This table contains 45 series, with data for years 2014 - 2014 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Country of origin (15 items: United States; United Kingdom; France; China; ...) Traveller characteristics (3 items: Trips; Nights; Spending in Canada).

On the continental scale, climate is an important determinant of the distributions of plant taxa and ecoregions. To quantify and depict the relations between specific climate variables and these distributions, we placed modern climate and plant taxa distribution data on an approximately 25-kilometer (km) equal-area grid with 27,984 points that cover Canada and the continental United States (Thompson and others, 2015). The gridded climatic data include annual and monthly temperature and precipitation, as well as bioclimatic variables (growing degree days, mean temperatures of the coldest and warmest months, and a moisture index) based on 1961-1990 30-year mean values from the University of East Anglia (UK) Climatic Research Unit (CRU) CL 2.0 dataset (New and others, 2002), and absolute minimum and maximum temperatures for 1951-1980 interpolated from climate-station data (WeatherDisc Associates, 1989). As described below, these data were used to produce portions of the "Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America" (hereafter referred to as "the Atlas"; Thompson and others, 1999a, 1999b, 2000, 2006, 2007, 2012a, 2015). Evolution of the Atlas Over the 16 Years Between Volumes A & B and G: The Atlas evolved through time as technology improved and our knowledge expanded. The climate data employed in the first five Atlas volumes were replaced by more standard and better documented data in the last two volumes (Volumes F and G; Thompson and others, 2012a, 2015). Similarly, the plant distribution data used in Volumes A through D (Thompson and others, 1999a, 1999b, 2000, 2006) were improved for the latter volumes. However, the digitized ecoregion boundaries used in Volume E (Thompson and others, 2007) remain unchanged. Also, as we and others used the data in Atlas Volumes A through E, we came to realize that the plant distribution and climate data for areas south of the US-Mexico border were not of sufficient quality or resolution for our needs and these data are not included in this data release. The data in this data release are provided in comma-separated values (.csv) files. We also provide netCDF (.nc) files containing the climate and bioclimatic data, grouped taxa and species presence-absence data, and ecoregion assignment data for each grid point (but not the country, state, province, and county assignment data for each grid point, which are available in the .csv files). The netCDF files contain updated Albers conical equal-area projection details and more precise grid-point locations. When the original approximately 25-km equal-area grid was created (ca. 1990), it was designed to be registered with existing data sets, and only 3 decimal places were recorded for the grid-point latitude and longitude values (these original 3-decimal place latitude and longitude values are in the .csv files). In addition, the Albers conical equal-area projection used for the grid was modified to match projection irregularities of the U.S. Forest Service atlases (e.g., Little, 1971, 1976, 1977) from which plant taxa distribution data were digitized. For the netCDF files, we have updated the Albers conical equal-area projection parameters and recalculated the grid-point latitudes and longitudes to 6 decimal places. The additional precision in the location data produces maximum differences between the 6-decimal place and the original 3-decimal place values of up to 0.00266 degrees longitude (approximately 143.8 m along the projection x-axis of the grid) and up to 0.00123 degrees latitude (approximately 84.2 m along the projection y-axis of the grid). The maximum straight-line distance between a three-decimal-point and six-decimal-point grid-point location is 144.2 m. Note that we have not regridded the elevation, climate, grouped taxa and species presence-absence data, or ecoregion data to the locations defined by the new 6-decimal place latitude and longitude data. For example, the climate data described in the Atlas publications were interpolated to the grid-point locations defined by the original 3-decimal place latitude and longitude values. Interpolating the data to the 6-decimal place latitude and longitude values would in many cases not result in changes to the reported values and for other grid points the changes would be small and insignificant. Similarly, if the digitized Little (1971, 1976, 1977) taxa distribution maps were regridded using the 6-decimal place latitude and longitude values, the changes to the gridded distributions would be minor, with a small number of grid points along the edge of a taxa's digitized distribution potentially changing value from taxa "present" to taxa "absent" (or vice versa). These changes should be considered within the spatial margin of error for the taxa distributions, which are based on hand-drawn maps with