{ "dataflow": "OECD.STI.DEP.DSD_TOOLKIT_14@DF_GD_BREAKDOWNS_14", "dataset_title": "Going Digital Toolkit - Data for the breakdown visualisations - part 14", "dataset_description": "In the context \"world excluding domestic\"", "fields": { "MEASURE": { "type": "dimension", "concept": "MEASURE", "label": "Indicator", "description": "", "codelist": "CL_MEASURE_TOOLKIT" }, "REF_AREA": { "type": "dimension", "concept": "REF_AREA", "label": "Country", "description": "", "codelist": "CL_AREA" }, "SCOPE": { "type": "dimension", "concept": "SCOPE", "label": "Scope", "description": "", "codelist": "CL_BREAKDOWN_TOOLKIT" }, "UNIT_MEASURE": { "type": "dimension", "concept": "UNIT_MEASURE", "label": "Unit of measure", "description": "", "codelist": "CL_UNIT_MEASURE_TOOLKIT" }, "TIME_PERIOD": { "type": "time", "label": "Time period", "description": "Observation time period" }, "OBS_STATUS": { "type": "attribute", "concept": "OBS_STATUS", "label": "Observation status", "description": "", "codelist": "CL_OBS_STATUS_TOOLKIT" }, "OBS_VALUE": { "type": "measure", "concept": "OBS_VALUE", "label": "Value", "description": "" } }, "codelists": { "CL_MEASURE_TOOLKIT": { "IND00": "Share of information industries in total employment", "IND01": "Labour productivity of information industries relative to other non-agriculture business sector activities", "IND02": "Intermediate consumption of information industry products", "IND03": "Final demand for information industry products as a share of total final demand", "IND04": "Extended information industries domestic value added footprint", "IND05": "Jobs in information industries sustained by foreign final demand", "IND06": "Students aged 15-16 years who feel bad if no Internet connection is available", "IND07": "Workers experiencing job stress associated with frequent computer use at work", "IND08": "Digital-intensive sectors' contribution to value added growth", "IND10": "Fixed broadband subscriptions per 100 inhabitants", "IND11": "Mobile broadband subscriptions per 100 inhabitants", "IND12": "M2M (machine-to-machine) SIM cards per 100 inhabitants", "IND13": "Share of households with broadband connections", "IND14": "Share of businesses with broadband contracted speed of 30 Mbps or more", "IND15": "Average monthly mobile data usage per mobile broadband subscription", "IND16": "Mobile network by technology", "IND17": "Disparity in broadband uptake between urban and rural households", "IND20": "Internet users as a share of individuals", "IND21": "Share of businesses making e‑commerce sales", "IND22": "Share of Internet users who have purchased online", "IND23": "Share of individuals using the Internet to interact with public authorities", "IND24": "Adults' proficiency in key skills for the digital age", "IND25": "Share of businesses purchasing cloud services", "IND26": "Share of businesses with a web presence", "IND30": "ICT investment", "IND31": "Business R&D expenditure", "IND32": "Top 10% most-cited documents", "IND33": "Patents in ICT technologies", "IND34": "Share of start-up firms (up to 2 years old) in the business population", "IND35": "Venture capital investments", "IND40": "ICT task-intensive jobs", "IND41": "Digital-intensive sectors' share in total employment", "IND42": "Public spending on active labour market policies", "IND43": "New tertiary graduates", "IND44": "Workers receiving job-related training", "IND50": "Share of individuals aged 55-74 years using the Internet", "IND51": "Share of individuals who live in households with income in the lowest quintile who use the Internet", "IND52": "15 year old students' performance in science mathematics and reading", "IND53": "E-waste", "IND54": "Individuals who can program", "IND55": "Share of individuals who use digital equipment at work that telework from home", "IND56": "Air pollution from digital-intensive sectors", "IND57": "Disparity in Internet use between men and women", "IND58": "OECD Digital Government Index", "IND59": "Share of students aged 