The Toronto Employment Survey Bulletin summarizes the highlights of the field survey by City Planning. Surveyors visit all businesses in the city to collect information about the number of employees working in each business located within the city of Toronto boundaries, and the type of work that is taking place. Each business provides information on the number of full- and part-time employees as well as the type of employment activity taking place at each location. For more information, refer to the bulletin. The Toronto Employment Survey explores one or more special topics related to Toronto's economy. As a result, additional tables related to those topics may exist for some years that do not exist for other years Additional contact: cityplanning@toronto.ca

Please note that this dataset is not an official City of Toronto land use dataset. It was created for personal and academic use using City of Toronto Land Use Maps (2019) found on the City of Toronto Official Plan website at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/official-plan-maps-copy, along with the City of Toronto parcel fabric (Property Boundaries) found at https://open.toronto.ca/dataset/property-boundaries/ and Statistics Canada Census Dissemination Blocks level boundary files (2016). The property boundaries used were dated November 11, 2021. Further detail about the City of Toronto's Official Plan, consolidation of the information presented in its online form, and considerations for its interpretation can be found at https://www.toronto.ca/city-government/planning-development/official-plan-guidelines/official-plan/ Data Creation Documentation and Procedures Software Used The spatial vector data were created using ArcGIS Pro 2.9.0 in December 2021. PDF File Conversions Using Adobe Acrobat Pro DC software, the following downloaded PDF map images were converted to TIF format. 9028-cp-official-plan-Map-14_LandUse_AODA.pdf 9042-cp-official-plan-Map-22_LandUse_AODA.pdf 9070-cp-official-plan-Map-20_LandUse_AODA.pdf 908a-cp-official-plan-Map-13_LandUse_AODA.pdf 978e-cp-official-plan-Map-17_LandUse_AODA.pdf 97cc-cp-official-plan-Map-15_LandUse_AODA.pdf 97d4-cp-official-plan-Map-23_LandUse_AODA.pdf 97f2-cp-official-plan-Map-19_LandUse_AODA.pdf 97fe-cp-official-plan-Map-18_LandUse_AODA.pdf 9811-cp-official-plan-Map-16_LandUse_AODA.pdf 982d-cp-official-plan-Map-21_LandUse_AODA.pdf Georeferencing and Reprojecting Data Files The original projection of the PDF maps is unknown but were most likely published using MTM Zone 10 EPSG 2019 as per many of the City of Toronto's many datasets. They could also have possibly been published in UTM Zone 17 EPSG 26917 The TIF images were georeferenced in ArcGIS Pro using this projection with very good results. The images were matched against the City of Toronto's Centreline dataset found here The resulting TIF files and their supporting spatial files include: TOLandUseMap13.tfwx TOLandUseMap13.tif TOLandUseMap13.tif.aux.xml TOLandUseMap13.tif.ovr TOLandUseMap14.tfwx TOLandUseMap14.tif TOLandUseMap14.tif.aux.xml TOLandUseMap14.tif.ovr TOLandUseMap15.tfwx TOLandUseMap15.tif TOLandUseMap15.tif.aux.xml TOLandUseMap15.tif.ovr TOLandUseMap16.tfwx TOLandUseMap16.tif TOLandUseMap16.tif.aux.xml TOLandUseMap16.tif.ovr TOLandUseMap17.tfwx TOLandUseMap17.tif TOLandUseMap17.tif.aux.xml TOLandUseMap17.tif.ovr TOLandUseMap18.tfwx TOLandUseMap18.tif TOLandUseMap18.tif.aux.xml TOLandUseMap18.tif.ovr TOLandUseMap19.tif TOLandUseMap19.tif.aux.xml TOLandUseMap19.tif.ovr TOLandUseMap20.tfwx TOLandUseMap20.tif TOLandUseMap20.tif.aux.xml TOLandUseMap20.tif.ovr TOLandUseMap21.tfwx TOLandUseMap21.tif TOLandUseMap21.tif.aux.xml TOLandUseMap21.tif.ovr TOLandUseMap22.tfwx TOLandUseMap22.tif TOLandUseMap22.tif.aux.xml TOLandUseMap22.tif.ovr TOLandUseMap23.tfwx TOLandUseMap23.tif TOLandUseMap23.tif.aux.xml TOLandUseMap23.tif.ov Ground control points were saved for all georeferenced images. The files are the following: map13.txt map14.txt map15.txt map16.txt map17.txt map18.txt map19.txt map21.txt map22.txt map23.txt The City of Toronto's Property Boundaries shapefile, "property_bnds_gcc_wgs84.zip" were unzipped and also reprojected to EPSG 26917 (UTM Zone 17) into a new shapefile, "Property_Boundaries_UTM.shp" Mosaicing Images Once georeferenced, all images were then mosaiced into one image file, "LandUseMosaic20211220v01", within the project-generated Geodatabase, "Landuse.gdb" and exported TIF, "LandUseMosaic20211220.tif" Reclassifying Images Because the original images were of low quality and the conversion to TIF made the image colours even more inconsistent, a method was required to reclassify the images so that different land use classes could be identified. Using Deep learning Objects, the images were re-classified into useful consistent colours. Deep Learning Objects and Training The resulting mosaic was then prepared for reclassification using the Label Objects for Deep Learning tool in ArcGIS Pro. A training sample, "LandUseTrainingSamples20211220", was created in the geodatabase for all land use types as follows: Neighbourhoods Insitutional Natural Areas Core Employment Areas Mixed Use Areas Apartment Neighbourhoods Parks Roads Utility Corridors Other Open Spaces General Employment Areas Regeneration Areas Lettering (not a land use type, but an image colour (black), used to label streets). By identifying the letters, it then made the reclassification and vectorization results easier to clean up of unnecessary clutter caused by the labels of streets. Reclassification Once the training samples were created and saved, the raster was then reclassified using the Image Classification Wizard tool in ArcGIS Pro, using the Support...

