Science and technology

Description: Challenges faced by business or organization when adopting or incorporating technologies, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

Description: Use of artificial intelligence (AI) by businesses and organizations in producing goods or delivering services over the last 12 months, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

Description: Extent to which artificial intelligence (AI) has reduced tasks previously performed by employees and the impact of AI use on total employment, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

Description: Changes made by business or organization when using artificial intelligence (AI) to produce goods or deliver services, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

Description: New or significantly improved goods or services brought onto the market from 2020 to 2023, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

Description: Innovation of new products or services and most significant recent product innovation was new to its market, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2024.

Description: This article explores trends in patent applications made by Canadian-resident businesses for advanced technologies from 2001 to 2019, drawing on Eurostat's aggregation of high-tech patents. Approximately one-third of applications fall under high-tech categories, the bulk of which were associated with Communication, Computer, and Automated business equipment technologies. While these fields saw growth until 2012, a subsequent decline occurred, notably in Computer and Electronic Product Manufacturing. Biotechnology, Semiconductors, and Lasers showed limited dynamism, while aviation technology applications surged by nearly twentyfold over the period.

Description: This study compares the Government of Canada’s direct and indirect measures to support R&D, as captured by business innovation and growth support (BIGS) programs and the Scientific Research and Experimental Development (SR&ED) tax incentive program. BIGS and SR&ED are two central instruments that the Canadian government uses to stimulate R&D expenditures in the business sector.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: This classification system was developed conjointly by the Social Sciences and Humanities Research Council of Canada (SSHRC), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), and Statistics Canada which is the custodian. This shared standard classification, inspired by the Frascati Model 2015 of the Organisation for Economic Co-operation and Development (OECD), will be used by the federal granting agencies and Statistics Canada to collect, and disseminate data related to research and development in Canada. The Canadian Research and Development Classification (CRDC) first official version was the 2020 Version 1.0, now being replaced by CRDC Version 2.0. The CRDC is revised within 2 years for minor changes, and every five years for major revisions. CRDC 2020 Version 2.0 is composed of 3 main pieces: the type of activity or TOA (with 3 categories), the field of research or FOR (with 1,671 fields at the lowest level) and socioeconomic objective or SEO (with 85 main groups at the lowest level).

Description: This dashboard shows traffic count data that is obtained from traffic camera imagery using a computer vision-based system developed at the Data Exploration and Integration Lab (DEIL) at Statistics Canada. The system periodically pulls traffic imagery from the Application Programmable Interfaces (APIs) of municipal and provincial traffic camera programs. Vehicle detection was implemented using the open source You Only Look Once version 3 (YOLOv3) object detection model that was trained on the Common Objects in Context (COCO) dataset. The output of the model is used to generates real-time counts of the detected vehicles (cars, trucks, buses, motorcycles).

Description: Federal expenditures on science and technology and its components in current dollars and 2012 constant dollars by type of expenditures for Canada from 1995 to today.

Description: Federal expenditures on science and technology and its components, by type of science and technology components and performing sector for Canada from 1998 to today.

Description: Federal expenditures by science and technology components and activities and by performing sector for Canada from 2003 to today.

Description: Federal intramural expenditures by science and technology components and type of science for the National Capital Region from 1994 to today.

Description: Federal personnel engaged in science and technology activities, by type of science and personnel category for Canada from 1993 to today.

Description: Federal personnel engaged in science and technology and its components, by type of science and personnel category for Canada from 1993 to today.

Description: Federal personnel engaged in science and technology and its components, by type of science, personnel category, for provinces and territories from 2000 to today.

Description: Federal expenditures on science and technology and its components, by type of science and performing sector for Canada, provinces, territories and foreign from 2004 to today.

Description: Federal extramural expenditures on science and technology and its components, by type of science, performing sector, type of payment, for Canada and foreign, provinces and territories from 2003 to today.

Description:

As the ninth goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation by 2030. This 2022 infographic provides an overview of indicators underlying the ninth Sustainable Development Goal in support of industry, innovation and infrastructure, and the statistics and data sources used to monitor and report on this goal in Canada.

Description:

Monitoring traffic in large urban areas remains a challenge for both practical and technical reasons. This paper presents a computer vision-based system to periodically extract vehicle counts from Canadian traffic camera imagery.

Description:

This paper documents the use of the Worldwide Patent Statistical Database (PATSTAT), a global patent application database created by the European Patent Office, to create the Canadian Research Patent Database at Statistics Canada. Innovation is an important driver of the economy, and patent statistics are recognized as a useful measure of innovative activity. The current version of the Canadian Research Patent Database focuses on the worldwide patent applications of businesses with an address in Canada (Canada-resident businesses).

