A listing of each of Connecticut's 169 municipalities indicating both the form of local government (such as Mayor-Council) and the Term in years for the Chief Elected Official Updated annually as part of OPM's Municipal Fiscal Indicators report

Between January 18 and November 2023, a quarter of data breach incidents in the United States government happened at city administration offices. A further 17 percent of the incidents involved counties, while law enforcement agencies encountered 14 percent of the data breaches.

Success.ai’s Governmental and Congressional Data with Contact Data for Government Professionals Worldwide provides businesses, organizations, and institutions with verified contact information for key decision-makers in public sector roles. Sourced from over 170 million verified professional profiles, this dataset includes work emails, direct phone numbers, and LinkedIn profiles for government officials, administrators, policy advisors, and other influential leaders. Whether you’re targeting local municipalities, national agencies, or international government bodies, Success.ai delivers accurate, up-to-date data to help you engage effectively with public sector stakeholders.

Why Choose Success.ai’s Government Professionals Data?

1. Comprehensive Contact Information
2. Access verified work emails, phone numbers, and LinkedIn profiles of government professionals worldwide.

3. AI-driven validation ensures 99% accuracy, giving you confidence in the reliability and precision of the data.

4. Global Reach Across Public Sectors

5. Includes profiles of elected officials, policy advisors, department heads, procurement managers, and regulatory authorities.

6. Covers regions such as North America, Europe, Asia-Pacific, South America, and the Middle East, enabling true global engagement.

7. Continuously Updated Datasets

8. Real-time updates ensure your outreach remains timely, relevant, and aligned with current roles and responsibilities.

9. Ethical and Compliant

10. Adheres to GDPR, CCPA, and other global data privacy regulations, ensuring ethical, lawful use of all contact data.

Data Highlights:

• 170M+ Verified Professional Profiles: Includes government decision-makers and influential public sector leaders worldwide.
• 50M Work Emails: AI-validated for accuracy and easy communication.
• 30M Company (Agency/Institution) Profiles: Offers insights into various government departments, agencies, and organizations.
• 700M Global Professional Profiles: Enriched datasets to support a wide range of outreach and strategic initiatives.

Key Features of the Dataset:

1. Government Decision-Maker Profiles
2. Identify and connect with officials responsible for policy-making, budget approvals, program implementation, and public procurement.

3. Engage with professionals who influence legislation, infrastructure projects, and community development initiatives.

4. Advanced Filters for Precision Targeting

5. Filter by geographic jurisdiction, agency type, policy focus, job title, and more to reach the right government professionals.

6. Tailor your campaigns to align with specific public interests, regulatory frameworks, or service areas.

7. AI-Driven Enrichment

8. Profiles are enriched with actionable data, providing deeper insights that help you tailor your messaging and improve engagement success rates.

Strategic Use Cases:

1. Policy and Advocacy Outreach
2. Reach policymakers, advisors, and regulators to advocate for policy changes, present research findings, or share best practices.

3. Engage with officials who have the authority to influence regulations and legislative outcomes.

4. Procurement and Vendor Relations

5. Connect with procurement managers and government buyers seeking solutions, products, or services.

6. Present technology, infrastructure, or consulting offerings to decision-makers managing public tenders and supplier relationships.

7. Public-Private Partnerships

8. Identify and connect with key stakeholders involved in PPP initiatives, infrastructure projects, and long-term strategic collaborations.

9. Expand your network within government circles to foster joint ventures and co-development opportunities.

10. Market Research and Strategic Planning

11. Utilize government contact data for in-depth market research, stakeholder analysis, and feasibility assessments.

12. Gather insights from regulators, policy experts, and department heads to inform business strategies.

Why Choose Success.ai?

1. Best Price Guarantee

2. Access premium-quality verified data at competitive prices, ensuring you achieve the best value for your outreach efforts.

3. Seamless Integration

4. Integrate verified government contact data into your CRM or marketing platforms via APIs or customizable downloads, streamlining your data management.

5. Data Accuracy with AI Validation

6. Count on 99% accuracy to inform your decision-making and improve the effectiveness of each interaction.

7. Customizable and Scalable Solutions

8. Tailor datasets to specific government tiers, agency types, or policy areas to meet unique organizational requirements.

APIs for Enhanced Functionality:

1. Data Enrichment API

2. Enhance your existing records with verified government contact data, refining targeting and personalization efforts.

3. Lead Generation API

4. Automate lead generation, ensuring efficient scaling of your outreach and saving time a...

Ranked categories of data based on government respondents' rating of what is important to publish. Results are presented in terms of %, for all types of government combined.

Respondents multi-selected between 6 choices to identify the main motivation for starting a data transparency initiative. Results can be grouped by country, type of government org and role of respondent. Choices included "no initiative" to account for those who did not have one.