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Toronto. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Toronto, the median income for all workers aged 15 years and older, regardless of work hours, was $44,429 for males and $26,303 for females.

These income figures highlight a substantial gender-based income gap in Toronto. Women, regardless of work hours, earn 59 cents for each dollar earned by men. This significant gender pay gap, approximately 41%, underscores concerning gender-based income inequality in the city of Toronto.

- Full-time workers, aged 15 years and older: In Toronto, among full-time, year-round workers aged 15 years and older, males earned a median income of $76,078, while females earned $33,188, leading to a 56% gender pay gap among full-time workers. This illustrates that women earn 44 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Toronto, showcasing a consistent income pattern irrespective of employment status.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Toronto median household income by race. You can refer the same here

The CYI Survey invites employees to voluntarily disclose how they self-identify based on questions related to Indigenous identity, Black identity, gender, race/ethnicity, sexual orientation and if they identify as a person with a disability. The data displays the diversity within the workforce at the City of Toronto. The goal of the survey is to track progress towards realizing the City's Motto "Diversity Our Strength", and to continuously monitor and socialize diversity data across the City, in order to help inform decision-making and address gaps in representation across all levels at the City. About the Datasets The following datasets were collected through the City's CYI Workforce survey between 2013 and 2024. The data has been reported in aggregate formats that do not allow for the identification of individual employees. First Nations, Inuit, and Metis Data The City is working with an external working group of First Nations, Inuit, and Métis (FNIM) advisors to develop a framework for the collection and use of FNIM data. While this framework is in development, Indigenous data from CYI surveys conducted in 2022, 2023, and 2024 will not be made available until Ownership, Control, Access, and Possession (OCAP) and United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) principles have been applied. However, Indigenous data from 2018, 2019, 2020 and 2021 is still available. For questions related to the implications or considerations of the framework’s development, please contact dataequity@toronto.ca

