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.

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 data.gov.au Dataset Ontology is an OWL ontology designed to describe the characteristics of datasets published on data.gov.au.

The ontology contains elements which describe the publication, update, origin, governance, spatial and temporal coverage and other contextual information about the dataset. The ontology also covers aspects of organisational custodianship and governance.

By using this ontology to describe datasets on data.gov.au publishers increase discoverability and enable the consumption of this information in other applications/systems as Linked Data. It further enables decentralised publishing of catalogs and facilitates federated dataset search across sites, e.g. in datasets that are published by the States.

Other publishers of Linked Data may make assertions about data published using this ontology, e.g. they may publish information about the use of the dataset in other applications.

Search for a business by name. You can obtain business information and then proceed to purchase a certificate of good standing or other documents. The purpose of this search is simply to determine whether a company/entity exists and to provide basic information on the company/entity.

This dataset contains the count of all vehicles registered in the ACT. The information is aggregated by make, model, body type and colour. This information includes trailers and motorbikes. The data presented is point in time either on or before the Data Last Updated date. Data Quality Whilst every effort has been made to ensure this information is accurate, there may be instances where words are misspelt, or attributes are incorrect. System improvements should see these instances reduce over time. Disclaimer No claim is made as to the accuracy or currency of the content at any time. This data is provided on the basis that users undertake responsibility for assessing the relevance and accuracy of its content. We accept no liability to any person or group for the data or advice (or the use of such data or advice) which is provided or incorporated into it by reference.

This dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development.Data Source Type: ESRI ArcGIS Enterprise GeodatabasePreparation Method: N/APublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

The Government is committed to increasing transparency across Whitehall and local Authorities. The first step for central Government departments is to publish on-line items of spend over £25,000 from April 2010 onwards. However at The NHS Information Centre we believe that we should start to release as much information as soon as possible and we will publish details of all of our invoices paid which total over £500. The information will be published on a monthly basis by the 15th working day. Publication of these lists forms part of The NHS Information Centre's commitment to be open and transparent with the wider public. For data protection reasons, where payments have been made to individuals, the names have been replaced with the word 'Redacted'.

NOTE: This dataset is updated weekly. Please ensure that you use the most up-to-date version.

The Australian Charities and Not-for-profits Commission (ACNC) is Australia’s national regulator of charities.

Since 3 December 2012, charities wanting to access Commonwealth charity tax concessions (and other benefits), need to register with the ACNC. Although many charities choose to register, registration with the ACNC is voluntary.

Each financial year, registered charities are required to lodge an Annual Information Statement (AIS) with the ACNC. Charities are required to submit their AIS within six months of the end of their reporting period.

Registered charities can apply to the ACNC to have some or all of the information they provide withheld from the ACNC Register. There are only limited circumstances when the ACNC can agree to withhold information, including if the information:

• is commercially sensitive and could cause harm
• is false, confusing or misleading
• is offensive
• could endanger public safety
• falls within the circumstances allowed by the regulations (such as if the information identifies a private donor in relation to a private ancillary fund).

If a charity has applied to have their data withheld, the AIS data relating to that charity has been excluded from this dataset.

The AIS information for individual charities can be viewed at www.acnc.gov.au/charity.

This dataset can be used to find the AIS information lodged by multiple charities. It can also be used to filter and sort by different variables across all AIS information.

The 2017 AIS collects information about charity finances, and financial information provides a basis for understanding the charity and its activities in greater detail. However, it is easy to misunderstand a charity's financial position or performance by judging it solely on its financial information.

When comparing charities’ financial information it is important to consider each charity's unique situation. This is particularly true for small charities, which are not compelled to provide financial reports – reports that often contain more details about their financial position and activities – as part of their AIS.

For more information on interpreting financial information, please refer to the ACNC website.

The ACNC also publishes other datasets on data.gov.au as part of our commitment to open data and transparent regulation. Please click here to view them.

