A listing of State Representatives and State Senators. For more information see: http://www.cga.ct.gov/asp/menu/legdownload.asp

FG: saar: CA: Less: Social Contributions data was reported at 2,137.603 USD bn in Mar 2018. This records an increase from the previous number of 2,111.206 USD bn for Dec 2017. FG: saar: CA: Less: Social Contributions data is updated quarterly, averaging 323.041 USD bn from Dec 1951 (Median) to Mar 2018, with 266 observations. The data reached an all-time high of 2,137.603 USD bn in Mar 2018 and a record low of 7.632 USD bn in Jun 1952. FG: saar: CA: Less: Social Contributions data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.AB079: Integrated Macroeconomic Accounts: Federal Government.

The Consumer Complaint Database is a collection of complaints about consumer financial products and services that we sent to companies for response. Complaints are published after the company responds, confirming a commercial relationship with the consumer, or after 15 days, whichever comes first. Complaints referred to other regulators, such as complaints about depository institutions with less than $10 billion in assets, are not published in the Consumer Complaint Database. The database generally updates daily.

This dataset provides information about public assets on the CT Open Data Portal. It includes datasets that meet the following criteria:

-Published on the data.ct.gov domain -Public -Official (ie published by a registered user) -Not a derived view

It includes assets that are currently published on the Open Data Portal and does not include assets that have been retired.

Government Revenue: Guangdong: Foshan data was reported at 76,708.000 RMB mn in 2024. This records a decrease from the previous number of 80,076.890 RMB mn for 2023. Government Revenue: Guangdong: Foshan data is updated yearly, averaging 43,821.280 RMB mn from Dec 2000 (Median) to 2024, with 23 observations. The data reached an all-time high of 80,825.870 RMB mn in 2021 and a record low of 5,953.000 RMB mn in 2000. Government Revenue: Guangdong: Foshan data remains active status in CEIC and is reported by Foshan Municipal Bureau of Statistics. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FC: Government Revenue: Prefecture Level City.

