The Regional Tourism Profiles contain tourism statistics at the regional level. The profiles include reports on visits, spending, the number of tourism related businesses, hotel performance and itemized tourism receipts.

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) State visited (15 items: Florida; New York; Washington; California; ...) Travel characteristics (3 items: Visits; Nights; Spending in country).

Analysis of ‘Travel Review Rating Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/wirachleelakiatiwong/travel-review-rating-dataset on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Context

This data set has been sourced from the Machine Learning Repository of University of California, Irvine (UC Irvine) : Travel Review Ratings Data Set. This data set is populated by capturing user ratings from Google reviews. Reviews on attractions from 24 categories across Europe are considered. Google user rating ranges from 1 to 5 and average user rating per category is calculated.

Content

Attribute 1 : Unique user id Attribute 2 : Average ratings on churches Attribute 3 : Average ratings on resorts Attribute 4 : Average ratings on beaches Attribute 5 : Average ratings on parks Attribute 6 : Average ratings on theatres Attribute 7 : Average ratings on museums Attribute 8 : Average ratings on malls Attribute 9 : Average ratings on zoo Attribute 10 : Average ratings on restaurants Attribute 11 : Average ratings on pubs/bars Attribute 12 : Average ratings on local services Attribute 13 : Average ratings on burger/pizza shops Attribute 14 : Average ratings on hotels/other lodgings Attribute 15 : Average ratings on juice bars Attribute 16 : Average ratings on art galleries Attribute 17 : Average ratings on dance clubs Attribute 18 : Average ratings on swimming pools Attribute 19 : Average ratings on gyms Attribute 20 : Average ratings on bakeries Attribute 21 : Average ratings on beauty & spas Attribute 22 : Average ratings on cafes Attribute 23 : Average ratings on view points Attribute 24 : Average ratings on monuments Attribute 25 : Average ratings on gardens

Acknowledgements

This data set has been sourced from the Machine Learning Repository of University of California, Irvine (UC Irvine) : Travel Review Ratings Data Set

The UCI page mentions the following publication as the original source of the data set: Renjith, Shini, A. Sreekumar, and M. Jathavedan. 2018. Evaluation of Partitioning Clustering Algorithms for Processing Social Media Data in Tourism Domain. In 2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 12731. IEEE

Inspiration

I'm kind of people who love traveling. But sometimes I've problems like where should I visit? Are there somewhere interesting places matched with my lifestyle? Often I spent hours to search for interesting place to go out. Such a waste of time.

What if we can build a recommender system which can recommend you several interesting venue based on your preferences. With information from Google review, I'll try to divide Google review user into cluster of similar interest for further work of building recommender system based on thier preference.

--- Original source retains full ownership of the source dataset ---

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).

International travel by non-Canadian visitors coming to Canada for a trip. Data come from Frontier Counts, part of the Tourism Statistics Program.

This dataset provides information on 52 in California, United States as of May, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

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) Countries visited (15 items: United States; Mexico; United Kingdom; France; ...) Travel characteristics (3 items: Visits; Nights; Spending in country).

The travel time map was generated using the Pedestrian Evacuation Analyst model from the USGS. The travel time analysis uses ESRI's Path Distance tool to find the shortest distance across a cost surface from any point in the hazard zone to a safe zone. This cost analysis considers the direction of movement and assigns a higher cost to steeper slopes, based on a table contained within the model. The analysis also adds in the energy costs of crossing different types of land cover, assuming that less energy is expended walking along a road than walking across a sandy beach. To produce the time map, the evacuation surface output from the model is grouped into 1-minute increments for easier visualization. The times in the attribute table represent the estimated time to travel on foot to the nearest safe zone at the speed designated in the map title. The bridge or nobridge name in the map title identifies whether bridges were represented in the modeling or whether they were removed prior to modeling to estimate the impact on travel times from earthquake-damaged bridges.

The properties in this polygon layer have been issued Amusement business licenses by the City of Niagara Falls. Business licenses are renewable annually and this data set has a spatial record for each year of issue for each location. The business name, address, license document ID, and year of issuance are included as attributes.

IMPORTANT NOTE: The Ministry of Tourism (MTO) has begun the migration of its data to a new tourist information system, the SIT Québec. The operation will take place over several months, during which time this open data set will no longer be updated. However, it will remain available as an archive on the Data Québec portal, until a replacement process for the publication of open data is put in place. Note that the upcoming open data set may be published in a different granularity and information format. Comprising approximately 240 tourist reception and information sites spread across the regions of Quebec, the network offers tourists and excursionists information on attractions, activities, accommodations and restaurants, as well as comprehensive tourist documentation, as well as comprehensive tourist documentation so that they can make the most of their stay.This third party metadata element was translated using an automated translation tool (Amazon Translate).