Statistics Canada publishes monthly labour force statistics for all Canadian Census Metropolitan Areas (CMAs) and provinces. In addition, the City of Toronto purchases a special run from Statistics Canada of Labour Force Survey (LFS) data for city of Toronto residents (i.e. separate from the rest of the Toronto CMA). LFS data are collected by place of residence, and therefore city of Toronto's "employment" represents "employed residents" and not "jobs" in the city of Toronto. There are more jobs in the city of Toronto than employed city of Toronto residents. In this LFS database, you will find 22 monthly tables and 28 annual tables. Most of the tables contain data for five geographies: city of Toronto, Toronto CMA, Toronto/Hamilton/Oshawa CMAs, Ontario and Canada ( see attachment Table of Contents below a full description ). LFS data in the IVT tables are not seasonally adjusted. Top level seasonally adjusted LFS data are available in our monthly Toronto Economic Bulletin on Open Data. LFS is based on a monthly sample of approximately 2,800 households in the Toronto CMA, about half of the sample is from the city of Toronto; therefore, estimates will vary from the results of a complete census. LFS follows a rotating panel sample design, in which households remain in the sample for six consecutive months. The total sample consists of six representative sub-samples of panels, and each month a panel is replaced after completing its six month stay in the survey. Outgoing households are replaced by households in the same or similar area. This results in a five-sixths month-to-month sample overlap, which makes the design efficient for estimating month-to-month changes. The rotation after six months prevents undue respondent burden for households that are selected for the survey ( see attachment Guide to the Labour Force Survey for more information). Upon reviewing the data, you will see that at least some cells in the IVT tables have been suppressed. For confidentiality reasons, Statistics Canada suppresses Labour Force Survey data for any cell that corresponds to less than 1,500 persons. At the beginning of 2015, Statistics Canada substantially changed the methodology used to produce LFS population estimates for the city of Toronto. These changes have resulted in large and inexplicable swings in population and related counts, which are not real. However, the unemployment and participation rates for city residents showed very little change in this revision. The red dots in the chart above represents Statistics Canada's Annual Demographics estimates for the populations of the city of Toronto, age 15 and over. These are only estimates, but they are generally accepted as the most accurate estimates for the city's population. (Source: https://www150.statcan.gc.ca/n1/pub/91-214-x/91-214-x2018000-eng.htm). The most recent Statistics Canada population estimate for the city of Toronto is for July 1, 2015; therefore, we have to use projections thereafter. There are several population projections for the city. The projection that EDC staff has chosen to use for rebasing city of Toronto LFS data is the Ontario Ministry of Finance Population Projections 2017-2041 and downloaded June, 2017 from http://www.fin.gov.on.ca/en/economy/demographics/projections/ Please see attachment Rebased Labour Force Survey for City of Toronto below for annual adjustment factors, monthly adjustment factors and an example of how to rebase the absolute numbers for the city of Toronto.

The Development Pipeline bulletin examines how and where the City has been growing over the past five years and how it may continue to develop in the near future. It summarizes information from the City of Toronto’s Land Use Information System II, providing an overview of all projects with any development activity between January 1, 2015 and December 31, 2019. This development pipeline data is supplemented by other data sources such as CMHC, Statistics Canada and the Toronto Employment Survey. For further information refer to the bulletin.

This data set contains input from the Community Council boundaries consultation held between May 3 and May 27, 2018 by the City of Toronto. The purpose of posting this dataset is to create a record of the consultation and the public's views, in a respectful way without offensive or otherwise inappropriate content, and to protect the City from legal liability. The data set has been reviewed to ensure that the content does not: 1. Contravene the City's policies or applicable laws related to anti-discrimination, human rights or privacy; 2. Include information that identifies an individual other than one acting in an official capacity, nor any comments that are personal attacks on someone's character, personal or business affairs, etc.; 3. Address an issue before the courts or outside of the City's jurisdiction, or comments on another organization or private company; 4. Contain unsubstantiated rumours or potentially libellous statements; 5. Contain obscenities, derogatory, insulting, offensive, violent or hateful language; 6. Include any email addresses, attachments, or web links. In cases where such comments are found, only the language that contradicts the policy is removed by staff -- the remainder of the comments remains in the data set. The Community Council boundary feedback survey received 619 partial and complete responses and an additional four submissions by email. The purpose of the survey was to collect input on an Options Paper, which was developed by staff and provided information on Community Councils, highlighted three primary, and five alternative models, and asked what issues or considerations would support the selection of a final model for Council's consideration. In addition to collecting information on a preferred model, the consultation sought public input on why one model was thought to be better than another, what geographic considerations would contribute to an effective Community Council, the impact changing the boundaries would have on respondents, and whether or not respondents had previously attended a Community Council meeting. This survey is not a vote. Public and stakeholders opinions, along with technical and policy considerations will all be used to inform City staff recommendations and decisions to be made by City Council. The survey was available in English, Spanish, French, Italian, Portuguese, Urdu, Korean, Chinese Simplified, Panjabi, Tagolog and Tamil. A small number of survey responses (25) were received on paper and entered in by City staff. One Tamil response was received and translated into English for analysis. The data published here includes both complete and incomplete surveys. Further explanation in the readme file and available on request. For more information: https://www.toronto.ca/city-government/accountability-operations-customer-service/city-administration/city-managers-office/key-intiatives/views-on-new-community-council-boundaries-for-the-city-of-toronto-2/