Types of approved legal experience for the year 2023

Types of approved legal expertise 2020-2022

Although Lijphart's typology of consensus and majoritarian democracy can be regarded as the most widely used tool to classify democratic regimes, it has been rarely applied to Latin America so far. We try to fill this gap by adapting Lijphart's typological framework to the Latin American context in the following way. In contrast to previous studies, we treat the type of democracy as an independent variable and include informal factors such as clientelism or informal employment in our assessment of democratic patterns. On this basis, we aim to answer the following questions. First, how did the patterns of democracy evolve in Latin America over the two decades between 1990 and 2010 and what kind of differences can be observed in the region? Second, what are the institutional determinants of the observed changes? We focus on the emergence of new parties because of their strong impact on the first dimension of Lijphart's typology. From our observations we draw the following tentative conclusions: If strong new parties established themselves in the party system but failed to gain the presidency, they pushed the system towards consensualism. Conversely, new parties that gained the presidency produced more majoritarian traits.

United States Google Search Trends: Government Measures: Government Subsidy data was reported at 0.000 Score in 30 Nov 2025. This stayed constant from the previous number of 0.000 Score for 29 Nov 2025. United States Google Search Trends: Government Measures: Government Subsidy data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 30 Nov 2025, with 1461 observations. The data reached an all-time high of 0.000 Score in 30 Nov 2025 and a record low of 0.000 Score in 30 Nov 2025. United States Google Search Trends: Government Measures: Government Subsidy data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s United States – Table US.Google.GT: Google Search Trends: by Categories.

Global Government Open Data Management Platform Market size was valued at USD 1.75 Billion in 2024 and is projected to reach USD 3.38 Billion by 2032, growing at a CAGR of 8.54% from 2026 to 2032.

Global Government Open Data Management Platform Market Drivers

Increasing Demand for Transparency and Accountability: There is a growing public demand for transparency in government operations, which drives the adoption of open data initiatives. According to a survey by the World Bank, 85% of respondents in various countries indicated that transparency in government decisions is crucial for reducing corruption, prompting governments to implement open data platforms.

Technological Advancements: Rapid advancements in information and communication technology (ICT) facilitate the development and deployment of open data management platforms. The International Telecommunication Union (ITU) reported that global Internet penetration reached approximately 64% in 2023, enabling more citizens to access open data and engage with government services online.

Government Initiatives and Policies: Many governments are actively promoting open data through policies and initiatives. For instance, the U.S. government's Open Data Initiative, launched in 2013, has led to the publication of over 300,000 datasets on Data.gov. Additionally, the European Union's Open Data Directive, which aims to make public sector data available, is further encouraging governments to embrace open data practices.

A searchable index of many governments' open data catalogues.

Percentage of respondents, in each level of government, who chose a specific obstacle as the main challenge to data transparency/ open data.

Types of accredited legal experience 2021

Over the summer of 2013, the Cabinet Office started to develop the processes to support the maintenance of a dynamic NII. We can now launch a first iteration which will be the basis for user feedback and the identification of additional datasets. The processes for defining the NII can be broadly outlined as follows: a) Identifying and maintaining an inventory of data held by government; b) Prioritising data to be included in the NII; and c) Supporting organisations to release data, where possible. The Cabinet Office has developed an over-arching framework for the NII to be used as a “thinking tool” in engaging with the NII. Without this framework it will be hard to communicate the function and benefits of the NII. The framework combines a high-level categorisation of government data and characteristics of different types of data to provide a framework for the processes and identify early candidates for inclusion in the NII. The data themes in the framework for the NII relate primarily to characteristics of the organisation which hold the data and also reflect the high level categories of data in the G8 Open Data Charter. Transparency was one of the key three priorities of the recent G8, chaired by the UK where all G8 Leaders signed up to a set of principles specified in an Open Data Charter. G8 members identified 14 high-value areas, jointly regarded as data that will help unlock the economic potential of open data, support and encourage innovation, and provide greater accountability to improve our democracies. The UK has aligned these categories to inform the creation of its NII. Datasets listed against Transport and Infrastructure include datasets owned and held by government agencies, ALBs and the wider transport industry, reflecting the organisation of information in the sector. Overlaying these data themes, we have analysed user feedback, ODUG benefits cases, applications and services which successfully use government data, and expert feedback to develop 4 primary uses of data. These are: a) Location: Geospatial data which can inform mapping and planning. b) Performance and Delivery: Data which shows how effectively public bodies and services are fulfilling their public tasks and the delivery of policy. c) Fiscal: Government spend, procurement and contractual data as well as data about the financial management of public sector activities. This also includes data that government holds about companies which may be of value to users. d) Operational: Data about the operational structure, placement of public service delivery points and the nature of the resources available within each of them.