the distributions evidently generalized, or represented by a small, filled circle, and these distributions were subsequently hand digitized. Users wanting to use data that exactly match the data in the Atlas volumes should use the 3-decimal place latitude and longitude data provided in the .csv files in this data release to represent the center point of each grid cell. Users for whom an offset of up to 144.2 m from the original grid-point location is acceptable (e.g., users investigating continental-scale questions) or who want to easily visualize the data may want to use the data associated with the 6-decimal place latitude and longitude values in the netCDF files. The variable names in the netCDF files generally match those in the data release .csv files, except where the .csv file variable name contains a forward slash, colon, period, or comma (i.e., "/", ":", ".", or ","). In the netCDF file variable short names, the forward slashes are replaced with an underscore symbol (i.e., "_") and the colons, periods, and commas are deleted. In the netCDF file variable long names, the punctuation in the name matches that in the .csv file variable names. The "country", "state, province, or territory", and "county" data in the .csv files are not included in the netCDF files. Data included in this release: - Geographic scope. The gridded data cover an area that we labelled as "CANUSA", which includes Canada and the USA (excluding Hawaii, Puerto Rico, and other oceanic islands). Note that the maps displayed in the Atlas volumes are cropped at their northern edge and do not display the full northern extent of the data included in this data release. - Elevation. The elevation data were regridded from the ETOPO5 data set (National Geophysical Data Center, 1993). There were 35 coastal grid points in our CANUSA study area grid for which the regridded elevations were below sea level and these grid points were assigned missing elevation values (i.e., elevation = 9999). The grid points with missing elevation values occur in five coastal areas: (1) near San Diego (California, USA; 1 grid point), (2) Vancouver Island (British Columbia, Canada) and the Olympic Peninsula (Washington, USA; 2 grid points), (3) the Haida Gwaii (formerly Queen Charlotte Islands, British Columbia, Canada) and southeast Alaska (USA, 9 grid points), (4) the Canadian Arctic Archipelago (22 grid points), and (5) Newfoundland (Canada; 1 grid point). - Climate. The gridded climatic data provided here are based on the 1961-1990 30-year mean values from the University of East Anglia (UK) Climatic Research Unit (CRU) CL 2.0 dataset (New and others, 2002), and include annual and monthly temperature and precipitation. The CRU CL 2.0 data were interpolated onto the approximately 25-km grid using geographically-weighted regression, incorporating local lapse-rate estimation and correction. Additional bioclimatic variables (growing degree days on a 5 degrees Celsius base, mean temperatures of the coldest and warmest months, and a moisture index calculated as actual evapotranspiration divided by potential evapotranspiration) were calculated using the interpolated CRU CL 2.0 data. Also included are absolute minimum and maximum temperatures for 1951-1980 interpolated in a similar fashion from climate-station data (WeatherDisc Associates, 1989). These climate and bioclimate data were used in Atlas volumes F and G (see Thompson and others, 2015, for a description of the methods used to create the gridded climate data). Note that for grid points with missing elevation values (i.e., elevation values equal to 9999), climate data were created using an elevation value of -120 meters. Users may want to exclude these climate data from their analyses (see the Usage Notes section in the data release readme file). - Plant distributions. The gridded plant distribution data align with Atlas volume G (Thompson and others, 2015). Plant distribution data on the grid include 690 species, as well as 67 groups of related species and genera, and are based on U.S. Forest Service atlases (e.g., Little, 1971, 1976, 1977), regional atlases (e.g., Benson and Darrow, 1981), and new maps based on information available from herbaria and other online and published sources (for a list of sources, see Tables 3 and 4 in Thompson and others, 2015). See the "Notes" column in Table 1 (https://pubs.usgs.gov/pp/p1650-g/table1.html) and Table 2 (https://pubs.usgs.gov/pp/p1650-g/table2.html) in Thompson and others (2015) for important details regarding the species and grouped taxa distributions. - Ecoregions. The ecoregion gridded data are the same as in Atlas volumes D and E (Thompson and others, 2006, 2007), and include three different systems, Bailey's ecoregions (Bailey, 1997, 1998), WWF's ecoregions (Ricketts and others, 1999), and Kuchler's potential natural vegetation regions (Kuchler, 1985), that are each based on distinctive approaches to categorizing ecoregions. For the Bailey and WWF ecoregions for North America and the Kuchler potential natural vegetation regions for the contiguous United States (i.e.,