11, 13 and 15 years who are problematic social media users", "IND60": "Share of businesses in which employees carry out ICT security related activities", "IND61": "Share of Internet users experiencing abuse of personal information or privacy violations", "IND62": "Share of Internet users not buying online due to payment security concerns", "IND63": "Share of Internet users not buying online due to concerns about returning products", "IND64": "Health data sharing intensity", "IND70": "Digital-intensive services value added embodied in manufacturing exports as a share of manufacturing export value", "IND71": "Trade in digitally-deliverable services", "IND72": "Share of businesses making e-commerce sales that sell across borders", "IND73": "OECD Digital Services Trade Restrictiveness Index", "IND74": "OECD Foreign Direct Investment Regulatory Restrictiveness Index", "IND75": "ICT goods and services", "ID0": "Share of information industries in total employment", "ID1": "Labour productivity of information industries relative to other non-agriculture business sector activities", "ID2": "Intermediate consumption of information industry products as a share of total intermediate consumption", "ID3": "Final demand for information industry products as a share of total final demand", "ID4": "Extended information industries domestic value added footprint as a share of domestic value added of the country", "ID5": "Share of jobs in information industries that are sustained by foreign final demand", "ID6": "Students aged 15-16 years who feel bad if no Internet connection is available", "ID7": "Workers experiencing job stress associated with frequent computer use at work", "ID8": "Digital-intensive sectors' contribution to value added growth", "ID10": "Fixed broadband subscriptions per 100 inhabitants", "ID11": "Mobile broadband subscriptions per 100 inhabitants", "ID12": "M2M (machine-to-machine) SIM cards per 100 inhabitants", "ID13": "Share of households with broadband connections", "ID14": "Share of businesses with broadband contracted speed of 30 Mbps or more", "ID15": "Average monthly mobile data usage per mobile broadband subscription", "ID16": "Share of the population covered by at least a 4G mobile network", "ID17": "Disparity in broadband uptake between urban and rural households", "ID20": "Internet users as a share of individuals", "ID21": "Share of small businesses making e‑commerce sales", "ID22": "Share of Internet users who have purchased online", "ID23": "Share of individuals using the Internet to interact with public authorities", "ID24": "Share of adults proficient at problem solving in technology-rich environments", "ID25": "Share of businesses purchasing cloud services", "ID26": "Share of businesses with a web presence", "ID30": "ICT investment as a share of GDP", "ID31": "Business R&D expenditure in information industries as a share of GDP", "ID32": "Top 10% most-cited documents in computer science, as a share of the top 10% ranked documents in all fields", "ID33": "Patents in ICT technologies, as a share of total IP5 patent families", "ID34": "Start-up firms (up to 2 years old) in information industries as a share of all businesses", "ID35": "Venture capital investment in the ICT sector as a share of GDP", "ID40": "Share of ICT task-intensive jobs", "ID41": "Digital-intensive sectors' share in total employment", "ID42": "Public spending on active labour market policies as a share of GDP", "ID43": "New tertiary graduates in science, technology, engineering and mathematics as a share of new graduates", "ID44": "Workers receiving job-related training as a share of total employment", "ID50": "Share of individuals aged 55-74 years using the Internet", "ID51": "Share of individuals who live in households with income in the lowest quintile who use the Internet", "ID52": "Top-performing 15-16 year old students in science, mathematics and reading", "ID53": "E-waste generated per capita", "ID54": "Women as a share of all 16-24 year-olds