Ethical Data ManagementExecutive SummaryIn the age of data and information, it is imperative that the City of Virginia Beach strategically utilize its data assets. Through expanding data access, improving quality, maintaining pace with advanced technologies, and strengthening capabilities, IT will ensure that the city remains at the forefront of digital transformation and innovation. The Data and Information Management team works under the purpose:“To promote a data-driven culture at all levels of the decision making process by supporting and enabling business capabilities with relevant and accurate information that can be accessed securely anytime, anywhere, and from any platform.”To fulfill this mission, IT will implement and utilize new and advanced technologies, enhanced data management and infrastructure, and will expand internal capabilities and regional collaboration.Introduction and JustificationThe Information technology (IT) department’s resources are integral features of the social, political and economic welfare of the City of Virginia Beach residents. In regard to local administration, the IT department makes it possible for the Data and Information Management Team to provide the general public with high-quality services, generate and disseminate knowledge, and facilitate growth through improved productivity.For the Data and Information Management Team, it is important to maximize the quality and security of the City’s data; to develop and apply the coherent management of information resources and management policies that aim to keep the general public constantly informed, protect their rights as subjects, improve the productivity, efficiency, effectiveness and public return of its projects and to promote responsible innovation. Furthermore, as technology evolves, it is important for public institutions to manage their information systems in such a way as to identify and minimize the security and privacy risks associated with the new capacities of those systems.The responsible and ethical use of data strategy is part of the City’s Master Technology Plan 2.0 (MTP), which establishes the roadmap designed by improve data and information accessibility, quality, and capabilities throughout the entire City. The strategy is being put into practice in the shape of a plan that involves various programs. Although these programs was specifically conceived as a conceptual framework for achieving a cultural change in terms of the public perception of data, it basically covers all the aspects of the MTP that concern data, and in particular the open-data and data-commons strategies, data-driven projects, with the aim of providing better urban services and interoperability based on metadata schemes and open-data formats, permanent access and data use and reuse, with the minimum possible legal, economic and technological barriers within current legislation.Fundamental valuesThe City of Virginia Beach’s data is a strategic asset and a valuable resource that enables our local government carry out its mission and its programs effectively. Appropriate access to municipal data significantly improves the value of the information and the return on the investment involved in generating it. In accordance with the Master Technology Plan 2.0 and its emphasis on public innovation, the digital economy and empowering city residents, this data-management strategy is based on the following considerations.Within this context, this new management and use of data has to respect and comply with the essential values applicable to data. For the Data and Information Team, these values are:Shared municipal knowledge. Municipal data, in its broadest sense, has a significant social dimension and provides the general public with past, present and future knowledge concerning the government, the city, society, the economy and the environment.The strategic value of data. The team must manage data as a strategic value, with an innovative vision, in order to turn it into an intellectual asset for the organization.Geared towards results. Municipal data is also a means of ensuring the administration’s accountability and transparency, for managing services and investments and for maintaining and improving the performance of the economy, wealth and the general public’s well-being.Data as a common asset. City residents and the common good have to be the central focus of the City of Virginia Beach’s plans and technological platforms. Data is a source of wealth that empowers people who have access to it. Making it possible for city residents to control the data, minimizing the digital gap and preventing discriminatory or unethical practices is the essence of municipal technological sovereignty.Transparency and interoperability. Public institutions must be open, transparent and responsible towards the general public. Promoting openness and interoperability, subject to technical and legal requirements, increases the efficiency of operations, reduces costs, improves services, supports needs and increases public access to valuable municipal information. In this way, it also promotes public participation in government.Reuse and open-source licenses. Making municipal information accessible, usable by everyone by default, without having to ask for prior permission, and analyzable by anyone who wishes to do so can foster entrepreneurship, social and digital innovation, jobs and excellence in scientific research, as well as improving the lives of Virginia Beach residents and making a significant contribution to the city’s stability and prosperity.Quality and security. The city government must take firm steps to ensure and maximize the quality, objectivity, usefulness, integrity and security of municipal information before disclosing it, and maintain processes to effectuate requests for amendments to the publicly-available information.Responsible organization. Adding value to the data and turning it into an asset, with the aim of promoting accountability and citizens’ rights, requires new actions, new integrated procedures, so that the new platforms can grow in an organic, transparent and cross-departmental way. A comprehensive governance strategy makes it possible to promote this revision and avoid redundancies, increased costs, inefficiency and bad practices.Care throughout the data’s life cycle. Paying attention to the management of municipal registers, from when they are created to when they are destroyed or preserved, is an essential part of data management and of promoting public responsibility. Being careful with the data throughout its life cycle combined with activities that ensure continued access to digital materials for as long as necessary, help with the analytic exploitation of the data, but also with the responsible protection of historic municipal government registers and safeguarding the economic and legal rights of the municipal government and the city’s residents.Privacy “by design”. Protecting privacy is of maximum importance. The Data and Information Management Team has to consider and protect individual and collective privacy during the data life cycle, systematically and verifiably, as specified in the general regulation for data protection.Security. Municipal information is a strategic asset subject to risks, and it has to be managed in such a way as to minimize those risks. This includes privacy, data protection, algorithmic discrimination and cybersecurity risks that must be specifically established, promoting ethical and responsible data architecture, techniques for improving privacy and evaluating the social effects. Although security and privacy are two separate, independent fields, they are closely related, and it is essential for the units to take a coordinated approach in order to identify and manage cybersecurity and risks to privacy with applicable requirements and standards.Open Source. It is obligatory for the Data and Information Management Team to maintain its Open Data- Open Source platform. The platform allows citizens to access open data from multiple cities in a central location, regional universities and colleges to foster continuous education, and aids in the development of data analytics skills for citizens. Continuing to uphold the Open Source platform with allow the City to continually offer citizens the ability to provide valuable input on the structure and availability of its data. Strategic areasIn order to deploy the strategy for the responsible and ethical use of data, the following areas of action have been established, which we will detail below, together with the actions and emblematic projects associated with them.In general, the strategy pivots on the following general principals, which form the basis for the strategic areas described in this section.Data sovereigntyOpen data and transparencyThe exchange and reuse of dataPolitical decision-making informed by dataThe life cycle of data and continual or permanent accessData GovernanceData quality and accessibility are crucial for meaningful data analysis, and must be ensured through the implementation of data governance. IT will establish a Data Governance Board, a collaborative organizational capability made up of the city’s data and analytics champions, who will work together to develop policies and practices to treat and use data as a strategic asset.Data governance is the overall management of the availability, usability, integrity and security of data used in the city. Increased data quality will positively impact overall trust in data, resulting in increased use and adoption. The ownership, accessibility, security, and quality, of the data is defined and maintained by the Data Governance Board.To improve operational efficiency, an enterprise-wide data catalog will be created to inventory data and track metadata from various data sources to allow for rapid data asset discovery. Through the data catalog, the city will

