Individual Land Management Initiative boundaries. The aim of the LMI programmes was to research and demonstrate innovative practical solutions that would maintain viable farm businesses, while providing a wide range of economic, environmental and social benefits. Individual Land Management Initiative boundaries. The LMIs worked with farmers, local communities and other interested organisations, to investigate the problems faced by land managers. The aim was to research and demonstrate innovative practical solutions that would maintain viable farm businesses, while providing a wide range of economic, environmental and social benefits. The aims of each LMI were defined locally, in partnership with stakeholders, and were guided by the objectives of the national programme. A national advisory group helped to guide the development of the overall programme. More information about the LMIs can be found at http://ukeconet.org/wp-content/uploads/2009/10/Experiences_from_the_land_management_initiatives.pdf. Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year].

We publish data on all current Private Finance Initiative (PFI) projects once a year. The information is provided by the departments and Devolved Administrations that procured or sponsored the projects, and is not audited by us. This year the full consolidated list will be published in the autumn. In the meantime we’ve published a list of those projects which reached financial close between 1 April 2012 and 31 March 2013, and the projects which were in procurement as at 31 March 2013. As set out in the PF2 policy document, ‘A new approach to public private partnerships’, business case approval trackers have also been published in response to calls from the private sector for greater transparency of the government’s approval process. These trackers provide procurement status updates on legacy PFI and new PF2 projects.

Individual Land Management Initiative boundaries Attribution statement: Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year].

Dataset held by the Government Equalities Office on companies that have signed up to the initiative which encourages companies to share progress in promoting gender equality and the framework (Think, Act, Report initiative).

The Doorstep Greens initiative provides new or renovated areas of public open space close to people's homes that could be enjoyed permanently by the local community. The initiative is a joint Natural England and New Opportunities Fund project. The initiative is aimed at targeting communities who experience disadvantage and where regeneration of the local environment and outdoor recreation provision is sorely needed. They could be small or large, and in urban or rural locations. Attribution statement: Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year].

Data collection comprising information about public sector procurement from Local Authorities in the UK and Clinical Commissioning Groups in England from 2013-15, funding awards made by foundations and charitable funders, and data on recipient organisations, mainly charities and social enterprises. Data were sourced from a large number of local authorities and Clinical Commissioning Groups by downloading the datasets from authority websites. Each of the datasets were then cleaned, including identifying missing or incomplete rows andconverting dates into a standard format. This data collection represents a formidable resource which has the potential to inform analyses of the distribution of funding to third sector organisations in the form of grants from foundations, government and others; to support further analytical work on the effects of such grants on the subsequent financial trajectories of organisations; to underpin investigations of the extent to which third sector organisations are in receipt of contracts from public sector agencies; and to analyse the balance between public and private provision of welfare services.

The aim of this project is to provide comprehensive data on funding flows to third sector organisations in England. We exploit the growing body of data being made available on grant making to voluntary organisations, and on public procurement, to build resources which will allow researchers to improve understanding of the funding mix of third sector organisations. The resources we create will help third sector organisations and policy makers because it will improve their understanding of their environment, particularly funding opportunities and also potential competitors or collaborators. This means they will be able to better support their beneficiaries by, for example, targeting their services or co-operating with similar organisations. The data will meet administrative and research challenges facing the sector by providing a "spine" for the growing number of open data initiatives. This new data infrastructure will add new value to existing UK social science infrastructure, and will be able to be reused by academic and non-academic researchers (such as those working in government). This data will also help the Office for National Statistics as they work to improve coverage of non-profit organisations in the National Accounts (see letters of support). It is consistent with ESRC's strategic priorities such as a "Vibrant and fair society", in that it significantly enhances understanding of the resources of third sector organisations. Building on TSRC/NCVO's existing databases, generated by combining registers of charities and the Companies House register of companies, we have developed novel data sources for the third sector in the following way. 1. we will download local authority and clinical commissioning group (CCG) data for England, usually available from relevant authorities on a monthly basis; 2. match the CCG data to our existing third sector databases using string matching techniques, and make available the results; 3. match the local authority procurement data to the same databases; 4. capture listings of grants made by charitable funders to organisations in England, such as those lists of grant recipients collated by the "360 Giving"; initiative which is encouraging grant makers to open up data about who they fund but we will work with other major funders. Published data already includes several hundred thousand awards made to voluntary organisations. the sheer scale and ambition of this project is unprecedented anywhere in the world. it provides much greater granular data on relationships between public sector agencies and those from whom they are commissioning services than is possible anywhere else. The project represents an excellent example of a partnership between a strong academic research centre, TSRC, and a high-profile national voluntary organisation, NCVO, in which research is designed and developed with the needs of user and academic communities equally in mind.

