A complete list of live websites using the Wp Table Builder technology, compiled through global website indexing conducted by WebTechSurvey.

Each year, the Department of Education in partnership with the Department of Children, Equality, Disability, Integration and Youth and Department of Department of Further and Higher Education, Research, Innovation and Science publish a set of annual indicators on the Education System in Ireland. The report contains over 200 statistical indicators going back to 2014. This application allows users to explore the data in the indicators report, to build a table containing multiple indicators and download the results for their own use.

A complete list of live websites using the Price Table Builder technology, compiled through global website indexing conducted by WebTechSurvey.

ABS TableBuilder outputsAustralian Bureau of Statistics (2021) MB/SA1/SA2 by Household Family Composition (HCFMD) [Census TableBuilder], accessed 1 July 2023.

This dataset presents the employment rate of the population in small regions of Australia based on the 2016 Census and aggregated following the 2016 edition of the Australian Statistical Geography Standard (ASGS). The data has been provided by The National Centre for Social and Economic Modelling (NATSEM). This indicator is the number and proportion of people employed. The rate is calculated as the number employed divided by the total number in that Age/Sex group (excluding Not Stated). Note that the denominator for the total employment rate is total population aged 15-64. All indicators were extracted from the ABS Tablebuilder system using the usual residence profile. For usual residence data, the ABS moves people back to where they live, rather than using the location the data were collected (place of enumeration). Usual residence data is preferred for individual level data because it removes the effect of respondents travelling or holidaying. For more information please view the NATSEM Technical Report.

The Australian Census Longitudinal Dataset (ACLD) brings together a 5% sample from the 2006 Census with records from the 2011 Census to create a research tool for exploring how Australian society is changing over time. In taking a longitudinal view of Australians, the ACLD may uncover new insights into the dynamics and transitions that drive social and economic change over time, conveying how these vary for diverse population groups and geographies. It is envisaged that the 2016 and successive Censuses will be added in the future, as well as administrative data sets. The ACLD is released in ABS TableBuilder and as a microdata product in the ABS Data Laboratory. \r \r The Census of Population and Housing is conducted every five years and aims to measure accurately the number of people and dwellings in Australia on Census Night. \r \r Microdata products are the most detailed information available from a Census or survey and are generally the responses to individual questions on the questionnaire. They also include derived data from answers to two or more questions and are released with the approval of the Australian Statistician.\r The following microdata products are available for this longitudinal dataset: \r •ACLD in TableBuilder - an online tool for creating tables and graphs. \r •ACLD in ABS Data Laboratory (ABSDL) - for in-depth analysis using a range of statistical software packages.\r \r

Key Statistics on Business Performance and Operating Characteristics of the Building, Construction and Real Estate Sectors - Table 615-73013 : Principal statistics for all establishments in the construction sector by industry value added

A complete list of live websites using the Drag Drop Pricing Tables Builder technology, compiled through global website indexing conducted by WebTechSurvey.

This ArcGIS model inserts a file name into a feature class attribute table. The tool allows an user to identify features by a field that reference the name of the original file. It is useful when an user have to merge multiple feature classes and needs to identify which layer the features come from.

This code is used to compile China's MRIO table based on the semi-survey method.

Robotic Sand Table Terrain Builder Market Outlook

According to our latest research, the global market size for Robotic Sand Table Terrain Builders in 2024 stands at USD 1.3 billion, with a robust compound annual growth rate (CAGR) of 12.7% projected from 2025 to 2033. By the end of 2033, the market is forecasted to reach an impressive USD 3.9 billion. This remarkable growth is primarily driven by increasing adoption in military training, educational innovation, and the integration of advanced robotics and artificial intelligence in simulation technologies.

One of the principal growth factors for the Robotic Sand Table Terrain Builder market is the escalating demand for realistic, interactive, and cost-effective simulation tools in military training and defense applications. Modern military strategies require advanced visualization and scenario planning tools, and robotic sand tables provide a dynamic and tangible platform for terrain analysis, mission rehearsal, and tactical training. The ability to replicate real-world terrains accurately and update scenarios in real-time through automated or semi-automated systems has made these solutions indispensable for armed forces worldwide. Additionally, the growing emphasis on reducing training costs and minimizing environmental impact by replacing traditional manual sand tables with robotic alternatives is fueling market expansion.

Another significant driver is the increasing utilization of robotic sand table terrain builders in educational institutions and research environments. Universities, schools, and research centers are leveraging these innovative platforms for teaching geography, geology, civil engineering, and environmental sciences. The hands-on, interactive nature of robotic sand tables enhances student engagement and facilitates a deeper understanding of complex spatial and topographical concepts. Furthermore, the integration of digital overlays, augmented reality, and data analytics capabilities with sand table systems is expanding their application scope, making them valuable tools for both STEM education and advanced academic research.

