open Data Policy summarizes its Purpose, Definitions, Open Data Program, Governance, Published Data, and Open Data Report and Review.

In December 2016 the City issued an Executive Order and CAO Data Policy No. 135 (https://nola.gov/chief-administrative-office/policies/policies/no-135-data-policy/) which mandates an annual report of the progress of the implementation of the policy and progress towards its goals.

The data consists in crawled privacy policies from European privacy policies. They were split into paragraphs and annotated as containing or not personal data.

The question that was asked to annotators was "Does this paragraph contain the explicit mention of specific personal data (e.g. name, phone number, social security, …) being collected?".

A full description of the dataset can be found in D3.4 of the SMOOTH project

Fundamentally approved policies

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., and the current database will be updated with new data as it becomes available.

The QoG Institute is an independent research institute within the Department of Political Science at the University of Gothenburg. Overall 30 researchers conduct and promote research on the causes, consequences and nature of Good Governance and the Quality of Government - that is, trustworthy, reliable, impartial, uncorrupted and competent government institutions. The main objective of our research is to address the theoretical and empirical problem of how political institutions of high quality can be created and maintained. A second objective is to study the effects of Quality of Government on a number of policy areas, such as health, the environment, social policy, and poverty. The dataset was created as part of a research project titled “Quality of Government and the Conditions for Sustainable Social Policy”. The aim of the dataset is to promote cross-national comparative research on social policy output and its correlates, with a special focus on the connection between social policy and Quality of Government (QoG). The data comes in three versions: one cross-sectional dataset, and two cross-sectional time-series datasets for a selection of countries. The two combined datasets are called “long” (year 1946-2009) and “wide” (year 1970-2005). The data contains six types of variables, each provided under its own heading in the codebook: Social policy variables, Tax system variables, Social Conditions, Public opinion data, Political indicators, Quality of government variables. QoG Social Policy Dataset can be downloaded from the Data Archive of the QoG Institute at http://qog.pol.gu.se/data/datadownloads/data-archive Its variables are now included in QoG Standard. Purpose: The primary aim of QoG is to conduct and promote research on corruption. One aim of the QoG Institute is to make publicly available cross-national comparative data on QoG and its correlates. The aim of the QoG Social Policy Dataset is to promote cross-national comparative research on social policy output and its correlates, with a special focus on the connection between social policy and Quality of Government (QoG). The dataset combining cross-sectional data and time-series data for a selection of 40 countries. The dataset is specifically tailored for the analysis of public opinion data over time, instead uses country as its unit of observation, and one variable for every 5th year from 1970-2005 (or, one per module of each public opinion data source). Samanni, Marcus. Jan Teorell, Staffan Kumlin, Stefan Dahlberg, Bo Rothstein, Sören Holmberg & Richard Svensson. 2012. The QoG Social Policy Dataset, version 4Apr12. University of Gothenburg:The Quality of Government Institute. http://www.qog.pol.gu.se