In order to anticipate the impact of local public policies, a synthetic population reflecting the characteristics of the local population provides a valuable test bed. While synthetic population datasets are now available for several countries, there is no open-source synthetic population for Canada. We propose an open-source synthetic population of individuals and households at a fine geographical level for Canada for the years 2021, 2023 and 2030. Based on 2016 census data and population projections, the synthetic individuals have detailed socio-demographic attributes, including age, sex, income, education level, employment status and geographic locations, and are related into households. A comparison of the 2021 synthetic population with 2021 census data over various geographical areas validates the reliability of the synthetic dataset. Users can extract populations from the dataset for specific zones, to explore ‘what if’ scenarios on present and future populations. They can extend the dataset using local survey data to add new characteristics to individuals. Users can also run the code to generate populations for years up to 2042.

To capture the full social and economic benefits of AI, new technologies must be sensitive to the diverse needs of the whole population. This means understanding and reflecting the complexity of individual needs, the variety of perceptions, and the constraints that might guide interaction with AI. This challenge is no more relevant than in building AI systems for older populations, where the role, potential, and outstanding challenges are all highly significant.

The RAIM (Responsible Automation for Inclusive Mobility) project will address how on-demand, electric autonomous vehicles (EAVs) might be integrated within public transport systems in the UK and Canada to meet the complex needs of older populations, resulting in improved social, economic, and health outcomes. The research integrates a multidisciplinary methodology - integrating qualitative perspectives and quantitative data analysis into AI-generated population simulations and supply optimisation. Throughout the project, there is a firm commitment to interdisciplinary interaction and learning, with researchers being drawn from urban geography, ageing population health, transport planning and engineering, and artificial intelligence.

The RAIM project will produce a diverse set of outputs that are intended to promote change and discussion in transport policymaking and planning. As a primary goal, the project will simulate and evaluate the feasibility of an on-demand EAV system for older populations. This requires advances around the understanding and prediction of the complex interaction of physical and cognitive constraints, preferences, locations, lifestyles and mobility needs within older populations, which differs significantly from other portions of society. With these patterns of demand captured and modelled, new methods for meeting this demand through optimisation of on-demand EAVs will be required. The project will adopt a forward-looking, interdisciplinary approach to the application of AI within these research domains, including using Deep Learning to model human behaviour, Deep Reinforcement Learning to optimise the supply of EAVs, and generative modelling to estimate population distributions.

A second component of the research involves exploring the potential adoption of on-demand EAVs for ageing populations within two regions of interest. The two areas of interest - Manitoba, Canada, and the West Midlands, UK - are facing the combined challenge of increasing older populations with service issues and reducing patronage on existing services for older travellers. The RAIM project has established partnerships with key local partners, including local transport authorities - Winnipeg Transit in Canada, and Transport for West Midlands in the UK - in addition to local support groups and industry bodies. These partnerships will provide insights and guidance into the feasibility of new AV-based mobility interventions, and a direct route to influencing future transport policy. As part of this work, the project will propose new approaches for assessing the economic case for transport infrastructure investment, by addressing the wider benefits of improved mobility in older populations.

At the heart of the project is a commitment to enhancing collaboration between academic communities in the UK and Canada. RAIM puts in place opportunities for cross-national learning and collaboration between partner organisations, ensuring that the challenges faced in relation to ageing mobility and AI are shared. RAIM furthermore will support the development of a next generation of researchers, through interdisciplinary mentoring, training, and networking opportunities.

This table contains 32 series, with data for years 1956 - 1976 (not all combinations necessarily have data for all years), and was last released on 2012-02-16. This table contains data described by the following dimensions (Not all combinations are available): Unit of measure (1 items: Persons ...) Geography (32 items: Outside Canada; Great Britain; France; Europe ...).

Our data feed provides our client's the ability and flexibility to leverage our e-receipt dataset to answer their business questions. We train you on the nuances of transaction data and provide client support to make you successful in using the dataset on your own.

Edison's data feed includes a few components: 1) User level data (user panel) - We provide a user panel dataset to help understand panel level metrics, make adjustments for panel growth, and extrapolate from our sample. 2) Receipt data - Each email receipt we observe is parsed based on the most advanced approach combining deep learning and human coding. We follow a standardized structure when categorizing values in receipts and try to account for edge cases. Each row in this dataset represents a unique item on a receipt.

Canada CA: Foreign Direct Investment Income: Inward: USD: Total: United Kingdom data was reported at 2.117 USD bn in 2023. This records a decrease from the previous number of 2.986 USD bn for 2022. Canada CA: Foreign Direct Investment Income: Inward: USD: Total: United Kingdom data is updated yearly, averaging 2.965 USD bn from Dec 2011 (Median) to 2023, with 12 observations. The data reached an all-time high of 4.704 USD bn in 2013 and a record low of 2.117 USD bn in 2023. Canada CA: Foreign Direct Investment Income: Inward: USD: Total: United Kingdom data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Canada – Table CA.OECD.FDI: Foreign Direct Investment Income: USD: by Region and Country: OECD Member: Annual. Reverse investment:Reverse investment in equity (when a direct investment enterprise acquires less than 10% equity ownership in its parent) cannot be identified but is believed to be extremely rare. Netting of reverse investment in debt (when a direct investment enterprise extends a loan to its parent) is applied in the recording of total inward and outward FDI transactions and positions. In the case of Canada, any extension of loans by the DIE to its parent is netted out from inward and outward transactions and positions, regardless of the DIE's equity ownership in its parent. Treatment of debt transactions and positions between fellow enterprises: asset/liability basis. FDI transactions and positions by partner country and by industry include resident Special Purpose Entities (SPEs), which cannot yet be reported separately. Valuation method used for listed inward and outward equity positions: Own funds at book values. Valuation method used for unlisted inward and outward equity positions: Own funds at book values. Valuation method used for inward and outward debt positions: Book value .; FDI statistics are available by geographic allocation, vis-à-vis single partner countries worldwide and geographical and economic zones aggregates. Partner country allocation can be subject to confidentiality restrictions. Geographic allocation of inward and outward FDI transactions and positions is according to the immediate counterparty. Inward FDI positions according to the ultimate counterparty (the ultimate investing country) are also available and publishable. In the dataset 'FDI statistics by parner country and by industry - Summary', inward FDI positions are showed according to the UIC. Intercompany debt between related financial intermediaries, including permanent debt, are excluded from FDI transactions and positions. Direct investment relationships are identified according to the criteria of the Framework for Direct Investment Relationships (FDIR) method. Debt between fellow enterprises are completely covered except in outward FDI positions. Collective investment institutions are covered as direct investment enterprises. Non-profit institutions serving households are covered as direct investors. FDI statistics are available by industry sectors according to ISIC4 classification. Industry sector allocation can be subject to confidentiality restrictions. Inward FDI transactions and positions are allocated to the activity of the resident direct investment enterprise. Outward FDI transactions are allocated according to the activity of the resident direct investor. Outward FDI positions are allocated according to the activity of the non resident direct investment enterprise. Statistical unit: Enterprise.