The entertainment and museum sectors are also contributing to the growth of the Robotic Sand Table Terrain Builder market. Interactive exhibits and immersive experiences powered by robotic sand tables are increasingly featured in museums, science centers, and theme parks, captivating audiences with real-time terrain modeling and interactive storytelling. The ability to dynamically alter landscapes and simulate historical or futuristic scenarios offers unique educational and entertainment value, driving adoption in these segments. This trend is supported by ongoing advancements in robotics, sensor technologies, and user interface design, which are making sand table systems more accessible, reliable, and visually compelling.

From a regional perspective, North America currently leads the global market, accounting for the largest revenue share due to substantial defense budgets, strong research infrastructure, and widespread adoption in educational and entertainment sectors. Asia Pacific is emerging as a high-growth region, driven by increasing investments in military modernization, expanding educational initiatives, and rising demand for advanced simulation technologies in China, India, and Japan. Europe also maintains a significant presence, supported by robust defense collaborations, technological innovation, and a growing focus on experiential learning. Meanwhile, Latin America and the Middle East & Africa are witnessing gradual adoption, primarily driven by targeted defense procurements and educational modernization initiatives.

Product Type Analysis

The Robotic Sand Table Terrain Builder market is segmented by product type into Automated Sand Table Builders and Semi-Automated Sand Table Builders. Automated Sand Table Builders represent the more technologically advanced segment, characterized by fully integrated robotics, real-ti

Statistical table of cases with changes in the name of the person responsible for construction in progress

Key Table Information.Table Title.Island Areas: Selected Statistics by Construction Industry and Legal Form of Organization for Puerto Rico: 2022.Table ID.ISLANDAREASIND2022.IA2200IND08.Survey/Program.Economic Census of Island Areas.Year.2022.Dataset.ECNIA Economic Census of Island Areas.Source.U.S. Census Bureau, 2022 Economic Census of Island Areas, Core Statistics.Release Date.2024-12-19.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.2022 Economic Census of Island Areas tables are released on a flow basis from June through December 2024.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe. The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in Puerto Rico, have paid employees, and are classified in one of eighteen in-scope sectors defined by the 2022 NAICS..Sponsor.U.S. Department of Commerce.Methodology.Data Items and Other Identifying Records.Number of establishmentsAnnual payroll ($1,000)Number of employeesSales, value of shipments, or revenue ($1,000)Value of construction work ($1,000)Net value of construction work ($1,000)Value added ($1,000)Cost of materials, components, packaging and/or supplies used, minerals received, or purchased machinery installed ($1,000)Cost of construction work subcontracted out to others ($1,000)Total capital expenditures for buildings, structures, machinery, and equipment (new and used) ($1,000)Total rental payments and lease payments ($1,000)Gross value of depreciable assets (acquisition costs, end of year) ($1,000)Range indicating imputed percentage of total annual payrollRange indicating imputed percentage of total employeesRange indicating imputed percentage of total sales, value of shipments, or revenueEach record includes a LFO code, which represents a specific legal form of organization category.The data are shown for legal form of organization.Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the Economic Census of Island Areas are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed..Geography Coverage.The data are shown for employer establishments and firms that vary by industry:At the Territory level for Puerto RicoFor information about economic census geographies, including changes for 2022, see Economic Census: Economic Geographies..Industry Coverage.The data are shown for Puerto Rico at the 2- through 5-digit 2022 NAICS code levels for the construction industry.For information about NAICS, see Economic Census Code Lists..Sampling.The Economic Census of Island Areas is a complete enumeration of establishments located in the islands (i.e., all establishments on the sampling frame are included in the sample). Therefore, the accuracy of tabulations is not affected by sampling error..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0044).The primary method of disclosure avoidance protection is noise infusion. Under this method, the quantitative data values such as sales or payroll for each establishment are perturbed prior to tabulation by applying a random noise multiplier (i.e., factor). Each establishment is assigned a single noise factor, which is applied to all its quantitative data value. Using this method, most published cell totals are perturbed by at most a few percentage points.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. For more information on disclosure avoidance, see Methodology for the 2022 Economic Census- Island Areas..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, see Methodology for the 2022 Economic Census- Island Areas.For more information about survey questionnaires, Primary Business Activity/NAICS codes, and NAPCS codes, see Economic Census Technical Documentation..Weights.Because the Economic Census of Island Areas is a complete enumeration, there is no sample weighting..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector00.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate qua...