This is a searchable historical collection of standards referenced in regulations - Voluntary consensus standards, government-unique standards, industry standards, and international standards referenced in the Code of Federal Regulations (CFR).

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The Electronic Code of Federal Regulations (e-CFR) is the codification of the general and permanent rules published in the Federal Register by the executive departments and agencies of the Federal Government. It is divided into 50 titles that represent broad areas subject to Federal regulation. The Electronic Code of Federal Regulations is updated daily. The Electronic Code of Federal Regulations and its accompanying XML data is not yet an official format of the Code of Federal Regulations. Only the PDF and Text versions of the annual Code of Federal Regulations have legal status as parts of the official online format of the Code of Federal Regulations. The XML-structured files are derived from SGML-tagged data and printing codes, which may produce anomalies in display. In addition, the XML data does not yet include image files. Users who require a higher level of assurance may wish to consult the official version of the Code of Federal Regulations or the daily Federal Register on FDsys.gov.

China Local Government Debt Outstanding: General data was reported at 10,993,875.000 RMB mn in 2018. This records an increase from the previous number of 10,363,179.000 RMB mn for 2017. China Local Government Debt Outstanding: General data is updated yearly, averaging 9,831,288.000 RMB mn from Dec 2014 (Median) to 2018, with 5 observations. The data reached an all-time high of 10,993,875.000 RMB mn in 2018 and a record low of 9,261,904.000 RMB mn in 2015. China Local Government Debt Outstanding: General data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FA: Government Debt: Local Government: Outstanding.

CN: Local Government Debt Issuance: ytd: General data was reported at 2,164,300.000 RMB mn in Oct 2018. This records an increase from the previous number of 2,035,600.000 RMB mn for Sep 2018. CN: Local Government Debt Issuance: ytd: General data is updated monthly, averaging 1,782,850.000 RMB mn from Dec 2015 (Median) to Oct 2018, with 14 observations. The data reached an all-time high of 3,549,516.000 RMB mn in Dec 2016 and a record low of 0.000 RMB mn in Jan 2018. CN: Local Government Debt Issuance: ytd: General data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under China Premium Database’s Government and Public Finance – Table CN.FA: Government Debt: Local Government: Issuance.

Brazil Public Sector: Last 12 Months Accumulated: Federal Government: Sources: External Borrowing data was reported at 33,655.202 BRL mn in Apr 2019. This records a decrease from the previous number of 47,137.493 BRL mn for Mar 2019. Brazil Public Sector: Last 12 Months Accumulated: Federal Government: Sources: External Borrowing data is updated monthly, averaging 11,817.578 BRL mn from Dec 2001 (Median) to Apr 2019, with 209 observations. The data reached an all-time high of 113,121.453 BRL mn in May 2015 and a record low of -68,050.132 BRL mn in Jan 2017. Brazil Public Sector: Last 12 Months Accumulated: Federal Government: Sources: External Borrowing data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Government and Public Finance – Table BR.FA024: Public Sector: Uses and Sources: Federal Government: Last 12 Months Accumulated.