who can program", "ID55": "Share of individuals who use digital equipment at work that telework from home once a week or more", "ID56": "Air pollution from digital-intensive sectors, kg per million USD of value added", "ID57": "Disparity in Internet use between men and women", "ID58": "OECD Digital Government Index", "ID59": "Share of students aged 11, 13 and 15 years who are problematic social media users", "ID60": "Share of enterprises in which own employees carry out ICT security related activities", "ID61": "Share of Internet users experiencing abuse of personal information or privacy violations", "ID62": "Share of Internet users not buying online due to payment security concerns", "ID63": "Share of Internet users not buying online due to concerns about returning products", "ID64": "Health data sharing intensity", "ID70": "Digital-intensive services value added embodied in manufacturing exports as a share of manufacturing export value", "ID71": "Digitally-deliverable services as a share of commercial services trade", "ID72": "Share of businesses making e-commerce sales that sell across borders", "ID73": "OECD Digital Services Trade Restrictiveness Index", "ID74": "OECD Foreign Direct Investment Regulatory Restrictiveness Index", "ID75": "ICT goods and services as a share of international trade", "NONE": "None", "HBSC_B1": "Share of students who report being victims of cyberbullying at least once in the past couple of months", "HBSC_B2": "Share of students who report having cyberbullied others at least once in the past couple of months", "HBSC_C1": "Share of students who report being victims of bullying at least once in the past couple of months", "HBSC_C2": "Share of students who report having bullied others at least once in the past couple of months", "IND80": "Ability of adults to identify the veracity of online news", "ID80": "Ability of adults to identify the veracity of online news", "IND81": "Ability of adults to identify the veracity of online news created by generative AI", "ID81": "Ability of adults to identify online disinformation created by generative AI", "IND82": "Perception of the impact of AI on life", "ID82": "Share of adults who feel AI will have a positive impact on their life", "IND83": "Trust in news", "ID83": "Share of adults who trust news from social media sites or apps", "IND84": "Share of adults who avoid using certain websites, apps, or social media due to privacy concerns", "ID84": "Share of adults who avoid using certain websites, apps, or social media due to privacy concerns", "IND36": "Founders of VC-funded start-ups", "ID36": "Share of VC-funded start-ups in digital-related activities with female founders", "IND65": "Patents in cybersecurity", "ID65": "Patents in cybersecurity, as a share of total IP5 patent families", "ID66": "Top 10% most-cited documents in cybersecurity, as a share of the top 10% ranked documents in all fields", "IND66": "Top 10% most-cited documents", "IND85": "Online activities among 15-year-olds", "ID85": "Share of 15-year-olds who are intensive social media users", "IND09": "Placeholder for indicator 9", "IND18": "Placeholder for indicator 18", "IND19": "Placeholder for indicator 19", "IND27": "Placeholder for indicator 27", "IND28": "Placeholder for indicator 28", "IND29": "Placeholder for indicator 29", "IND37": "Placeholder for indicator 37", "IND38": "Placeholder for indicator 38", "IND39": "Placeholder for indicator 39", "IND45": "Placeholder for indicator 45", "IND46": "Placeholder for indicator 46", "IND47": "Placeholder for indicator 47", "IND48": "Placeholder for indicator 48", "IND49": "Placeholder for indicator 49", "IND67": "Placeholder for indicator 67", "IND68": "Placeholder for indicator 68", "IND69": "Placeholder for indicator 69", "IND76": "Placeholder for indicator 76", "IND77": "Placeholder for indicator 77", "IND78": "Placeholder for indicator 78", "IND79": "Placeholder for indicator 79", "IND86": "Placeholder for indicator 86", "IND87": "Placeholder for