The workforce dataset contains monthly workforce sizes from July 2005 to June 2018 in the eight Australian capital cities with estimated stratification by indoor and outdoor workers. It is included in both csv and rda format. It includes variables for:

Year Month GCCSA (Greater Capital City Statistical Area, which is used to define capital cities) Date (using the first day of the month) fulltime: Fulltime workers parttime: Parttime workers n. Overall workers outorin. Estimated indoor or outdoor status

This data are derived from the Australian Bureau of Statistics (ABS) Labour Force, Australia, Detailed, LM1 dataset: LM1 - Labour force status by age, greater capital city and rest of state (ASGS), marital status and sex, February 1978 onwards (pivot table). Occupational data from the 2006, 2011 and 2016 Census of Population and Housing (ABS Census TableBuilder Basic data) were used to stratify this dataset into indoor and outdoor classifications as per the "Indooroutdoor classification.xlsx" file. For the Census data, GCCSA for the place of work was used, not the place of usual residence.

Occupations were defined by the Australian and New Zealand Standard Classification of Occupations (ANZSCO). Each 6-digit ANZSCO occupation (the lowest level classification) was manually cross-matched with their corresponding occupation(s) from the Canadian National Occupation System (NOC). ANZSCO and NOC share a similar structure, because they are both derived from the International Standard Classification of Occupations. NOC occupations listed with an “L3 location” (include main duties with outdoor work for at least part of the working day) were classified as outdoors, including occupations with multiple locations. Occupations without a listing of "L3 location" were classified as indoors (no outdoor work). 6-digit ANZSCO occupations were then aggregated to 4-digit unit groups to match the ABS Census TableBuilder Basic data. These data were further aggregated into indoor and outdoor workers. The 4-digit ANZSCO unit groups’ indoor and outdoor classifications are listed in "Indooroutdoor classification.xlsx."

ANZSCO occupations associated with both indoor and outdoor listings were classified based on the more common listing, with indoors being selected in the event of a tie. The cross-matching of ANZSCO and NOC occupation was checked against two previous cross-matches used in published Australian studies utilising older ANZSCO and NOC versions. One of these cross-matches, the original cross-match, was validated with a strong correlation between ANZSCO and NOC for outdoor work (Smith, Peter M. Comparing Imputed Occupational Exposure Classifications With Self-reported Occupational Hazards Among Australian Workers. 2013).

To stratify the ABS Labour Force detailed data by indoors or outdoors, workers from the ABS Census 2006, 2011 and 2016 data were first classified as indoors or outdoors. To extend the indoor and outdoor classification proportions from 2005 to 2018, the population counts were (1) stratified by workplace GCCSA (standardised to the 2016 metrics), (2) logit-transformed and then interpolated using cubic splines and extrapolated linearly for each month, and (3) back-transformed to the normal population scale. For the 2006 Census, workplace location was reported by Statistical Local Area and then converted to GCCSA. This interpolation method was also used to estimate the 1-monthly worker count for Darwin relative to the rest of Northern Territory (ABS worker 1-monthly counts are reported only for Northern Territory collectively).

ABS data are owned by the Commonwealth Government under a CC BY 4.0 license. The attached datasets are derived and aggregated from ABS data.

These are the figures behind the figures in the Revised National Budget 2015. The first sheet of each workbook provides an overview of the figures in the respective chapter of the Revised National Budget. It has been appropriate to extract the figures in the tables that are in the budget documents in a more convenient way than to search through all the documents. Since it is an extensive job to create such extracts manually, we have instead chosen to spend some time creating a table generator — which will automatically extract the tables in the budget documents and present these in a rainsheet etc. This is one of several data sets associated with the revised state budget 2015. These are the figures behind the figures in the Revised National Budget 2015. The first sheet of each workbook provides an overview of the figures in the respective chapter of the Revised National Budget. It has been appropriate to extract the figures in the tables that are in the budget documents in a more convenient way than to search through all the documents. Since it is an extensive job to create such extracts manually, we have instead chosen to spend some time creating a table generator — which will automatically extract the tables in the budget documents and present these in a rainsheet etc. This is one of several data sets associated with the revised state budget 2015. These are the figures behind the figures in the Revised National Budget 2015. The first sheet of each workbook provides an overview of the figures in the respective chapter of the Revised National Budget. It has been appropriate to extract the figures in the tables that are in the budget documents in a more convenient way than to search through all the documents. Since it is an extensive job to create such extracts manually, we have instead chosen to spend some time creating a table generator — which will automatically extract the tables in the budget documents and present these in a rainsheet etc. This is one of several data sets associated with the revised state budget 2015. These are the figures behind the figures in the Revised National Budget 2015. The first sheet of each workbook provides an overview of the figures in the respective chapter of the Revised National Budget. It has been appropriate to extract the figures in the tables that are in the budget documents in a more convenient way than to search through all the documents. Since it is an extensive job to create such extracts manually, we have instead chosen to spend some time creating a table generator — which will automatically extract the tables in the budget documents and present these in a rainsheet etc. This is one of several data sets associated with the revised state budget 2015.