About this dataset

Context

The dataset presents the the household distribution across 16 income brackets among four distinct age groups in Toronto: Under 25 years, 25-44 years, 45-64 years, and over 65 years. The dataset highlights the variation in household income, offering valuable insights into economic trends and disparities within different age categories, aiding in data analysis and decision-making..

Key observations

• Upon closer examination of the distribution of households among age brackets, it reveals that there are 30(1.26%) households where the householder is under 25 years old, 719(30.20%) households with a householder aged between 25 and 44 years, 855(35.91%) households with a householder aged between 45 and 64 years, and 777(32.63%) households where the householder is over 65 years old.
• The age group of 25 to 44 years exhibits the highest median household income, while the largest number of households falls within the 45 to 64 years bracket. This distribution hints at economic disparities within the city of Toronto, showcasing varying income levels among different age demographics.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income brackets:

• Less than $10,000
• $10,000 to $14,999
• $15,000 to $19,999
• $20,000 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $59,999
• $60,000 to $74,999
• $75,000 to $99,999
• $100,000 to $124,999
• $125,000 to $149,999
• $150,000 to $199,999
• $200,000 or more

Variables / Data Columns

• Household Income: This column showcases 16 income brackets ranging from Under $10,000 to $200,000+ ( As mentioned above).
• Under 25 years: The count of households led by a head of household under 25 years old with income within a specified income bracket.
• 25 to 44 years: The count of households led by a head of household 25 to 44 years old with income within a specified income bracket.
• 45 to 64 years: The count of households led by a head of household 45 to 64 years old with income within a specified income bracket.
• 65 years and over: The count of households led by a head of household 65 years and over old with income within a specified income bracket.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Toronto median household income by age. You can refer the same here

This dataset includes information related to all arrests and strip searches. A strip search refers to a search conducted by a police officer on a person, which includes the removal of some or all clothing and a visual inspection of the body. The dataset also includes indicators of whether a person was booked at a police station within 24 hours following a particular arrest event. Due to issues with the booking template, there may be some records where a person was strip searched, but the data does not indicate a booking (i.e., value = 0); in those cases, the user should presume a booking took place. The location of arrest is aggregated to the Division level and refers to where the arrest took place within Division boundaries. Users should not interpret location as the Division to which the arresting officer was assigned. For some arrests, the location could not be geo-coded or the arrest took place outside of City of Toronto boundaries in other jurisdictions; these are indicated by XX. The age of person arrested and/or strip searched is their age at the time of the arrest, as given to the arresting officer.

The High Resolution Digital Elevation Model (HRDEM) product is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The complete coverage of the Canadian territory is gradually being established. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps. The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements. In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generally generated. Most of these datasets have optical digital images as their source data. They are generated at a 2 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km. For some locations in the north, DSM and DTM datasets can also be generated from airborne LiDAR data. In this case, these products will be generated with the same specifications as those generated from airborne LiDAR in the southern part of the country. The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada. Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project. The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. Collaboration is a key factor to the success of the National Elevation Data Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

This data primarily pertains to City-owned trees located on road allowances across Toronto. The intent of the database is to provide an inventory of City owned-trees on the road allowance for inspection and maintenance. Urban Forestry has had requests to determine ownership of trees within the road allowance, and where this has confirmed private ownership, these trees may be in the database as well for future reference. The dataset is limited to the City of Toronto boundaries and is best utilized when overlaid with the City's Street Centreline file. This shape file should not be used for ownership verification. The positioning shown is not accurate as the tree data has been geographically coded to the parcel address, and this will incorrectly indicate the tree location within the private parcel. The Toronto Street Tree data is compiled by Urban Forestry staff during their inspections or tree maintenance work on trees located on City owned street allowances. The database is large covering over 530,000 records and annually Urban Forestry can only update the volume that is worked on. Some data may be several years old and have not been updated recently, so there may be inaccuracies with the data as a result. Note: We are currently updating and improving street tree location information. This is an ongoing process; therefore, some trees may still appear mapped to the address point, whereas others will be mapped in their physical location along the street. For more information please contact Urban Forestry. Downloading This is a fairly large data set. If you have any issues (like a timeout) using the dynamic file downloader (the first link in the "Download Data" section) feel free to use the Alternate Files.