This dataset comprises hydrographic sections, together with measurements collected by ocean gliders and moored instrumentation deployed during the UK Overturning In the Subpolar North Atlantic Programme (UK-OSNAP). UK-OSNAP is the UK contribution to the International OSNAP Programme. The dataset also includes modelling output informed by the observations. OSNAP observations are focused on two lines: i) OSNAP West, extending from south Labrador to southwest Greenland and ii) OSNAP East from southeast Greenland to Scotland. Data collection commenced June 2014 and is ongoing. UK-OSNAP consists of cruises JR302, PE399, DY053, DY054, two alternating glider deployments, current meter moorings (five at Cape Farewell and three in the Rockall trough) and ADCPs in the Rockall Trough Shelf Edge Current. The model data addresses the Subpolar Gyre circulation and fluxes using data assimilation and theoretical analysis. The datasets assembled as part of UK-OSNAP provide a continuous record of full-depth, trans-basin mass, heat, and freshwater fluxes in the North Atlantic Subpolar Gyre. These, coupled with the associated modelling exercises help improve the understanding of the circulation and fluxes of the North Atlantic Subpolar Gyre. UK-OSNAP, funded by the Natural Environment Research Council (NERC) is led by the National Oceanography Centre (NOC). UK-OSNAP is a partnership between NOC, Scottish Association for Marine Science (SAMS), University of Oxford and the University of Liverpool. It is part of international OSNAP that is led by USA and includes 10 further partner groups in Canada, France, Germany, the Netherlands and China. Investigators: National Oceanography Centre (NOC): Dr Penny Holliday, Dr Sheldon Bacon, Dr Chris Wilson, Neill Mackay. Scottish Association for Marine Science (SAMS): Dr Stuart Cunningham, Prof Mark Inall, Loic Houpert. University of Oxford: Prof David Marshall, Dr Helen Johnson. University of Liverpool: Prof Ric Williams, Dr Vassil Roussenov. The full dataset is still being assembled and currently consists of near real time glider measurements, mooring data and cruise data. NERC have added an extension to UK-OSNAP, until October 2024. This will result in the UK-OSNAP-Decade: 10 years of observing and understanding the overturning circulation in the subpolar North Atlantic (2014-2024).

Our data feed provides our client's the ability and flexibility to leverage our e-receipt dataset to answer their business questions. We train you on the nuances of transaction data and provide client support to make you successful in using the dataset on your own.

Edison's data feed includes a few components: 1) User level data (user panel) - We provide a user panel dataset to help understand panel level metrics, make adjustments for panel growth, and extrapolate from our sample. 2) Receipt data - Each email receipt we observe is parsed based on the most advanced approach combining deep learning and human coding. We follow a standardized structure when categorizing values in receipts and try to account for edge cases. Each row in this dataset represents a unique item on a receipt.

Abstract

This dataset, a product of the Trade Team - Development Research Group, is part of a larger effort in the group to measure the extent of the brain drain as part of the International Migration and Development Program. It measures international skilled migration for the years 1975-2000.

The methodology is explained in: "Tendance de long terme des migrations internationals. Analyse à partir des 6 principaux pays recerveurs", Cécily Defoort.

This data set uses the same methodology as used in the Docquier-Marfouk data set on international migration by educational attainment. The authors use data from 6 key receiving countries in the OECD: Australia, Canada, France, Germany, the UK and the US.

It is estimated that the data represent approximately 77 percent of the world’s migrant population.

Bilateral brain drain rates are estimated based observations for every five years, during the period 1975-2000.