A log of dataset alerts open, monitored or resolved on the open data portal. Alerts can include issues as well as deprecation or discontinuation notices.

This dataset is a subset of the statewide parcel dataset. The parcels in this dataset have been assigned a Government Ownership classification using the values "Federal", "State", "County Fee", "Tax Forfeit", or "Tribal" where it can be inferred from other fields in the parcel record. Only parcels from counties that have opted-in to sharing parcel data are included in this dataset.

For more information about the opt-in open parcel dataset, please refer to the opt-in open parcel compilation. https://gisdata.mn.gov/dataset/plan-parcels-open.

The State of Minnesota makes no representation or warranties, express or implied, with respect to the use or reuse of data provided herewith, regardless of its format or the means of its transmission. THE DATA IS PROVIDED “AS IS” WITH NO GUARANTEE OR REPRESENTATION ABOUT THE ACCURACY, CURRENCY, SUITABILITY, PERFORMANCE, MECHANTABILITY, RELIABILITY OR FITINESS OF THIS DATA FOR ANY PARTICULAR PURPOSE. This dataset is NOT suitable for accurate boundary determination. Contact a licensed land surveyor if you have questions about boundary determinations.

Abstract

The dataset was derived by the Bioregional Assessment Programme from multiple source datasets. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

Superseded by HUN AssetList v1.3 20150212 (GUID: dcf8349e-aaed-4d30-80ab-1c8cbad8fe68) on 2/12/2015

This dataset contains the spatial and non-spatial (attribute) components of the Hunter subregion Asset List as an .mdb file, which is readable as an MS Access database or as an ESRI Personal Geodatabase.

Under the BA program, a spatial assets database is developed for each defined bioregional assessment project. The spatial elements that underpin the identification of water dependent assets are identified in the first instance by regional NRM organisations (via the WAIT tool) and supplemented with additional elements from national and state/territory government datasets. A report on the WAIT process for the Hunter is included in the zip file as part of this dataset.

Elements are initially included in the preliminary assets database if they are partly or wholly within the subregion's preliminary assessment extent (Materiality Test 1, M1). Elements are then grouped into assets which are evaluated by project teams to determine whether they meet the second Materiality Test (M2). Assets meeting both Materiality Tests comprise the water dependent asset list. Descriptions of the assets identified in the Hunter subregion are found in the "AssetList" table of the database.

Assets are the spatial features used by project teams to model scenarios under the BA program. Detailed attribution does not exist at the asset level. Asset attribution includes only the core set of BA-derived attributes reflecting the BA classification hierarchy, as described in Appendix A of "AnR_database_HUN_v1p2_20150128.doc", located in the zip file as part of this dataset.

The "Element_to_Asset" table contains the relationships and identifies the elements that were grouped to create each asset.

Detailed information describing the database structure and content can be found in the document "AnR_database_HUN_v1p2_20150128.doc" located in the zip file.

Some of the source data used in the compilation of this dataset is restricted.

Purpose

The Asset List Database was developed to identify water dependent assets located within the Hunter subregion.

Dataset History

Superseded by HUN AssetList v1.3 20150212 (GUID: dcf8349e-aaed-4d30-80ab-1c8cbad8fe68) on 2/12/2015*****

This dataset is an update of the previous version of the Hunter asset list database: "Asset list for Hunter - CURRENT"; ID: 51b1e021-2958-4cd3-8daa-ba46ece09d1c, which was updated with the inclusion of data from NSW Department of Primary Industries - Office of Water: HIGH PROBABILITY GROUNDWATER DEPENDENT VEGETATION WITH HIGH ECOLOGICAL VALUE (Hunter-Central Rivers).

Dataset Citation

Bioregional Assessment Programme (2015) HUN AssetList Database v1p2 20150128. Bioregional Assessment Derived Dataset. Viewed 09 October 2018, http://data.bioregionalassessments.gov.au/dataset/64ecd565-bb7c-4f21-951e-f35966b91c99.