Regional unemployment rates used by the Employment Insurance program, by effective date, current month.

To address Toronto's 2012 budget gap of $774 million, City Council launched a review of all of its services and implemented a multi-year financial planning process. This data set contains the responses to the open-ended questions on the Services Review Public Consultation Feedback Form from members of the public. Approximately 13,000 responses were received (full and partial). The consultation was held between May 11 and June 17, 2011. As a public consultation, respondents chose to participate, and chose which questions to answer. This produced a self-selected sample of respondents. The majority of the responses were from City of Toronto residents. There were some responses from GTA residents. City staff reviewed the data and removed personal information and input violating city policies (for example, contravenes the City's current anti-discrimination policy or confidentiality policy).

Description and Purpose of the Dataset This dataset lists all festivals, special events and exhibits (etc.) approved to appear on the City of Toronto Festivals and Events Calendar. All details are submitted by the event's organizer/organization, reviewed by City of Toronto - Tourism Services staff (against established submission criteria) and approved for posting to the calendar. The City is not responsible for the accuracy of the self-identified data provided by the organizations. Source(s) of the Data The City collects data from event organizers via web interface. City staff review the data for completeness before it goes up on the City's calendar. Accuracy of data is the responsibility of each organization. Update to the City of Toronto Festivals and Events Calendar The City of Toronto Festivals and Events Calendar is undergoing an update that is expected to greatly improve the ease of submitting festival, special event and exhibit information and will provide a better display for the public to view information. The existing data was shared in an XML format. Data for the new calendar will be available in JSON format. Changes have been made to fields and data display may be effected. Note: Image URLs in this feed need to add https://secure.toronto.ca to the beginning. e.g. https://secure.toronto.ca/webapps/CC/fileAPI/edc_eventcal/Arctic_signature_th_ymVcv32iXtmmfg3zXPBH7w.png All details are submitted by the event's organizer/organization, reviewed by City of Toronto - Tourism Services staff (against established submission criteria) and approved for posting to the calendar. The City is not responsible for the accuracy of the self-identified data provided by the organizations.

Description and Purpose of the Dataset This dataset lists all festivals, special events and exhibits (etc.) approved to appear on the City of Toronto Festivals and Events Calendar. All details are submitted by the event's organizer/organization, reviewed by City of Toronto - Tourism Services staff (against established submission criteria) and approved for posting to the calendar. The City is not responsible for the accuracy of the self-identified data provided by the organizations. Source(s) of the Data The City collects data from event organizers via web interface. City staff review the data for completeness before it goes up on the City's calendar. Accuracy of data is the responsibility of each organization. Update to the City of Toronto Festivals and Events Calendar The City of Toronto Festivals and Events Calendar is undergoing an update that is expected to greatly improve the ease of submitting festival, special event and exhibit information and will provide a better display for the public to view information. The existing data was shared in an XML format. Data for the new calendar will be available in JSON format. Changes have been made to fields and data display may be effected. Note: Image URLs in this feed need to add https://secure.toronto.ca to the beginning. e.g. https://secure.toronto.ca/webapps/CC/fileAPI/edc_eventcal/Arctic_signature_th_ymVcv32iXtmmfg3zXPBH7w.png All details are submitted by the event's organizer/organization, reviewed by City of Toronto - Tourism Services staff (against established submission criteria) and approved for posting to the calendar. The City is not responsible for the accuracy of the self-identified data provided by the organizations.

