Science and technology

Description:

This table contains 140 series, with data for years 2014 - 2015 (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) Intellectual property and other technology related services (10 items: Total intellectual property and other technology related services; Patents; Copyrights; Trademarks; ...) Payments made and received for intellectual property and other technology related services (14 items: Payments made; Payments to parent, affiliated or subsidiary companies; Payments to parent, affiliated or subsidiary companies made within Canada; Payments to parent, affiliated or subsidiary companies made outside Canada; ...).

Description:

This table contains 1500 series, with data for years 2014 - 2015 (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) North American Industry Classification System (NAICS) (75 items: Total all industries; Agriculture, forestry, fishing and hunting; Agriculture (except aquaculture) and support activities for crop production and animal production; Forestry, logging and support activities for forestry; ...) Intellectual property and other technology related services (10 items: Total intellectual property and other technology related services; Patents; Copyrights; Trademarks; ...) Payments made and received for intellectual property and other technology related services (2 items: Payments made; Payments received).

Description:

This interactive data visualization dashboard provides a comprehensive picture of research and development (R&D) activities in Canadian industry. Users will find extensive coverage of characteristics on R&D activities in Canadian industry. The dashboard features information on in-house as well as outsourced R&D expenditures, statistics on energy-related R&D expenditures by area of technology and details on intellectual property product commerce.

Description: As we begin to use these new versions of AI, our jobs are destined to change. So, what will an average day of work look like a decade from now? Which jobs will AI impact the most? And is AI coming to replace our jobs all together? In this episode, we sat down with AI expert Tahsin Mehdi, an economist in the social analysis and modeling division of Statistics Canada, to answer our questions about how AI will transform our work lives in Canada.

Description: Annual estimates of capital expenditures on environmental protection and resource management activities by North American Industry Classification System (NAICS) and geography. The unit of measure is dollars (x1,000,000).

Description: Annual estimates of the percentage of enterprises that reported drivers and obstacles to the purchase of technologies, systems or equipment related to environmental protection by North American Industry Classification System (NAICS). The unit of measure is percent.

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:

Product innovators' average percentage of sales that came from products that were new to one of the business's markets, new only to the business, and unchanged or marginally modified in three years, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Estimates refer to fiscal year 2017 (end date falling after January 1, 2017 and on or before December 31, 2017).

Description:

Average expenditures (x 1,000) on specific innovation activities, by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Innovation activities include research and experimental development; acquisition or development of advanced technology; design activities related to other organizations; employee training specifically for innovation projects; consultation activities with external experts or internal workgroups; activities related to the development and implementation of new marketing methods; market preparation activities directly linked to the introduction of new goods or services; and other innovation activities. Estimates refer to fiscal year 2017 (end date falling after January 1, 2017 and on or before December 31, 2017).

Description:

The number of full-time equivalent (FTE) personnel employed outside Canada by businesses that are not an affiliate of a foreign parent (in the United States of America, Mexico, other Latin American and Caribbean countries, Europe, China, other Asian countries or all other countries), by North American Industry Classification System (NAICS) code and enterprise size, based on a one-year observation period. Estimates refer to fiscal year 2017 (end date falling after January 1, 2017 and on or before December 31, 2017).

Description: Provincial estimates of research and development expenditures in the higher education sector, by funding sector and type of science by provinces, from 2000 to today.

Description: Total domestic expenditures on research and development (R&D) as percentage of gross domestic product (GDP). This table is included in Section D: Postsecondary education: Research and development of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

Description: Percentage of total research and development (R&D) expenditure by performing sector. This table is included in Section D: Postsecondary education: Research and development of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

Description: Sources of funds for expenditures on research and development (R&D) in the higher education sector. This table is included in Section D: Postsecondary education: Research and development of the Pan Canadian Education Indicators Program (PCEIP). PCEIP draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, education finance and labour market outcomes. The program presents indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. PCEIP is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.

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Percentage of enterprises that allow the use of personally-owned devices to carry out regular business-related activities by the North American Industry Classification System (NAICS) and size of enterprise.

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Percentage of enterprises that have a specific number of employees that complete tasks related to cyber security as part of their regular responsibilities by the North American Industry Classification System (NAICS) and size of enterprise.

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Percentage of enterprises that use specific risk management arrangements to manage cyber security risks by the North American Industry Classification System (NAICS) and size of enterprise.

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Average spending on specific measures to prevent or detect cyber security incidents by the North American Industry Classification System (NAICS) and size of enterprise.

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Average spending on specific measures to recover from cyber security incidents by the North American Industry Classification System (NAICS) and size of enterprise.

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Percentage of enterprises impacted by cyber security incidents in specific ways by the North American Industry Classification System (NAICS) and size of enterprise.

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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:

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:

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.

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

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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: 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.

Description: The survey on Research Activities and Commercialization of Intellectual Property in Higher Education collects information on how research conducted and produced in the higher education sector is transferred to the private sector.