This data release contains files of the data from 2008, the data from 2016, the data from sites with measurements in both years that were used to determined water table change, and the metadata for the three files. These data were used to support the following published online map which contains the contours for 2008 and 2016 and the water-table elevation change layer: Flickinger, A.K., Mitchell, A.C., 2020, Water-table Elevation Maps for 2008 and 2016 and Water-table Elevation Changes of the Aquifer System Underlying Eastern Albuquerque, New Mexico: U.S. Geological Survey Open File Report

Total value of construction work performed by type of work and type of construction for Canada, provinces and territories form 1952 to 1993. (Terminated)

Release Date: 2020-12-17.Release Schedule:.The data in this file come from the 2017 Economic Census of Island Areas data files released on a flow basis from October 2019 through December 2020. For more information about economic census planned data product releases, see Economic Census: About: 2017 Release Schedules...Key Table Information:.Includes only establishments and firms with payroll..Data may be subject to employment- and/or sales-size minimums that vary by industry..The level of geographic detail covered varies by island. Refer to geographic area definitions for a detailed list of the geographies. Note that some tables include geography levels that only pertain to Puerto Rico..Some noise range columns are hidden..Totals may not sum due to rounding...Data Items and Other Identifying Records: .Number of establishments.Annual payroll ($1,000).Number of employees.Sales, value of shipments, or revenue ($1,000).Value of construction work ($1,000).Net value of construction work ($1,000).Value added ($1,000).Cost of construction work subcontracted out to others ($1,000).Total capital expenditures for buildings, structures, machinery, and equipment (new and used) ($1,000).Total rental payments and lease payments ($1,000).Gross value of depreciable assets (acquisition costs, end of the year) ($1,000).Range indicating percent of total annual payroll imputed.Range indicating percent of total employees imputed.Range indicating percent of total sales, value of shipments, or revenue imputed..Each record includes a LFO code, which represents a specific legal form of organization category...The data are shown for legal form of organization...Geography Coverage:.The data are shown for employer establishments and firms that vary by industry:. At the Territory level for Puerto Rico.For information about economic census geographies, including changes for 2017, see Economic Census: Economic Geographies...Industry Coverage:.The data are shown for Puerto Rico at the 2- through 5-digit NAICS code levels for the construction industry. For information about NAICS, see Economic Census: Technical Documentation: Economic Census Code Lists...Footnotes:.Not applicable...FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/economic-census/data/2017/sector00/IA1700IND08.zip..API Information:.Economic census data are housed in the Census Bureau API. For more information, see Explore Data: Developers: Available APIs: Economic Census..Methodology:.To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and/or nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only...To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. Additionally, establishment counts are suppressed when other select statistics in the same row are suppressed. For detailed information about the methods used to collect and produce statistics, including sampling, eligibility, questions, data collection and processing, data quality, review, weighting, estimation, coding operations, confidentiality protection, sampling error, nonsampling error, and more, see Economic Census: Technical Documentation: Methodology...Symbols:.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totals.N - Not available or not comparable.S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page..X - Not applicable.A - Relative standard error of 100% or more.r - Revised.s - Relative standard error exceeds 40%.For a complete list of symbols, see Economic Census: Technical Documentation: Data Dictionary.. .Source:.U.S. Census Bureau, 2017 Economic Census.For information about the economic census, see Business and Economy: Economic Census...Contact Information:.U.S. Census Bureau.For general inquiries:. (800) 242-2184/ (301) 763-5154. ewd.outreach@census.gov.For specific data questions:. (800) 541-8345.For additional contacts, see Economic Census: About: Contact Us.

Regional profile tables containing gross regional product and output, employment, household income and expenditure, and trade. The tables are estimates derived as part of the input-output table construction process for South Australia and its regions. They are not taken directly from a census or survey, but are based on a mix of collected data, state shares (if a regional table) and estimates based on “parent” table values. Regional profile tables containing gross regional product and output, employment, household income and expenditure, and trade. The tables are estimates derived as part of the input-output table construction process for South Australia and its regions. They are not taken directly from a census or survey, but are based on a mix of collected data, state shares (if a regional table) and estimates based on “parent” table values.