Geographic coverage

Australia, Canada, France, Germany, UK and US

Kind of data

Aggregate data [agg]

Mode of data collection

Other [oth]

Data comprise soil temperature, air temperature, soil volumetric moisture content, relative humidity, and surface wetness data from Onset Microstation Data Loggers at 5 locations (within the main vegetation types) at SikSik creek catchment, Trail Valley Creek, NWT, Canada. The data were collected under Project HYDRA, a NERC funded UK research project linking Heriot Watt University, the Universities of Durham, Aberdeen and Stirling, and the Centre for Ecology & Hydrology (CEH), Edinburgh. Project HYDRA is part of the UK Arctic Research Programme. Project HYDRA studies sites in Arctic Canada to investigate the biological, chemical and physical controls on the release of greenhouse gases from permafrost into melt water and to the atmosphere and how these emissions will influence global warming. Full details about this dataset can be found at https://doi.org/10.5285/10839b38-cc29-4a07-999a-ac32e3f70609

Full resource found at: https://sparcopen.org/our-work/big-deal-knowledge-base

Sourcing: Pricing Data: Individual entries are linked to third party resources within the database; non-linked entries come from Freedom of Information requests (courtesy of Ted Bergstrom and Paul Courant). FTE Data: UK Higher Education Statistics Agency for UK FTE (HE student enrollment FTE + HE staff); DOE IPEDS for US FTE (“Full-time equivalent fall enrollment” + “Total FTE staff”); Universities Canada and COPPUL for Canadian FTE (student data only). Institutional Categories: Carnegie Classification of Institutions of Higher Education.

We propose a novel econometric approach to estimating time-varying policy effects using external instruments in the presence of time-varying instrument relevance in a factor-augmented VAR model with data on the U.S., Canada, Germany, Japan, and the U.K. We find that U.S. monetary policy shocks are an important driver of the exchange rate movements, with no delayed overshooting. We show that estimates of spillover effects of U.S. monetary policy shocks on the inflation and real economic activity would be distorted without considering time variation in instrument relevance, and time variation in policy effects reflects primarily varying shock size, not their transmission.