indicator 87", "IND88": "Placeholder for indicator 88", "IND89": "Placeholder for indicator 89", "IND90": "Placeholder for indicator 90", "IND91": "Placeholder for indicator 91", "IND92": "Placeholder for indicator 92", "IND93": "Placeholder for indicator 93", "IND94": "Placeholder for indicator 94", "IND95": "Placeholder for indicator 95", "IND96": "Placeholder for indicator 96", "IND97": "Placeholder for indicator 97", "IND98": "Placeholder for indicator 98", "IND99": "Placeholder for indicator 99", "ID9": "Placeholder for indicator 9", "ID18": "Placeholder for indicator 18", "ID19": "Placeholder for indicator 19", "ID27": "Placeholder for indicator 27", "ID28": "Placeholder for indicator 28", "ID29": "Placeholder for indicator 29", "ID37": "Placeholder for indicator 37", "ID38": "Placeholder for indicator 38", "ID39": "Placeholder for indicator 39", "ID45": "Placeholder for indicator 45", "ID46": "Placeholder for indicator 46", "ID47": "Placeholder for indicator 47", "ID48": "Placeholder for indicator 48", "ID49": "Placeholder for indicator 49", "ID67": "Placeholder for indicator 67", "ID68": "Placeholder for indicator 68", "ID69": "Placeholder for indicator 69", "ID76": "Placeholder for indicator 76", "ID77": "Placeholder for indicator 77", "ID78": "Placeholder for indicator 78", "ID79": "Placeholder for indicator 79", "ID86": "Placeholder for indicator 86", "ID87": "Placeholder for indicator 87", "ID88": "Placeholder for indicator 88", "ID89": "Placeholder for indicator 89", "ID90": "Placeholder for indicator 90", "ID91": "Placeholder for indicator 91", "ID92": "Placeholder for indicator 92", "ID93": "Placeholder for indicator 93", "ID94": "Placeholder for indicator 94", "ID95": "Placeholder for indicator 95", "ID96": "Placeholder for indicator 96", "ID97": "Placeholder for indicator 97", "ID98": "Placeholder for indicator 98", "ID99": "Placeholder for indicator 99" }, "CL_BREAKDOWN_TOOLKIT": { "YS2_P_EMPL": "Share of 2-year-old employer enterprises in the business population", "YS1_P_EMPL": "Share of 1-year-old employer enterprises in the business population", "B_R_EMPL": "Birth rate of employer enterprises", "START_R_EBD": "Share of employer start-ups (0-2 year old enterprises) among active employer enterprises", "PM10": "Small particulates (less than 10µm)", "PM2_5": "Fine particulates (less than 2.5µm)", "GHG": "Greenhouse gases", "CO2": "Carbon dioxide", "DXD": "Domestic demand", "FFD": "Foreign final demand", "SPECIALIST": "ICT Specialists", "OTHER_ICT_INTENSIVE": "ICT Users", "ICT_INTENSIVE": "All ICT-intensive (Specialists + Users)", "SF": "Insurance and pension services", "SG": "Financial services", "SH": "Charges for the use of intellectual property n.i.e.", "SI": "Telecommunications, computer, and information services", "SK1": "Audiovisual and related services", "SOX": "Commercial Services", "TOT": "Total digitally deliverable services", "ICT00": "Total ICT goods", "ICT01": "Computers and peripheral equipment", "ICT02": "Communication equipment", "ICT03": "Consumer electronic equipment", "ICT04": "Electronic components", "ICT05": "Miscellaneous", "T": "Total ICT goods and services", "S": "Total ICT services", "PISA_M": "Mathematics only", "PISA_MAS": "Mathematics and science only", "PISA_R": "Reading only", "PISA_RAM": "Reading and mathematics only", "PISA_RAS": "Reading and science only", "PISA_S": "Science only", "PISA_SARAM": "Science, mathematics and reading (all 3 disciplines)", "PISA_T": "Science, mathematics and reading", "PISA_M_ALL": "Mathematics", "PISA_R_ALL": "Reading", "PISA_S_ALL": "Science", "PISA_MAS_ALL": "Mathematics and science", "PISA_RAM_ALL": "Reading and mathematics", "PISA_RAS_ALL": "Reading and science", "0": "Total ICT", "1": "High speed network", "2": "Mobile communication", "3": "Security", "4": "Sensor and device network", "5": "High speed computing", "6": "Large-capacity and high speed storage", "7": "Large-capacity information analysis", "8": "Cognition and meaning