Types of local government organisations in the United Kingdom Registers - Registers are lists of information. Each register is the most reliable list of its kind. If you wish to know more about registers, please visit the registers guidance at https://www.gov.uk/government/publications/registers/registers Fields in this register - local-authority-type, name, start-date, end-date

This paper attempts to describe and explain the long-term evolution of wage inequality in imperial China, covering over two millennia from the Han dynasty to the Qing dynasty (202 BCE-1912 CE). Based on historical government records of official salaries, commodity prices, and agricultural productivity, we convert various forms of salaries to equivalent rice volumes and comparable salary benchmarks. Wage inequality is measured by salary ratios and (partial) Gini coefficients between official and peasant classes as well as within the official class. The inter-class wage inequality features an “inverted U-u” pattern—first rose before the Tang dynasty and then declined afterwards (the “inverted U” trends) with “inverted u” dynastic cycles. The intra-class wage inequality has a secular decline trend. We propose a unified framework incorporating technological, institutional, political, and social (TIPS) mechanisms to explain both long-term and short-term patterns. It is concluded that the technological mechanism dominated the rise of wage inequality, while the political mechanism (emperor-bureaucracy power tensions) drove the decline.

These are the various 2-digit GAAP fund types and their titles under which GAAP Funds are consolidated for financial reporting. GAAP Fund Types are used to report consolidated fund activity for presentation on the Texas Comprehensive Annual Financial Report, according to Generally Accepted Accounting Principles (GAAP).

Context

The Open Data 500, funded by the John S. and James L. Knight Foundation (http://www.knightfoundation.org/) and conducted by the GovLab, is the first comprehensive study of U.S. companies that use open government data to generate new business and develop new products and services.

Study Goals

• Provide a basis for assessing the economic value of government open data

• Encourage the development of new open data companies

• Foster a dialogue between government and business on how government data can be made more useful

The Govlab's Approach

The Open Data 500 study is conducted by the GovLab at New York University with funding from the John S. and James L. Knight Foundation. The GovLab works to improve people’s lives by changing how we govern, using technology-enabled solutions and a collaborative, networked approach. As part of its mission, the GovLab studies how institutions can publish the data they collect as open data so that businesses, organizations, and citizens can analyze and use this information.

Company Identification

The Open Data 500 team has compiled our list of companies through (1) outreach campaigns, (2) advice from experts and professional organizations, and (3) additional research.

Outreach Campaign

• Mass email to over 3,000 contacts in the GovLab network

• Mass email to over 2,000 contacts OpenDataNow.com

• Blog posts on TheGovLab.org and OpenDataNow.com

• Social media recommendations

• Media coverage of the Open Data 500

• Attending presentations and conferences

Expert Advice

• Recommendations from government and non-governmental organizations

• Guidance and feedback from Open Data 500 advisors

Research

• Companies identified for the book, Open Data Now

• Companies using datasets from Data.gov

• Directory of open data companies developed by Deloitte

• Online Open Data Userbase created by Socrata

• General research from publicly available sources

What The Study Is Not

The Open Data 500 is not a rating or ranking of companies. It covers companies of different sizes and categories, using various kinds of data.

The Open Data 500 is not a competition, but an attempt to give a broad, inclusive view of the field.

The Open Data 500 study also does not provide a random sample for definitive statistical analysis. Since this is the first thorough scan of companies in the field, it is not yet possible to determine the exact landscape of open data companies.

Municipal Fiscal Indicators is an annual compendium of information compiled by the Office of Policy and Management, Office of Finance, Municipal Finance Services Unit (MFS). The data contained in Indicators provides key financial and demographic information on municipalities in Connecticut.

Municipal Fiscal Indicators contains the most current financial data available for each of Connecticut's 169 municipalities. The majority of this data was compiled from the audited financial statements that are filed annually with the State of Connecticut, Office of Policy and Management, Office of Finance. This database of information includes selected demographic and economic data relating to, or having an impact upon, a municipality’s financial condition. The most recent edition is for the Fiscal Years Ended 2015-2019 published in April 2021.

Data on the Municipal Fiscal Indicators is included in the following datasets:

Municipal Fiscal Indicators, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-2019/sb4i-6vik

Municipal Fiscal Indicators: Grand List Components, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Grand-List-Components-/ifrb-kp2b

Municipal Fiscal Indicators: Pension Funding Information For Defined Benefit Pension Plans, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Pension-Funding-Inform/civu-w22d

Municipal Fiscal Indicators: Type and Number of Pension Plans, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Type-and-Number-of-Pen/9f65-c4yr

Municipal Fiscal Indicators: Other Post-Employment Benefits (OPEB), 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Other-Post-Employment-/sa26-46h8

Municipal Fiscal Indicators: Economic and Grand List Data, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Economic-and-Grand-Lis/wpbp-b657

Municipal Fiscal Indicators: Benchmark Labor Data, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Benchmark-Labor-Data-2/db37-h23r

Municipal Fiscal Indicators: Unemployment, 2019 https://data.ct.gov/Local-Government/Municipal-Fiscal-Indicators-Unemployment-2019/cugp-2za3