Science and technology

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: 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: 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:

Percentage of enterprises that used specific types of advanced or emerging technologies, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Advanced technologies include material handling, supply chain or logistics technologies; design or information control technologies; processing or fabrication technologies; clean technologies; security or advanced authentication systems; business intelligence technologies; and other types of advanced technologies. Emerging technologies include nanotechnology, biotechnology, geomatics or geospatial technologies, artificial intelligence (AI), integrated Internet of Things (IoT) systems, blockchain technologies, and other types of emerging technologies.

Description:

Percentage of enterprises that did not adopt or use advanced technologies for specific reasons, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Reasons for not adopting or using advanced technologies include not convinced of economic benefit; difficulty in obtaining financing; high cost of advanced technologies; investment not necessary for continuing operations; lack of technical skills required to support this type of investment; organizational culture too inflexible; decisions made by parent, affiliates or subsidiary businesses; lack of technical support or services (from consultants or vendors); lack of information regarding advanced technology; difficulty in integrating new advanced technologies with existing systems, standards and processes; other reasons for not adopting or using advanced technologies; and adoption or use of advanced technologies not applicable to this business’s activities.

Description: Percentage of enterprises where the use of clean technologies was related to environmental protection, sustainable resource management or adapted goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Environmental protection includes air and environment protection or remediation; waste management, reduction or recycling; and water or wastewater treatment. Sustainable resource management includes alternative fuels; non-emitting energy supply; bio-products; smart grid; energy storage; energy management and efficiency improvements; water management or recycling; agriculture, aquaculture, forestry or biodiversity improvements; and sustainable mining. Adapted goods include energy-efficient transportation, energy-efficient equipment or appliances, and advanced or lightweight materials.

Description:

Percentage of enterprises for which specific long-term strategies were the most important, by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. The most important long-term strategies include main focus on good or service positioning, main focus on low-price and cost leadership, and good or service positioning and low-price and cost leadership are equally important.

Description:

Percentage of enterprises for which specific statements best described their strategic focus regarding goods or services (products), by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. Statements that best described enterprises’ strategic focus regarding goods or services (products) include maintain sales of existing goods or services, expand the sales of existing goods or services, introduce new or significantly improved goods or services regularly, and don’t know.

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:

Percentage of enterprises that used specific types of advanced or emerging technologies, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Advanced technologies include material handling, supply chain or logistics technologies; design or information control technologies; processing or fabrication technologies; clean technologies; security or advanced authentication systems; business intelligence technologies; and other types of advanced technologies. Emerging technologies include nanotechnology, biotechnology, geomatics or geospatial technologies, artificial intelligence (AI), integrated Internet of Things (IoT) systems, blockchain technologies, and other types of emerging technologies.

Description:

Percentage of enterprises that did not adopt or use advanced technologies for specific reasons, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Reasons for not adopting or using advanced technologies include not convinced of economic benefit; difficulty in obtaining financing; high cost of advanced technologies; investment not necessary for continuing operations; lack of technical skills required to support this type of investment; organizational culture too inflexible; decisions made by parent, affiliates or subsidiary businesses; lack of technical support or services (from consultants or vendors); lack of information regarding advanced technology; difficulty in integrating new advanced technologies with existing systems, standards and processes; other reasons for not adopting or using advanced technologies; and adoption or use of advanced technologies not applicable to this business’s activities.

Description: Percentage of enterprises where the use of clean technologies was related to environmental protection, sustainable resource management or adapted goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Environmental protection includes air and environment protection or remediation; waste management, reduction or recycling; and water or wastewater treatment. Sustainable resource management includes alternative fuels; non-emitting energy supply; bio-products; smart grid; energy storage; energy management and efficiency improvements; water management or recycling; agriculture, aquaculture, forestry or biodiversity improvements; and sustainable mining. Adapted goods include energy-efficient transportation, energy-efficient equipment or appliances, and advanced or lightweight materials.

Description:

Percentage of enterprises for which specific long-term strategies were the most important, by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. The most important long-term strategies include main focus on good or service positioning, main focus on low-price and cost leadership, and good or service positioning and low-price and cost leadership are equally important.