understanding", "9": "Human-interface", "10": "Imaging and sound technology", "11": "Information communication device", "12": "Electronic measurement", "13": "Others", "LITERACY": "Literacy", "NUMERACY": "Numeracy", "PSTRE": "Problem solving in technology-rich environments", "L_2": "Level 2", "L_3": "Level 3", "L_4_5": "Level 4 or 5", "_T": "Total", "F021": "Arts", "F032": "Journalism and information", "F05": "Natural sciences, mathematics and statistics", "F06": "Information and Communication Technologies (ICTs)", "F07": "Engineering, manufacturing and construction", "F05T07": "Science, technology, engineering and mathematics", "ISCED11_5": "Short-cycle tertiary education", "ISCED11_6": "Bachelor’s or equivalent level", "ISCED11_7": "Master’s or equivalent level", "ISCED11_8": "Doctoral or equivalent level", "I": "Equity restriction", "II": "Screening & approval", "III": "Key foreign personnel", "IV": "Other restrictions", "V": "All types of restrictions", "EU_EXCLUS": "Businesses undertaking cross-border e-commerce sales to EU countries exclusively", "EU_AND_ROW": "Businesses undertaking cross-border e-commerce sales to both EU and the rest of the world", "ROW_EXCLUS": "Businesses undertaking cross-border e-commerce sales to the rest of the world exclusively", "TOT_XBORDER": "Businesses undertaking cross-border e-commerce sales", "ENT_I": "Accommodation and food and beverage service activities", "ENT_N": "Administrative and support service activities", "ENT_T_S_GE10": "All businesses (excludes financial sector, 10 persons employed or more)", "ENT_F": "Construction", "ENT_J": "Information and communication", "ENT_S_GE250": "Large businesses (250 persons employed or more)", "ENT_C": "Manufacturing", "ENT_S50T249": "Medium businesses (50-249 persons employed)", "ENT_M": "Professional, scientific and technical activities", "ENT_L": "Real estate activities", "ENT_G47": "Retail trade, except of motor vehicles and motorcycles", "ENT_S10T49": "Small businesses (10-49 persons employed)", "ENT_H": "Transportation and storage", "ENT_G46": "Wholesale trade, except of motor vehicles and motorcycles", "OWN_OR_EXT": "Own or external employees", "EXT_EMP": "External employees", "OWN_EMP": "Own employees", "EXT_ONLY": "External employees only", "OWN_ONLY": "Own employees only", "OWN_AND_EXT": "Own and external employees", "IT_MOB_2GNTWK": "Proportion of population covered by at least 2G", "IT_MOB_3GNTWK": "Proportion of population covered by at least 3G", "IT_MOB_4GNTWK": "Proportion of population covered by at least 4G", "ENT_K": "Financial and insurance activities", "ENT_S0T9": "Micro (0 to 9 employees)", "MBB_VD": "Data and Voice subscriptions", "MBB_DO": "Data only subscriptions", "MBB_ALL": "All subscriptions", "FBB_ALL": "All subscriptions", "FBB_DSL": "DSL subscriptions", "FBB_CAB": "Cable subscriptions", "FBB_OTH": "Other subscriptions", "FBB_FIB": "Fibre/LAN subscriptions", "FBB_SAT": "Satellite subscriptions", "FBB_FWA": "Terrestrial Fixed Wireless subscriptions", "HFCE": "Household final consumption expenditure", "GFCF": "Gross fixed capital formation", "ICT_TTL": "Total ICT investment", "ICT_EQP": "ICT equipment", "ICT_CMP": "Computer hardware", "ICT_TLC": "Telecommunications equipment", "ICT_SFW": "Computer software and databases", "IPP_TTL": "Intellectual property products", "IPP_RD": "Research and Development", "ICT_TTL_GFCF": "Total ICT investment as a share of GFCF", "EWASTE_GENERA": "E-waste generated; kg per capita", "EWASTE_RECYCL": "E-waste collected and recycled; kg per capita", "EWASTE_USGDP": "E-waste generated; kg per 100k USD of GDP", "F_YOUNG": "Female", "M_YOUNG": "Male", "F": "Women", "M": "Men", "Y15T29": "15-29 years old", "Y30T49": "30-49 years old", "Y50T64": "50-64 years old", "Y_GE15": "All individuals (aged 15+)", "PC_SHARING": "% of sharing potential", "GOV_BODIES": "National health datasets allowing sharing with government bodies", "UNI_NOPROFIT": "National health datasets allowing sharing with universities and/or non-profit