Description:

This article presents some initial findings from a new longitudinal database created from administrative data sources to study patenting in Canada. The study of patenting is important as patenting is a measure of innovative activity and has been linked to positive economic outcomes for firms.

Description:

This study examines the economic footprint created by the Canadian research and development pharmaceutical sector on the Canadian economy in 2019, including a focus on the contribution of Innovative Medicines Canada’s members. While the impact of the sector’s medical research is well known, less known are the economic impacts of the sector on the Canadian economy, such as the value generated, the jobs supported and the investments made.

Description:

Micro-level information on buildings and physical infrastructure is increasing in relevance to social, economic and environmental statistical programs. Alternative data sources and advanced analytical methods can be used to generate some of this information. This paper presents how multiple convolutional neural networks (CNNs) are finetuned to classify buildings into different types (e.g., house, apartment, industrial) using their street-view images. The CNNs use the structure of the façade in the building’s image for classification. Multiple state-of-the-art CNNs are finetuned to accomplish the classification task. The trained models provide a proof of concept and show that CNNs can be used to classify buildings using their street-view imagery. The training and validation performance of the trained CNNs are measured. Furthermore, the trained CNNs are evaluated on a separate test set of street-view imagery. This approach can be used to augment the information available on openly accessible databases, such as the Open Database of Buildings.

Description:

The entrepreneurship indicator database provides data describing the dynamics of a subset of Canadian enterprises, such as the number of active enterprises with one or more employees, the number of high-growth enterprises, the number of births and deaths of active enterprises with one or more employees, the survival of newly created enterprises, and more.

Description:

This study examines the economic footprint created by the Canadian research and development pharmaceutical sector on the Canadian economy in 2018, including a focus on the contribution of Innovative Medicines Canada’s members. While the impact of the sector’s medical research is well known, less known are the economic impacts of the sector on the Canadian economy, such as the value generated, the jobs supported and the investments made.

Description:

The federal government offers business innovation and growth support through program streams managed by its departments and agencies. In 2017, enterprises in the manufacturing sector accounted for almost one-quarter of the beneficiaries of this support and received almost one-third of the total value of support (Statistics Canada, 2020). The objective of this analysis is to assess the impact of federal growth and innovation support on the employment and revenue of beneficiary enterprises in the manufacturing sector between 2007 and 2017. This analysis suggests that enterprises that received federal support for growth and innovation experienced stronger employment and revenue growth relative to non-beneficiary enterprises. Over the three years following receipt of support, employment growth for beneficiary enterprises averaged 1.8% per year while, on average, enterprises that did not receive support experienced employment declines. Over the same period, the average annual revenue growth of beneficiary enterprises was higher than that of non-beneficiary enterprises by 4.6 percentage points.

Description:

Over the past two decades, Canadians have embraced digital technologies at an unprecedented pace and breadth. The objective of this study is to develop statistical indexes to measure the intensity of digitalization in Canadian industries. Because of the ubiquitous presence of digitalization and businesses’ and individuals’ increasing reliance on digital products and services, it is essential to measure the digitalization in the Canadian economy to better understand its impact so that governments, businesses and other stakeholders can make informed decisions.

Description: This survey was sponsored by the Ontario Ministry of Economic Development and Trade.

Description: The Annual Survey of Research and Development in Canadian Industry collects research and development (R&D) expenditures and personnel data used to monitor science and technology related activities of businesses and industrial non-profit organizations in Canada.

Description: The Annual Survey of Research and Development of Canadian Private Non-Profit Organizations produces useful statistical information to monitor science and technology activities in Canada and to support the development of science and technology policy.

Description: This survey collects in-house and outsourced research and development expenditures on energy-related technology of businesses and industrial non-profit organizations in Canada.

Description: This annual survey collected data in all areas of technology, by Canadian firms operating in the petroleum industries.

Description: This survey collects detailed expenditure and full-time equivalent personnel data on the scientific activities of provincial research organizations.

Description: These statistical estimates cover scientific and technological (S&T) activities of the provincial government sector, except for provincial research organizations (PRO) which are surveyed separately (see record number 4208).

Description: These statistical estimates cover scientific and technological (S&T) activities of the provincial government sector, except for provincial research organizations (PRO) which are surveyed separately (see record number 4208).

Description: This survey collects financial and operating data on expenditures and full-time equivalent personnel on the scientific activities of Federal Government Public Administration in Canada.

Description: The information collected by this survey provides information on innovation and innovation activities of Canadian businesses and their characteristics.