This dataset displays the Open Data intake queue in its raw form. Data here contains attributes relating to how the Toronto Open Data team manages its various requests for updating old and publishing new datasets the Toronto Open Data Portal. Typically, an "Open Data Inquiry" ticket is first opened, prompting Open Data to investigate the possibility of updating or adding new data to the portal. Once the investigation is finished, another ticket will be opened, directing Open Data staff to "Publish a New Open Dataset Page" or "Update an Existing Open Dataset Page". These tickets will be related to the initial inquiry so to track the history of a change from beginning (Inquiry) to end (Publication or Update). Records here are direct from an internal ticket management system, so they match exactly what Open Data staff are working with. Each record is a period of time in which a ticket was in a particular status. The creation of this data is to support council motion 2023.EX10.18 and shared with the hopes that it will inform the public what Open Data is working on, and what datasets Open Data is updating or publishing.

In January 2015, the City's Open Government Committee - senior staff who promote an organizational culture of greater collaboration and openness - organized an internal Open Government Survey for the Toronto Public Service. The purpose of the survey was to learn how City staff viewed Open Government and discover their thoughts and stories about "opening up" government. The honest assessment provided by City staff would enable the committee to set priorities and focus on things that would help Toronto achieve the City's Strategic Action #13 Open Government by Design. Comment: The data represented here was provided only by a subset of City staff. Personal and identifiable information was removed in accordance with privacy standards. The City is committed to 'opening up government'. Open Government is about ensuring access to timely, reliable and relevant information which enables the public to choose when and how to use City services or engage in policy decision-making. Being transparent about what the City does demonstrates accountability. Being open builds public trust and confidence in government.

This dataset includes data on parking lots operated by the City of Toronto PF&R Division. Parking lots are located in parks or on the building grounds of community centres, schools, pool buildings, etc. These buildings or parks are considered parent assets of parking lots and listed in 'Park Name' column. A parking lot has certain number of spaces including handicap spots. Every parking lot is identified by (X, Y) GIS coordinate. Parking lots may be private, open for public, or used by members/staff only. Thus, parking lot information you'll find in this dataset is the following: - Parking Lot Asset ID - Park Name - Parking Spaces - Handicap Parking Spaces - GIS Coordinates - Access Comment: The source of the data is the City of Toronto Parks, Forestry & Recreation Asset Management System. Dataset has gone through necessary inter-divisional validation and on-site validation with parks supervisors. The dataset contains information about parking lots operated by Parks, Forestry, and Recreation Division of the City of Toronto. All other City-owned parking lots (either public, or private) are out of scope of this dataset. Valid date range of the data: 2013 - 2015. Data is currently going through additional validation process, estimated to be completed at the end of 2016. Some facilities or some values may be missing from the dataset. These will be added after data is captured by the validation team. As per the end of the validation, additional refresh of the data is planned.

The dataset, titled "Building Permits - Green Roofs," falls under the domain of Development and Infrastructure and Permits and Licenses. It is tagged with keywords such as Housing Potential, building permit, and green roof. The dataset is available in various formats including JSON, XML, CSV, and MS Excel. It was published on July 23, 2019, and the location of the dataset is provided. The owner of the dataset is Toronto Building, and the author is also listed as opendata@toronto.ca, who can be contacted via the same email for any queries. The dataset is owned by the City of Toronto Open Data organization. The dataset provides information about the Green Roof By-law adopted by Toronto City Council in May 2009. It explains that Toronto is the first city in North America to have a by-law requiring and governing the construction of green roofs. The bylaw applies to new commercial, institutional, and many residential development applications and to certain developments not completed before the bylaw came into effect on Jan 31, 2010. The source of the dataset is provided, and it is licensed under the Open Government Licence – Toronto. The resources available in the dataset include 'Building Permits - Green Roofs Data' in various formats and a readme file. The metadata for the dataset was created on October 4, 2024, and last modified on April 8, 2025.

This dataset includes data on drinking water sources (i.e. drinking fountains, bottle filling stations, dog fountains and combination units) operated by the City of Toronto Parks, Forestry and Recreation (PFR) division. Only drinking water sources that have been deemed as operational at the time of data validation exercise are included in this dataset. Drinking water sources have a "turn on" and "turn off" time period (turn on - May and turn off - October) and do not function throughout the entire year. The data provided is sourced from the City of Toronto Parks, Forestry and Recreation Asset Management System. The dataset has been validated by on-site parks supervisors and through necessary inter-divisional staff. Note: This dataset only contains information about drinking water sources operated by Parks, Forestry and Recreation division of the City of Toronto. All other City-owned drinking water sources are out of scope of this dataset.