Abstract copyright UK Data Service and data collection copyright owner.The Crime Survey for England and Wales (CSEW) asks a sole adult, in a random sample of households, about their, or their household's, experience of crime victimisation in the previous 12 months. These are recorded in the victim form data file (VF). A wide range of questions are then asked covering demographics and crime-related subjects such as attitudes to the police and the criminal justice system (CJS) these variables are contained within the non-victim form (NVF) data file. In 2009, the survey was extended to children aged 10-15 years old; one resident of that age range is also selected from the household and asked about their experience of crime, and other related topics. The first set of children's data covered January-December 2009 and is held separately under SN 6601. From 2009-2010, the children's data cover the same period as the adult data and are included with the main study.The CSEW was formerly known as the British Crime Survey (BCS), and has been in existence since 1981. The 1982 and 1988 BCS waves were also conducted in Scotland (data held separately under SNs 4368 and 4599). Since 1993, separate Scottish Crime and Justice Surveys have been conducted. Up to 2001, the BCS was conducted biennially. From April 2001, the Office for National Statistics took over the survey and it became the CSEW. Interviewing was then carried out continually and reported on in financial year cycles. The crime reference period was altered to accommodate this. Further information may be found on the ONS Crime Survey for England and Wales web page and for the previous BCS, from the GOV.UK BCS Methodology web page. Secure Access dataIn addition to the main survey, a series of questions covering drinking behaviour, drug use, self-offending, gangs and personal security, and intimate personal violence (IPV) (including stalking and sexual victimisation) are asked of adults via a laptop-based self-completion module (questions may vary over the years). Children aged 10-15 years also complete a separate self-completion questionnaire. The questionnaires are included in the main documentation, but the data are only available under Secure Access conditions (see SN 7280), not with the main study. In addition, from 2011 onwards, lower-level geographic variables are also available under Secure Access conditions (see SN 7311).New methodology for capping the number of incidents from 2017-18The CSEW datasets available from 2017-18 onwards are based on a new methodology of capping the number of incidents at the 98th percentile. Incidence variables names have remained consistent with previously supplied data but due to the fact they are based on the new 98th percentile cap, and old datasets are not, comparability has been lost with years prior to 2012-2013. More information can be found in the 2017-18 User Guide (see SN 8464) and the article ‘Improving victimisation estimates derived from the Crime Survey for England and Wales’. The central aim of the first BCS was to estimate the incidence of victimisation of selected types of crime among the adult population over a given period, to describe the circumstances under which people became victims of crime and assess the consequences for them of becoming victims. The design of the survey drew very heavily on experience from previous victim surveys, particularly the U.S. National Crime Survey and victim surveys in Canada and the Netherlands. The design of the first BCS however, had some individual features arising from its particular objectives and the circumstances and constraints under which it was carried out. These features are described in more detail in the publication by Hough and Mayhew (1983), listed on the Publications page. This first sweep of the BCS was also conducted in Scotland, as well as in England and Wales. This study, SN 1869, includes only the data for England and Wales; the Scottish data are held separately under SN 4368. Users who need data for all three countries (Scotland, England and Wales) should order both datasets. For the third edition (December 2006), the depositor supplied a new version of the non-victim form data file, with many variable and value labels added where none previously existed. The victim form data file currently remains unlabelled. Main Topics: Respondents were asked a series of screening questions to establish whether or not they had been the victims of crime during the reference period, and a series of very detailed questions about the incidents they reported. Basic descriptive background information on the respondents and their households was also collected to allow analysis of the sorts of people who do and do not become victims. Other information collected was on fear of crime, contact with the police, lifestyle, and self-reported offending. Multi-stage stratified random sample Face-to-face interview Self-completion 1982 ADVICE AGE ALCOHOL USE ALCOHOLIC DRINKS ANXIETY ARREST ASSAULT ATTITUDES BICYCLES BUILDINGS BURGLARY CAR PARKING AREAS CHILDREN CLUBS COMMUTING CONDITIONS OF EMPLO... CONSUMER GOODS CONVENTIONAL WEAPONS COSTS CRIME AND SECURITY CRIME PREVENTION CRIME VICTIMS CRIMINAL DAMAGE CRIMINAL INVESTIGATION CRIMINALS CULTURAL GOODS Crime and law enfor... DISTANCE MEASUREMENT DOGS DOMESTIC APPLIANCES DOMESTIC RESPONSIBI... DOMESTIC SAFETY DRINKING OFFENCES DRIVING ECONOMIC ACTIVITY ECONOMIC VALUE EDUCATIONAL BACKGROUND EMOTIONAL STATES EMPLOYMENT ETHNIC GROUPS England and Wales FAMILY MEMBERS FEAR OF CRIME FINANCIAL COMPENSATION FIRE FRIENDS FULL TIME EMPLOYMENT GENDER GOVERNMENT ORGANIZA... HEADS OF HOUSEHOLD HOME OWNERSHIP HOUSEHOLD HEAD S EC... HOUSEHOLD HEAD S OC... HOUSEHOLD INCOME HOUSEHOLDS HOUSING HOUSING TENURE HUMAN BEHAVIOUR HUMAN SETTLEMENT INDUSTRIES INJURIES INSURANCE INTERPERSONAL CONFLICT INTERPERSONAL RELAT... INTRUDER ALARM SYSTEMS JOB DESCRIPTION JOB HUNTING JOB REQUIREMENTS JUDGMENTS LAW LANDLORDS LEAVE LEISURE TIME ACTIVI... LOCATION LOCKS MARITAL STATUS MEDICAL CARE MONEY MOTOR VEHICLES NEIGHBOURHOODS OCCUPATIONS OFFENCES OFFENSIVE TELEPHONE... PART TIME EMPLOYMENT PAYMENTS PERFORMING ARTS PERSONAL CONTACT PERSONAL SAFETY PHYSICIANS POLICE COMMUNITY RE... POLICE SERVICES POLICING PRISON SENTENCES PUNISHMENT RELIGIOUS ATTENDANCE RENTED ACCOMMODATION RESIDENTIAL MOBILITY RETIREMENT ROAD ACCIDENTS ROBBERY SATISFACTION SELF EMPLOYED SEXUAL ASSAULT SEXUAL OFFENCES SICK LEAVE SOCIAL ACTIVITIES L... SOCIAL HOUSING SOCIAL SUPPORT SPORT SPOUSES STRUCTURAL ELEMENTS... SUPERVISORS Social behaviour an... TAX EVASION TELEPHONES THEFT THEFT PROTECTION TIME TRAFFIC OFFENCES TRANSPORT TRAVEL TRESPASS UNEMPLOYED URBAN AREAS VISITS PERSONAL WAGES WALKING WITNESSES WORKERS WORKPLACE

This table contains 25 series, with data for years 1955 - 2013 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...) Last permanent residence (25 items: Total immigrants; France; Great Britain; Total Europe ...).

QuestionTimeSpeech v.1 is a dataset on speech contributions during parliamentary question time sessions from Australia (2011-2022), Belgium (2010-2022), Canada (2006-2022), Croatia (2004-2022) and the UK (2010-2022). Each speech contribution during a question time session is treated as an observation (e.g. questions, answers, replies, points of order, interruptions, speakers’ interventions, etc.). Besides the actual transcript, the dataset includes information on the contributors such as party affiliation, status (government, opposition), position (opposition, majority, cabinet), role (prime minister, opposition leader, minister of finance, etc.) and gender (male, female). For some countries, the dataset also provides information on the contributor’s constituency (Australia, Canada and the UK) as well as the issue that is addressed (Australia, Canada and the UK). For Belgium and Croatia, we have also included the English translation. Read more in "ReleaseNote_QuestionTimeSpeech v.1".