Description:

Percentage of enterprises for which specific statements best described their strategic focus regarding goods or services (products), by North American Industry Classification System (NAICS) code and enterprise size, over the next five years. Statements that best described enterprises’ strategic focus regarding goods or services (products) include maintain sales of existing goods or services, expand the sales of existing goods or services, introduce new or significantly improved goods or services regularly, and don’t know.

Description:

Percentage of enterprises that sold only goods, only services or both goods and services, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

Description:

Percentage of enterprises that produced or manufactured any of the goods that they sold, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period.

Description:

Percentage of enterprises that offered specific services to complement the sale of goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Complementary services include after-sales maintenance or repair, installation or implementation, training or technical support, after-sales condition monitoring or quality control, customization, distribution or transportation, leasing or rental agreements, and other services.

Description:

Percentage of enterprises that expanded capacity for specific services to complement the sale of goods, by North American Industry Classification System (NAICS) code and enterprise size, based on a three-year observation period. Complementary services include after-sales maintenance or repair, installation or implementation, training or technical support, after-sales condition monitoring or quality control, customization, distribution or transportation, leasing or rental agreements, and other services.

Description:

This paper presents an open-source system that was developed for automatic estimation of building height from street-view images using Deep Learning (DL), advanced image processing techniques, and geospatial data. The goal of the developed system is to ultimately be used to enrich the Open Database of Buildings (ODB), that was published by Statistics Canada, as a part of the Linkable Open Data Environment (LODE). Some of the obtained results for building-height estimation are presented. Some challenging cases and the scalability of the system are discussed as well.

Description:

This infographic uses data from the Business Innovation and Growth Support and Linkable File Environment. It shows the relative distribution of beneficiaries and value of federal support related to business innovation and growth in 2018 by employment size, revenue size and industry.

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

Description:

Recent improvements in robotics have rekindled ancient fears about the impact of robotics on humankind. Unfortunately, existing data seldom distinguishes robots from other types of automation, so research into their impact so far has been difficult. This article introduces research from a new Statistics Canada dataset, Robots!, on the impact of robots at the firm-level. The article examines the impact of robot investment on firm performance and employment at the enterprise level.

Description:

Prior to the COVID-19 pandemic, advances in artificial intelligence and robotics raised concerns that automation might lead to relatively high unemployment rates in the coming years. This Economic Insights article examines the degree to which Canadians’ views about the impact of automation on net job creation in 1989 materialized three decades later.

Description:

This infographic describes the invesment in robots in the Canadian economy and its impact on employment.

Description:

Recent advances in artificial intelligence have rekindled ancient fears that robots will replace humans in the economy. Previous waves of automation changed but did not reduce labour’s role, but robots’ human-like flexibility could make this time different. Whether or not it will is an empirical question that has lacked suitable data to answer. This paper describes the creation of a dataset to fill the evidence gap in Canada. Robots! is firm-level panel data on robot adoption created using Canadian import data. The data identify a substantial amount of the robot investment in the Canadian economy from 1996 to 2017. Although many robots are imported by robotics wholesalers or programmers for resale, the majority of them can be attributed to their final (direct) adopting firm. The data can be used to study the impact of robot adoption at the economic region, industry or firm-level.

Description:

This study examines how employment and organizations have changed in response to robot adoption. As robotics and artificial intelligence (AI) become increasingly used by firms as the next engine of innovation and productivity growth, their effects on labour, firm practices and productivity have become a subject of growing importance. The study provides the most comprehensive evidence possible at the level of individual businesses on the employment and organizational effects of robot investments.

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 2020 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:

This infographic provides an overview of the Canadian Research and Development Classification (CRDC), a national standard jointly developed by the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Social Sciences and Humanities Research Council of Canada (SSHRC), and Statistics Canada.

Description: Gross domestic expenditure on research and development (GERD) is a statistical series, constructed by adding together the intramural expenditures on research and development (R&D) as reported by the performing sectors.

Description: This survey collects information related to research and development (R&D) in post secondary institutions in Canada, in particular information related to faculty teaching, research, administration and service. The data from the survey is an important component in estimating higher education research and development expenditures (HERD).

Description: This survey measures the general familiarity of owners and managers of enterprises across selected industries with intellectual property (IP). The purpose of collecting this information is to help evaluate impacts of Canadian Government programs to educate and raise awareness on the value of intellectual property.