FCO plan to achieve IATI standards by 31 March 2014

Future classes in Calderdale Council Sports and Leisure Centres including start date, end date, url, activity, name, location. Current data is for the next 2 weeks. This data aims to comply with the OpenActive standard. OpenActive is a community-led initiative with the ambition to help people in England get active using open data - https://www.openactive.io/

UK boundary dataset corresponding to the geography of the ONS UACNTY09 coding frame. The dataset consists of 143 features corresponding to a standard GB county/unitary authority geography with the following exceptions. Orkney, Shetland and the Western Isles are included as a single feature; The Isles of Scilly are not included; Greater London is split into 2 Inner and Outer features corresponding to the super geographies within which the Inner and Outer London boroughs fall; Northern Ireland is provided as a single feature and is shown alongside the rest of GB in British National Grid. The GB portions of this dataset was derived from Ordnance Survey Boundary-Line data available as part of the Ordnance Survey OpenData initiative. The full terms and conditions of use of Ordnance Survey OpenData which apply to this dataset may be viewed at the following location: http://www.ordnancesurvey.co.uk/opendata/docs/os-opendata-licence.pdf. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-10-15 and migrated to Edinburgh DataShare on 2017-02-21.

The Millennium Greens initiative set out to provide new areas of public open space close to people's homes that could be enjoyed permanently by the local community, in time to mark the start of the third millennium. They were to be breathing spaces - places for relaxation, play and enjoyment of nature and pleasant surroundings. They could be small or large, and in urban or rural locations Attribution statement: Attribution statement: © Natural England copyright. Contains Ordnance Survey data © Crown copyright and database right [year].

UK Crime Data (Oct–Dec 2022)

This dataset is part of the ALLANAI.CrimeVision open-data series by Mahira (ALLANAI Labs).
It includes monthly crime reports from October 2022 to December 2022, retrieved through the UK Police API.

📊 Data Coverage

• Metropolitan (London)
• Greater Manchester
• West Midlands (Birmingham)
• West Yorkshire (Leeds)
• Thames Valley (Oxford region)

📁 Columns

🧠 Applications

• Crime trend analysis (2022 Q4)
• Regional comparison visualization
• Machine learning for crime forecasting

🔗 Source & Project

• GitHub: ALLANAI-CrimeVision Repository
• Official Data Source: UK Police API

📧 Author: Mahira
🌐 ALLANAI Labs
💡 Building AI for a safer and sustainable world.

These data are from the Solar Together project. This is a group buying initiative by the West of England Mayoral Combined Authority which supports low cost retrofit of homes with solar panels, batteries and charging points through bulk purchase arrangements.The locations shown are approximate to preserve anonymity, but the assignment of local authority and census boundary IDs is correct.

Create your own initiative by combining existing applications with a custom site. Use this initiative to form teams around a problem and invite your community to participate.

The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Dataset (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from MODIS MOD14MD Collection 6 active fire products.

This dataset is part of v1.1 of the Small Fire Dataset (also known as FireCCISFD11), which covers Sub-Saharan Africa for the year 2016. Data is available here at pixel resolution (0.00017966259 degrees, corresponding to approximately 20m at the Equator). Gridded data products are also available in a separate dataset.

The Extractive Industries Transparency Initiative (EITI) is an international standard for openness around the management of revenues from natural resources. It is designed to improve accountability and public trust for the revenues paid and received for a country’s oil, gas and mineral resources. The Extractive Industries Transparency Initiative (EITI) reports covering payments and data for the UK extractives sector and a reconciliation of payments made by oil, gas, mining and quarrying companies for the UK extraction of raw materials and government receipts are now available on the UK EITI website. To access the data via the UK EITI website, please put a tick in the “UK EITI Reports” box and click on the “Filter” box. Each UK EITI payments report will be listed. When you double click on the report title a list of the related data will also be listed and accessible.

This dataset contains:

A kmz file for Kelmarsh wind farm in the UK (for opening in e.g. Google Earth)

Static data including turbine coordinates and turbine details (rated power, rotor diameter, hub height, etc.)

10-minute SCADA and events data from the 6 Senvion MM92's at Kelmarsh wind farm, grouped by year from 2016 to mid-2021, which was extracted from our secondary SCADA system (Greenbyte). Note not all signals are available for the entire period

Data mappings from primary SCADA to csv signal names

Site substation/PMU meter data where available for the same period

Site fiscal/grid meter data where available for the same period

MERRA2 and ERA5 since 2000 up to the same period

The dataset has been released by Cubico Sustainable Investments Ltd under a CC-BY-4.0 open data license and is provided as is. However, please provide any feedback you might have on the dataset and format of the data. I'll try and add or link to additional file formats that might be easier to work with (e.g. for use with specific analysis software), and update this dataset periodically (e.g. twice a year), but please prompt me as required.