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We use of globally recognized data laws like –

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• Elaborate data mining from credible sources • 7-tier verification, including manual quality check • Strict adherence to global and local data policies • Guaranteed 95% accuracy or cash-back • Free sample database available on request

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We understand the importance of data accuracy and employ every avenue to keep our database fresh and updated. We execute a multi-step QC process backed by our Patented AI and Machine learning tools to prevent anomalies in consistency and data precision. This cycle repeats every 45 days. Although maintaining 100% accuracy is quite impractical, since data such as email, physical addresses, and phone numbers are subjected to change, we guarantee 85% email deliverability and 95% accuracy on other data points.

100% replacement in case of hard bounces

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This data set includes microseismic and structural geological data collected at Aquistore (Canada). They cover a period from 26th April - 21st June 2015, during which CO2 was being injected in the Aquistore injection well at 3.5 km depth. The data were collected in the framework of a research project funded by UKCCSRC (EPSRC) and based at Aquistore in order to identify whether any microseismic events, that could be related to the CO2 injection, took place during this period and use of these events to image potential flowpathways at depth. The data were collected at a sampling rate of 1000Hz using a short-period microseismic array with a 25m aperture, consisting of one three-component and three one-component sensors (Lennartz, MKIII and MKII lite). The array was placed at 50cm depth, approximately 150m away from the injection well. Acquisition was continuous during the above period. The microseismic data are available in PASCAL or ASCII format. Full details on equipment used in data collection and data formats are available in the README file. Due to commercial constraints this dataset is currently under embargo until the end of 2017. Due to the large size of the dataset additional information and access requirements can be requested via the contact email supplied.

This collection presents data from 37 interviews' abstracts. These interviews were conducted in Montreal (Quebec, Canada) with key officials, public managers, community organizers and workers, representatives of Charity foundations, activists and trade unionists. This research aimed at understanding how austerity measures are affecting governance structures and collaboration between various actors: how are governance and collaboration structures coping with austerity and the tensions that derive from it? Very few, if any, of our respondent disagreed that a better "rigour" ("rigueur" is the euphemism commonly used by Quebec official to talk about austerity) is necessary in respect with public finances. But most of them rejected the way it was implemented: the authoritarianism of it, the lack of collaboration. What was most striking, in our results, is this consensus on the necessity to redefine the Welfare Model without any agreements on what new model of social solidarity should be implemented. This data collection presents the various trends within Montreal's civil society and local government that indicate what new model of social solidarity might emerge. This data collection is made up of the translated abstracts of the interview we've conducted. Austerity governance, defined as a sustained agenda for reducing public spending, poses new challenges for the organisation of relationships between government, business and citizens in many parts of the world. This project compares how these challenges are addressed in eight countries: Australia, Canada, France, Greece, Ireland, Spain, the UK and the USA. Governments have long sought effective ways of engaging citizen activists and business leaders in decision making, through many formal and informal mechanisms - what we term collaborative governance. The focus of our research is how collaboration contributes to the governance of austerity. Governments and public service leaders argue that collaboration with businesses, voluntary organisations and active citizens is essential for addressing the many challenges posed by austerity. The challenges include transforming public services to cope with cuts, changing citizen expectations and managing demand for services and enhancing the legitimacy of difficult policy decisions by involving people outside government in making them. But at the same time, collaboration can be exclusionary. For example, if there are high levels of protest, governmental and business elites may collaborate in ways that marginalise ordinary citizens to push through unpopular policies. Our challenge is to explore different ways in which collaboration works or fails in governing austerity and whether it is becoming more or less important in doing so. We propose to compare the role of collaboration in governing austerity in eight cities of the aforementioned countries: Athens, Baltimore, Barcelona, Dublin, Leicester, Melbourne, Montreal and Nantes. It is in towns and cities that government has the most immediate and closest day-to-day engagement with citizens and it is for this reason that we chose to locate our research at the urban scale. Our primary objective is to understand whether, and if so how, collaboration among public officials, citizens, business leaders and other actors contributes to austerity governance. For example is there more collaboration, less or are we seeing different kinds of collaboration emerging? Who, if anyone, refuses to collaborate and with what implications for governing austerity? Might collaboration be a way to subvert or resist aspects of austerity? The research is comparative, meaning that it is looking for patterns and to see what lessons and insights countries in different parts of the world might draw from one another. Finding ways to collaborate with citizens has always been important for central and local governments, although collaboration has been a higher political priority in the past 20 years than before. Our study will tell politicians and public officials much about how collaboration works as a way of governing austerity. However we are not trying to 'sell' collaboration, or suggest that those suffering from cuts and wanting to resist them should collaborate if they do not wish to. For citizen activists our research will highlight different strategies and options for speaking truth to power - by engaging with city government and local business elites, or refusing to do so and perhaps focusing on protest instead. We will discover when collaboration serves the ends of community groups and when it does not. Participants in our study, and others, will have the opportunity to discuss these issues at a series of local events, at which we will discuss our findings. The research will also engage with important academic debates about the changing nature of governance. In gathering and comparing a large body of data we will learn about the changing role of government under austerity and whether governing is becoming more elite-focused, remote and hierarchical, or perhaps even more inclusive despite the challenging times in which we live. For this research, we conducted 37 interviews in two successive phases. In the first one, we interviewed mainly public managers of the main local public institutions of Montreal. These are were we can find official, "public", collaborations as these institutions articulate the three different tiers of government and call upon the business milieu and civil society. This allowed us to have a clear picture of how governance was structured at the level of the local government and how austerity might affect it. After this first phase, we started looking into neighbourhood-level community organizations. We explored how the delegation of services operated and the community sector organized and collaborated. To do this, we interviewed key individuals working in the coordination of local community organizations and with charity foundations who finance these structures. We carried out interviews until we reached data saturation. After this we presented our analysis to our participants.