NOTE: It is possible that some information in this dataset might be subject to a future request from a charity to have their information withheld. If this occurs, this information will still appear in the dataset until the next update.

Please consider this risk when using this dataset.

Please use the attached explanatory notes to help with analysis of this dataset.

Abstract

\[x\[This dataset was superseded by GIP AssetList Database v1.3 20150212

GUID: e0a8bc96-e97b-44d4-858e-abbb06ddd87f

on 12/2/2015\]x\]

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.

This dataset contains the spatial and non-spatial (attribute) components of the Gippsland bioregion Asset List as two .mdb files, which are 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. All reports received associated with the WAIT process for Gippsland are 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 bioregion'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 Gippsland bioregion are found in the "AssetList" table of the database. In this version of the database only M1 has been assessed.

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 "AssetList_database_GIP_v1p2_20150130.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 "AssetList_database_GIP_v1p2_20150130.doc" located in the zip file.

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

Purpose

\[x\[\\\\\THIS IS NOT THE CURRENT ASSET LIST\\\\\

This dataset was superseded by GIP AssetList Database v1.3 20150212

GUID: e0a8bc96-e97b-44d4-858e-abbb06ddd87f

on 12/2/2015

THIS DATASET IS NOT TO BE PUBLISHED IN ITS CURRENT FORM\]x\]

Dataset History

This dataset is an update of the previous version of the Gippsland asset list database: "Gippsland Asset List V1 20141210"; ID: 112883f7-1440-4912-8fc3-1daf63e802cb, which was updated with the inclusion of a number of additional datasets from the Victorian Department of the Environment and Primary Industries as identified in the "linkages" section and below.

Victorian Farm Dam Boundaries

https://data.bioregionalassessments.gov.au/datastore/dataset/311a47f9-206d-4601-aa7d-6739cfc06d61

Flood Extent 100 year extent West Gippsland Catchment Management Authority GIP v140701

https://data.bioregionalassessments.gov.au/dataset/2ff06a4f-fdd5-4a34-b29a-a49416e94f15

Irrigation District Department of Environment and Primary Industries GIP

https://data.bioregionalassessments.gov.au/datastore/dataset/880d9042-abe7-4669-be3a-e0fbe096b66a

Landscape priority areas (West)

West Gippsland Regional Catchment Strategy Landscape Priorities WGCMA GIP 201205

https://data.bioregionalassessments.gov.au/datastore/dataset/6c8c0a81-ba76-4a8a-b11a-1c943e744f00

Plantation Forests Public Land Management(PLM25) DEPI GIP 201410

https://data.bioregionalassessments.gov.au/datastore/dataset/495d0e4e-e8cd-4051-9623-98c03a4ecded

and additional data identifying "Vulnerable" species from the datasets:

Victorian Biodiversity Atlas flora - 1 minute grid summary

https://data.bioregionalassessments.gov.au/datastore/dataset/d40ac83b-f260-4c0b-841d-b639534a7b63

Victorian Biodiversity Atlas fauna - 1 minute grid summary

https://data.bioregionalassessments.gov.au/datastore/dataset/516f9eb1-ea59-46f7-84b1-90a113d6633d

A number of restricted datasets were used to compile this database. These are listed in the accompanying documentation and below:

• The Collaborative Australian Protected Areas Database (CAPAD) 2010

• Environmental Assets Database (Commonwealth Environmental Water Holder)

• Key Environmental Assets of the Murray-Darling Basin

• Communities of National Environmental Significance Database

• Species of National Environmental Significance

• Ramsar Wetlands of Australia 2011

Dataset Citation

Bioregional Assessment Programme (2015) GIP AssetList Database v1.2 20150130. Bioregional Assessment Derived Dataset. Viewed 07 February 2017, http://data.bioregionalassessments.gov.au/dataset/6f34129d-50a3-48f7-996c-7a6c9fa8a76a.