Feel free to use the data according to the license, however, it would be helpful to me if you could let me know where, how and why you are using the data, so that I can highlight this to the business (and renewables industry) and hopefully promote similar data sharing initiatives. I am particularly interested in performance analysis/improvement opportunities, how the dataset can be augmented with other (open) datasets, and sharing more generally within the renewables industry.

If you would like to get access to other datasets we may hold (e.g. more recent data, data from our other sites, ~30s resolution data, etc.), please let me know, and, if you have any questions or want to discuss open data and this or other initiatives, please contact me and I will endeavour to help.

I would like to thank Cubico's Senior Legal Advisor & Compliance Officer, IT Director, UK Asset Management Team, Executive Committee and my manager for supporting this initiative, as well as our partners GLIL for agreeing to release this data under an open license. I would also like to thank those I have talked to during the process of releasing this data under an open license and the encouragement and advice I have had on the way.

For contact my email address is charlie.plumley@cubicoinvest.com.

You can also access data from Penmanshiel wind farm here.

According to Cognitive Market Research, the global AI Training Dataset Market size will be USD 2962.4 million in 2025. It will expand at a compound annual growth rate (CAGR) of 28.60% from 2025 to 2033.

North America held the major market share for more than 37% of the global revenue with a market size of USD 1096.09 million in 2025 and will grow at a compound annual growth rate (CAGR) of 26.4% from 2025 to 2033.
Europe accounted for a market share of over 29% of the global revenue, with a market size of USD 859.10 million.
APAC held a market share of around 24% of the global revenue with a market size of USD 710.98 million in 2025 and will grow at a compound annual growth rate (CAGR) of 30.6% from 2025 to 2033.
South America has a market share of more than 3.8% of the global revenue, with a market size of USD 112.57 million in 2025 and will grow at a compound annual growth rate (CAGR) of 27.6% from 2025 to 2033.
Middle East had a market share of around 4% of the global revenue and was estimated at a market size of USD 118.50 million in 2025 and will grow at a compound annual growth rate (CAGR) of 27.9% from 2025 to 2033.
Africa had a market share of around 2.20% of the global revenue and was estimated at a market size of USD 65.17 million in 2025 and will grow at a compound annual growth rate (CAGR) of 28.3% from 2025 to 2033.
Data Annotation category is the fastest growing segment of the AI Training Dataset Market

Market Dynamics of AI Training Dataset Market

Key Drivers for AI Training Dataset Market

Government-Led Open Data Initiatives Fueling AI Training Dataset Market Growth

In recent years, Government-initiated open data efforts have strongly driven the development of the AI Training Dataset Market through offering affordable, high-quality datasets that are vital in training sound AI models. For instance, the U.S. government's drive for openness and innovation can be seen through portals such as Data.gov, which provides an enormous collection of datasets from many industries, ranging from healthcare, finance, and transportation. Such datasets are basic building blocks in constructing AI applications and training models using real-world data. In the same way, the platform data.gov.uk, run by the U.K. government, offers ample datasets to aid AI research and development, creating an environment that is supportive of technological growth. By releasing such information into the public domain, governments not only enhance transparency but also encourage innovation in the AI industry, resulting in greater demand for training datasets and helping to drive the market's growth.

India's IndiaAI Datasets Platform Accelerates AI Training Dataset Market Growth

India's upcoming launch of the IndiaAI Datasets Platform in January 2025 is likely to greatly increase the AI Training Dataset Market. The project, which is part of the government's ?10,000 crore IndiaAI Mission, will establish an open-source repository similar to platforms such as HuggingFace to enable developers to create, train, and deploy AI models. The platform will collect datasets from central and state governments and private sector organizations to provide a wide and rich data pool. Through improved access to high-quality, non-personal data, the platform is filling an important requirement for high-quality datasets for training AI models, thus driving innovation and development in the AI industry. This public initiative reflects India's determination to become a global AI hub, offering the infrastructure required to facilitate startups, researchers, and businesses in creating cutting-edge AI solutions. The initiative not only simplifies data access but also creates a model for public-private partnerships in AI development.

Restraint Factor for the AI Training Dataset Market

Data Privacy Regulations Impeding AI Training Dataset Market Growth

Strict data privacy laws are coming up as a major constraint in the AI Training Dataset Market since governments across the globe are establishing legislation to safeguard personal data. In the European Union, explicit consent for using personal data is required under the General Data Protection Regulation (GDPR), reducing the availability of datasets for training AI. Likewise, the data protection regulator in Brazil ordered Meta and others to stop the use of Brazilian personal data in training AI models due to dangers to individuals' funda...

All organisations that publish International Aid Transparency Initiative (IATI) data are identified by their unique code, known as the IATI Organisation Identifier (IATI Org ID). The Foreign, Commonwealth and Development Office (FCDO) is the registration agency for the IATI Org IDs of all UK government organisations.