Number of cruise ship passenger visitors. Dataset broken down by the Port of Halifax and Port of Sydney. Data is reported quarterly.

Gross domestic product (GDP), employment, labour compensation per job, GDP per job and tourism share of employment and GDP by tourism industry, by province and territory.

Each Regional Tourism Organization is an independent, industry-led and not- for-profit and each provides leadership and coordination to support competitive and sustainable tourism regions. Ontario Regional Tourism Boundary data come in polygon and line versions. The polygon version is the main version and has the Region ID number. The line version is for cartographic purposes, as it shows the boundaries but contains no attributes (e.g., Region ID).

"https://www.ontario.ca/document/tourism-regions">More information on regional tourism

*[ID]: identification *[e.g.]: for example

Self-reported data from approximately 380 public libraries, First Nation public libraries and contracting organizations. The data includes:

• general information including address
• financial information
• holdings information
• staffing information
• facilities information
• activities information including typical week data
• partnership information (2011 onwards)

Data from 2011 and onwards is from a refreshed database. New fields were added for:

• provincial funding types
• project grant types
• special collections holdings
• circulation of E-resources including E-books
• lending laptops
• program types
• readers advisory transactions
• information technology support

In 2012, new fields were added for:

• E-readers
• requests for accessible format materials
• business and economic partnerships.

In 2013 more fields were added for social media visits and other professional staff.

In 2016 a field was added for indigenous language training and retention, while circulating and reference holdings information was combined.

In 2017 fields were added for e-learning services, students hired for a summer or semester, circulating wireless hot spots, and library service visits to residence-bound people.

In 2019 fields were added for Facility Rentals and Bookings, ‘Pop-up’ Libraries, Extended Services and Facilities, Government Services Partnerships, and Business and Economic Sector Partnerships.

The database uses the common name "LibStats".

Number of outbound visits by residents of Ontario to selected provinces. ## Related * Outbound visits * Outbound visitor spending * Outbound visitor spending by province * Outbound visitor spending by country * Outbound visits by country * Outbound visits by U.S. state * Outbound visitor spending by U.S. state *[U.S.]: United States

This table presents information on tourism spending of foreign visitors in Canada by country of residence, tourism region and spending category. Country of residence is organised into eleven major source of travellers to Canada including the United States, Australia, China, Japan, South Korea, India, United Kingdom, France, Germany, Mexico and other overseas countries. Spending categories include accommodation, food and beverage, transportation in Canada, recreation and entertainment, and clothes and gifts.

Number of vehicles travelling between Canada and the United States, by trip characteristics, length of stay and type of transportation. Data available monthly.

This table contains 12 series, with data for years 1980 - 1996 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada), Travel duration (3 items: Total, same day and overnight travel; Same day; Overnight), Age and sex (4 items: Total both sexes, all ages; Both sexes, under 15 years; Males, 15 years and over; Females, 15 years and over).

This table contains 333 series, with data for years 1972 - 2018 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (13 items: Canada; Newfoundland and Labrador; Prince Edward Island; Nova Scotia; ...) Traveller characteristics (15 items: Total non resident tourists; United States tourists; United States tourists entering by automobile; United States tourists entering by plane; ...) Seasonal adjustment (2 items: Unadjusted; Seasonally adjusted).

In a context of numerous projects, Montreal has made every effort to improve the mobility of users, all modes of transport combined. The [MTL Trajet] application (https://ville.montreal.qc.ca/mtltrajet/) is one of the many measures put forward to better understand and facilitate travel in Montreal. This set contains the filtered data collected during this study. The data is divided into two different sets to offer the maximum amount of data without compromising the confidentiality of users of the MTL Trajet application. Points The “points_mtl_trip” dataset includes each of the points, with an acceptable positioning quality, collected during the MTL Trajet travel survey. These points have been treated and filtered to remove all sensitive items on a user. Journeys This file includes each of the trips obtained using the filtered data. This file is therefore an agglomeration of points into segments making it possible to define the routes of users. These segments were produced using the OSRM routing engine in order to identify points on the networks (lanes, bike paths, subway, suburban train). In order to protect the privacy of users of the application, the information allowing trips to be linked to users has been removed. These trips are then complete; on the other hand, it is impossible to determine whether two trips were made by the same user.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**