Dataset Ancestors

• Derived From Flood Extent 100 year extent West Gippsland Catchment Management Authority GIP v140701

• Derived From Surface Water Economic Entitlements GIP 20141219

• Derived From West Gippsland Regional Catchment Strategy Landscape Priorities WGCMA GIP 20121205

• Derived From Irrigation District Department of Environment and Primary Industries GIP

• Derived From Surface Water and Groundwater Entitlement Data with Volumes - DEPI Regs Cat6 Victoria 20141218

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

• Derived From National Groundwater Dependent Ecosystems (GDE) Atlas

• Derived From Victorian Water Supply Protection Areas

• Derived From National Groundwater Information System (NGIS) v1.1

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

• Derived From Southern Rural Water SW Locations with BOM Regulations Category 6 Volumes Gippsland 20150430

• Derived From Gippsland Project boundary

• Derived From Victorian Groundwater Management Areas

• Derived From Plantation Forests Public Land Management(PLM25) DEPI GIP 201410

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

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

• Derived From Surface Water Entitlement Locations Gippsland Southern Rural Water 20141218

• Derived From Ramsar Wetlands of Australia

• Derived From National Groundwater Information System Victorian Extract (2014-03-21)

• Derived From GEODATA TOPO 250K Series 3

• Derived From Groundwater Licences Entitlement Volume To Bores Vic DEPI 20141021

• Derived From Groundwater Economic Elements Gippsland 20141120

• Derived From Commonwealth Heritage List Spatial Database (CHL)

• Derived From Potential Groundwater Dependent Ecosystems for West Gippsland Catchment Management Authority

• Derived From Victorian Biodiversity Atlas flora - 1 minute grid summary

• Derived From Unreg surface water licences DELWP Gippsland 20150301

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

• Derived From Gippsland Basin bioregion Asset List v01 - 20141210

• Derived From Victorian Farm Dam Boundaries

• Derived From Gippsland Basin bioregion Preliminary Assessment Extent (PAE)

• Derived From [Victoria Regional CMA - Water Asset Information Tool - WAIT

This is a collection of data sets, compiled by remit to assist regional managers in assessing inspection activities and outcomes in their areas. They contain information on key inspection judgements and some other provider information. The same information is reflected in official statistics which are published subsequently on the Ofsted website.

Data collected on schools for the administration of statutory assessments including test order information. The data will include location/geographical information such as addresses and postcodes. The data is extracted from Edubase (www.education.gov.uk/edubase), a publically available portal, on a regular basis before being used within STA. The data does not include any financial data.

This record is for Approval for Access product AfA214. Water temperature data is collected and stored by the Environment Agency for different reasons and in different locations. Time series of surface water temperatures can provide indicators of climate change and associated ecological responses. An archive was created in 2007 as part of a research project (SC070035), and is a unique collation of the Environment Agency’s water temperature data from more than 30,000 sites across England & Wales. The archive contains water temperature data (up to 2007) and site metadata. Most sites have records starting from the 1980s. The water temperature data are available in two main types; spot samples from routine monitoring (e.g. monthly) and high resolution samples (e.g. every 15 minutes). The database was created using Microsoft Access 2003 but has a simple query based front end. As part of the science project about 1 in 10 sites were analysed to assess trends, and images of these graphs are embedded within the archive and linked to sites for information. The archive can be interrogated to find out where water temperature data exist, how frequently sampling occurs and the length of each record. In addition, sites have information about water body type e.g. river, lake or canal. This dataset is available on DVD. INFORMATION WARNING Within these data: Site Operator means 'monitoring organisation'; Source Info – relates to the time the information was provided. Attribution statement: © Environment Agency copyright and/or database right 2015. All rights reserved.

The ERIC (Estates Return Information Collection) is collected and published here by the HSCIC on behalf of the Department of Health. It is the main central data collection for estates and facilities services from the NHS containing information dating back to 1999/2000 and will be added to as future returns are completed. The data provided enables the analysis of Estates & Facilities information from NHS Trusts and PCTs in England which is a compulsory requirement that NHS Trusts submit an Estates Return. The data is as provided by reporting organisations and has not been amended. The accuracy and completeness is the responsibility of the reporting organisations. This dataset is at trust-level. To obtain a complete picture, site-level data should also be accessed (see additional links). Note that trust-level data is a different collection to site-level, rather than site-level totals.