Data DescriptionWater Quality Parameters: Ammonia, BOD, DO, Orthophosphate, pH, Temperature, Nitrogen, Nitrate.Countries/Regions: United States, Canada, Ireland, England, China.Years Covered: 1940-2023.Data Records: 2.82 million.Definition of ColumnsCountry: Name of the water-body region.Area: Name of the area in the region.Waterbody Type: Type of the water-body source.Date: Date of the sample collection (dd-mm-yyyy).Ammonia (mg/l): Ammonia concentration.Biochemical Oxygen Demand (BOD) (mg/l): Oxygen demand measurement.Dissolved Oxygen (DO) (mg/l): Concentration of dissolved oxygen.Orthophosphate (mg/l): Orthophosphate concentration.pH (pH units): pH level of water.Temperature (°C): Temperature in Celsius.Nitrogen (mg/l): Total nitrogen concentration.Nitrate (mg/l): Nitrate concentration.CCME_Values: Calculated water quality index values using the CCME WQI model.CCME_WQI: Water Quality Index classification based on CCME_Values.Data Directory Description:Category 1: DatasetCombined Data: This folder contains two CSV files: Combined_dataset.csv and Summary.xlsx. The Combined_dataset.csv file includes all eight water quality parameter readings across five countries, with additional data for initial preprocessing steps like missing value handling, outlier detection, and other operations. It also contains the CCME Water Quality Index calculation for empirical analysis and ML-based research. The Summary.xlsx provides a brief description of the datasets, including data distributions (e.g., maximum, minimum, mean, standard deviation).Combined_dataset.csvSummary.xlsxCountry-wise Data: This folder contains separate country-based datasets in CSV files. Each file includes the eight water quality parameters for regional analysis. The Summary_country.xlsx file presents country-wise dataset descriptions with data distributions (e.g., maximum, minimum, mean, standard deviation).England_dataset.csvCanada_dataset.csvUSA_dataset.csvIreland_dataset.csvChina_dataset.csvSummary_country.xlsxCategory 2: CodeData processing and harmonization code (e.g., Language Conversion, Date Conversion, Parameter Naming and Unit Conversion, Missing Value Handling, WQI Measurement and Classification).Data_Processing_Harmonnization.ipynbThe code used for Technical Validation (e.g., assessing the Data Distribution, Outlier Detection, Water Quality Trend Analysis, and Vrifying the Application of the Dataset for the ML Models).Technical_Validation.ipynbCategory 3: Data Collection SourcesThis category includes links to the selected dataset sources, which were used to create the dataset and are provided for further reconstruction or data formation. It contains links to various data collection sources.DataCollectionSources.xlsxOriginal Paper Title: A Comprehensive Dataset of Surface Water Quality Spanning 1940-2023 for Empirical and ML Adopted ResearchAbstractAssessment and monitoring of surface water quality are essential for food security, public health, and ecosystem protection. Although water quality monitoring is a known phenomenon, little effort has been made to offer a comprehensive and harmonized dataset for surface water at the global scale. This study presents a comprehensive surface water quality dataset that preserves spatio-temporal variability, integrity, consistency, and depth of the data to facilitate empirical and data-driven evaluation, prediction, and forecasting. The dataset is assembled from a range of sources, including regional and global water quality databases, water management organizations, and individual research projects from five prominent countries in the world, e.g., the USA, Canada, Ireland, England, and China. The resulting dataset consists of 2.82 million measurements of eight water quality parameters that span 1940 - 2023. This dataset can support meta-analysis of water quality models and can facilitate Machine Learning (ML) based data and model-driven investigation of the spatial and temporal drivers and patterns of surface water quality at a cross-regional to global scale.Note: Cite this repository and the original paper when using this dataset.