research centres", "HEALTHC_PROV": "National health datasets allowing sharing with health care providers", "BUS": "National health datasets allowing sharing with businesses", "FOREIGN_UNI_NOPROFIT": "National health datasets allowing sharing with foreign governments, universities, or non-profit research centres", "PC_ALLOWING_SHARING": "% allowing some sharing", "SCORE": "Composite score", "DIG_DESIGN": "Digital by design", "DATA_DRIVEN": "Data-driven public sector", "GOV_PLATFORM": "Government as a platform", "OPEN_DEFAULT": "Open by default", "USER_DRIVEN": "User-driven", "PROACTIVENESS": "Proactiveness", "F1B": "Individuals using the Internet for downloading official forms", "F1": "Individuals using the Internet for visiting or interacting with public authorities websites", "F1A": "Individuals using the Internet for obtaining information from public authorities", "F1C": "Individuals using the Internet for sending filled forms via public authorities websites", "INTNET_MALE_FEMALE": "Disparity in Internet use between men and women", "C5B": "Individuals using the Internet", "C5B1": "Individuals using the Internet daily or almost every day", "C6E": "Individuals using the Internet in mobility", "INTNET_URBAN_RURAL": "Disparity in broadband uptake between urban and rural households", "B21": "Households with broadband Internet access at home", "GAP_IND": "Difference (male-female)", "GAP_HH": "Difference (urban-rural)", "F_LO": "Female aged 16-74 with no or a low level of educational attainment", "F_ME": "Female aged 16-74 with a middle level of educational attainment", "F_Y16T24": "Female aged 16-24", "F_Y16T74": "Female aged 16-74", "F_Y25T54": "Female aged 25-54", "F_Y55T74": "Female aged 55-74", "I_LO": "Individuals aged 16-74 with no or a low level of educational attainment", "I_ME": "Individuals aged 16-74 with a middle level of educational attainment", "M_LO": "Male aged 16-74 with no or a low level of educational attainment", "M_ME": "Male aged 16-74 with a middle level of educational attainment", "M_Y16T24": "Male aged 16-24", "M_Y16T74": "Male aged 16-74", "M_Y25T54": "Male aged 25-54", "M_Y55T74": "Male aged 55-74", "Y16T24": "Individuals aged 16-24", "Y16T24LO": "Individuals aged 16-24 with no or a low level of educational attainment", "Y16T24ME": "Individuals aged 16-24 with a middle level of educational attainment", "Y25T54": "Individuals aged 25-54", "Y25T54LO": "Individuals aged 25-54 with no or a low level of educational attainment", "Y25T54ME": "Individuals aged 25-54 with a middle level of educational attainment", "Y55T74": "Individuals aged 55-74", "Y55T74ME": "Individuals aged 55-74 with a middle level of educational attainment", "Y_GE75": "Individuals aged 75 and over", "F_HI": "Female aged 16-74 with a high level of educational attainment", "I_HI": "Individuals aged 16-74 with a high level of educational attainment", "M_HI": "Male aged 16-74 with a high level of educational attainment", "Y25T54HI": "Individuals aged 25-54 with a high level of educational attainment", "Y55T74HI": "Individuals aged 55-74 with a high level of educational attainment", "Y16T24HI": "Individuals aged 16-24 with a high level of educational attainment", "IND_TOTAL": "All (individuals aged 16-74)", "RETIR_OTHER": "Retired and other inactive aged 16-74", "SAL_SELF_FAM": "Employees, Self-employed and family workers aged 16-74", "ST": "Students aged 16-74", "UNE": "Unemployed aged 16-74", "Y55T74LO": "Individuals aged 55-74 with no or a low level of educational attainment", "IND_QNT1": "Individuals living in a household with income in first quintile", "IND_QNT2": "Individuals living in a household with income in second quintile", "IND_QNT3": "Individuals living in a household with income in third quintile", "IND_QNT4": "Individuals living in a household with income in fourth quintile", "IND_QNT5": "Individuals living in a household with income in fifth quintile", "IND_Q1": "Individual living in a household with income in first quartile", "IND_Q2": "Individual