Dataset Ancestors

• Derived From NSW Office of Water Surface Water Entitlements Locations v1_Oct2013

• Derived From Communities of National Environmental Significance Database - RESTRICTED - Metadata only

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas

• Derived From Birds Australia - Important Bird Areas (IBA) 2009

• Derived From Hunter CMA GDEs (DRAFT DPI pre-release)

• Derived From NSW Office of Water Surface Water Licences Processed for Hunter v1 20140516

• Derived From NSW Office of Water Surface Water Offtakes - Hunter v1 24102013

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas (including WA)

• Derived From Asset list for Hunter - CURRENT

• Derived From Species Profile and Threats Database (SPRAT) - Australia - Species of National Environmental Significance Database (BA subset - RESTRICTED - Metadata only)

• Derived From Ramsar Wetlands of Australia

• Derived From Commonwealth Heritage List Spatial Database (CHL)

• Derived From GW Element Bores with Unknown FTYPE Hunter NSW Office of Water 20150514

• Derived From New South Wales NSW Regional CMA Water Asset Information WAIT tool databases, RESTRICTED Includes ALL Reports

• Derived From National Heritage List Spatial Database (NHL) (v2.1)

• Derived From Groundwater Entitlement Hunter NSW Office of Water 20150324

• Derived From NSW Office of Water combined geodatabase of regulated rivers and water sharing plan regions

• Derived From Australia World Heritage Areas

• Derived From NSW Office of Water GW licence extract linked to spatial locations for NorthandSouthSydney v3 13032014

• Derived From Groundwater Economic Elements Hunter NSW 20150520 PersRem v02

• Derived From Directory of Important Wetlands in Australia (DIWA) Spatial Database (Public)

• Derived From New South Wales NSW - Regional - CMA - Water Asset Information Tool - WAIT - databases

• Derived From Operating Mines OZMIN Geoscience Australia 20150201

• Derived From NSW Office of Water - National Groundwater Information System 20141101v02

• Derived From Groundwater Economic Assets Hunter NSW 20150331 PersRem

• Derived From Australia - Species of National Environmental Significance Database

• Derived From Monitoring Power Generation and Water Supply Bores Hunter NOW 20150514

• Derived From Northern Rivers CMA GDEs (DRAFT DPI pre-release)

• Derived From Australia, Register of the National Estate (RNE) - Spatial Database (RNESDB) Internal

• Derived From NSW Office of Water Groundwater Entitlements Spatial Locations

• Derived From NSW Office of Water Groundwater Licence Extract, North and South Sydney - Oct 2013

• Derived From NSW Office of Water - GW licence extract linked to spatial locations for North and South Sydney v2 20140228

• Derived From Collaborative Australian Protected Areas Database (CAPAD) 2010 (Not current release)

Graph and download economic data for Federal government current tax receipts: Taxes on production and imports: Customs duties (B235RC1Q027SBEA) from Q1 1959 to Q1 2025 about receipts, imports, tax, federal, production, government, GDP, and USA.

This dataset has been developed by the Australian Government as an authoritative source of indigenous location names across Australia. It is sponsored by the Spatial Policy Branch within the Department of Communications and managed solely by the Department of Human Services.

The dataset is designed to support the accurate positioning, consistent reporting, and effective delivery of Australian Government programs and services to indigenous locations.

The dataset contains Preferred and Alternate names for indigenous locations where Australian Government programs and services have been, are being, or may be provided. The Preferred name will always default to a State or Territory jurisdiction's gazetted name so the term 'preferred' does not infer that this is the locally known name for the location. Similarly, locational details are aligned, where possible, with those published in State and Territory registers.

This dataset is NOT a complete listing of all locations at which indigenous people reside. Town and city names are not included in the dataset. The dataset contains names that represent indigenous communities, outstations, defined indigenous areas within a town or city or locations where services have been provided.

Graph and download economic data for Federal Debt: Total Public Debt (GFDEBTN) from Q1 1966 to Q1 2025 about public, debt, federal, government, and USA.