ScoffTow Case Information Why is this data collected? - To keep track of vehicles that have been booted or towed due to non-payment of judgment debt. How is this data collected? - DOF received notification whenever a vehicle is Booted or towed by the Sheriff's Department or the Marshal's Office. What does each record represent? - Each row represents a single ScoffTow case. How can this data be used? - To view salient information pertaining to each scfftow case. What are the idiosyncrasies or limitations of the data to be aware of? - Information is only accurate up to the time of collection.

This data contains all Corporations and Other Entity filings in the Department of State electronic database. Each record contains the Department of State ID number, Filing ID, Date Filed, Effective Date, Entity Name, the law under which the filing was made and other pertinent filing information.

This table contains data on the percent of population age 25 and up with a four-year college degree or higher for California, its regions, counties, county subdivisions, cities, towns, and census tracts. Greater educational attainment has been associated with health-promoting behaviors including consumption of fruits and vegetables and other aspects of healthy eating, engaging in regular physical activity, and refraining from excessive consumption of alcohol and from smoking. Completion of formal education (e.g., high school) is a key pathway to employment and access to healthier and higher paying jobs that can provide food, housing, transportation, health insurance, and other basic necessities for a healthy life. Education is linked with social and psychological factors, including sense of control, social standing and social support. These factors can improve health through reducing stress, influencing health-related behaviors and providing practical and emotional support. More information on the data table and a data dictionary can be found in the Data and Resources section. The educational attainment table is part of a series of indicators in the Healthy Communities Data and Indicators Project (HCI) of the Office of Health Equity. The goal of HCI is to enhance public health by providing data, a standardized set of statistical measures, and tools that a broad array of sectors can use for planning healthy communities and evaluating the impact of plans, projects, policy, and environmental changes on community health. The creation of healthy social, economic, and physical environments that promote healthy behaviors and healthy outcomes requires coordination and collaboration across multiple sectors, including transportation, housing, education, agriculture and others. Statistical metrics, or indicators, are needed to help local, regional, and state public health and partner agencies assess community environments and plan for healthy communities that optimize public health. More information on HCI can be found here: https://www.cdph.ca.gov/Programs/OHE/CDPH%20Document%20Library/Accessible%202%20CDPH_Healthy_Community_Indicators1pager5-16-12.pdf The format of the educational attainment table is based on the standardized data format for all HCI indicators. As a result, this data table contains certain variables used in the HCI project (e.g., indicator ID, and indicator definition). Some of these variables may contain the same value for all observations.

This operations dashboard shows historic and current data related to this performance measure.The performance measure dashboard is available at 2.21 Availability of City Information. Data Dictionary

This dataset contains a sample of the broadcast Traveler Information Messages (TIM) being generated by the Wyoming Connected Vehicle (CV) Pilot. This dataset only contains SchemaVersion 6 TIM sample data from December 18, 2018 to present. It is updated hourly and will hold up to 3 million of the most recent TIM records. The Schema Version 6 data is described further here. For sample TIM data prior to December 18, 2018, please refer to the Schema Version 5 dataset. The full set of TIMs can be found in the ITS Sandbox.

This Management Information (MI) site is a compilation of data reporting a variety of work measurements from the DDS perspective, and plays a key role in the effective management of SSA's disability program. Our goal is to deliver a MI application which will be easy to use and have information available to monitor workloads, processing times, and other key DDS performance measures by using current and retrospective data.

This data set includes information on Do Not Call and robocall complaints reported to the Federal Trade Commission. The data set contains information reported by consumers, including the telephone number originating the unwanted call, the date the complaint was created, the time the call was made, the consumer’s city and state locations reported, the subject of the call, and whether the call was a robocall. None of the information about the reported calls is verified.