living in a household with income in second quartile", "IND_Q3": "Individual living in a household with income in third quartile", "IND_Q4": "Individual living in a household with income in fourth quartile", "HH_TOTAL": "All (households)", "HH_DEG_PRURAL": "Households living in rural areas", "HH_DEG_PURBAN": "Households living in large urban areas", "HH_DEG_INT": "Households living in small urban areas", "HH_QNT1": "Households with income in first quintile", "HH_QNT2": "Households with income in second quintile", "HH_QNT3": "Households with income in third quintile", "HH_QNT4": "Households with income in fourth quintile", "HH_QNT5": "Households with income in fifth quintile", "G3_B": "Businesses purchasing cloud computing services (%)", "G3A_B": "Businesses purchasing cloud computing services: E-mail (%)", "G3F_B": "Businesses purchasing cloud computing services: Storage of files (%)", "G3G_B": "Businesses purchasing cloud computing services: Computing power to run own software (%)", "G3B_B": "Businesses purchasing cloud computing services: Office software (%)", "G3C_B": "Businesses purchasing cloud computing services: Finance or accounting software (%)", "G3D_B": "Businesses purchasing cloud computing services: Customer Relationship Management (CRM) software (%)", "G3E_B": "Businesses purchasing cloud computing services: Hosting of databases (%)", "B1_B": "Businesses with a website or home page (%)", "D1B_B": "Businesses receiving orders through the Internet (%)", "A3D_B": "Businesses with a broadband download speed at least 30 Mbit/s but less than 100 Mbit/s (%)", "A3E_B": "Businesses with a broadband download speed at least 100 Mbit/s (%)", "A3G_B": "Businesses with a broadband download speed at least 500 Mbit/s but less than 1 Gbit/s (%)", "A3F_B": "Businesses with a broadband download speed at least 100 Mbit/s but less than 500 Mbit/s (%)", "A3H_B": "Businesses with a broadband download speed at least 1 Gbit/s (%)", "A3D_E_B": "Businesses with a broadband download speed at least 30 Mbit/s (%)", "ASJC_10": "Multidisciplinary", "ASJC_11": "Agricultural & Biological Sciences", "ASJC_12": "Arts & Humanities", "ASJC_13": "Biochemistry, Genetics & Molecular Biology", "ASJC_14": "Business, Management & Accounting", "ASJC_15": "Chemical Engineering", "ASJC_16": "Chemistry", "ASJC_17": "Computer Science", "ASJC_18": "Decision Sciences", "ASJC_19": "Earth & Planetary Sciences", "ASJC_20": "Economics, Econometrics & Finance", "ASJC_21": "Energy", "ASJC_22": "Engineering", "ASJC_23": "Environmental Science", "ASJC_24": "Immunology & Microbiology", "ASJC_25": "Materials Science", "ASJC_26": "Mathematics", "ASJC_27": "Medicine", "ASJC_28": "Neuroscience", "ASJC_29": "Nursing", "ASJC_30": "Pharmacology, Toxicology & Pharmaceutics", "ASJC_31": "Physics & Astronomy", "ASJC_32": "Psychology", "ASJC_33": "Social Sciences", "ASJC_34": "Veterinary", "ASJC_35": "Dentistry", "ASJC_36": "Health Professions", "FORMAL": "Workers receiving formal only training", "ON_THE_JOB": "Workers receiving non-formal only training", "FORMAL_ON_THE_JOB": "Workers receiving formal and non-formal training", "TOTAL": "Total trained workforce", "HIGH_SK": "Highly skilled workers receiving job-related training", "MED_SK": "Medium skilled workers receiving job-related training", "LOW_SK": "Low skilled workers receiving job-related training", "ED": "Every day or almost every day", "OW": "At least once a week but not every day", "LOW": "Less than once a week", "LMPEXP_20": "Training", "LMPEXP_40": "Employment incentives", "LMPEXP_60": "Direct job creation", "LMPEXP_70": "Start-up incentives", "LMPEXP_11": "Placement and related services", "STRI": "Indicator DSTRI", "CLAS1_1": "Infrastructure and connectivity", "CLAS1_2": "Electronic transactions", "CLAS1_3": "Payment system", "CLAS1_4": "Intellectual property rights", "CLAS1_5": "Other barriers affecting trade in digitally enabled services", "VC_ICT": "Venture capital investment in the ICT sector", "SEED": "Seed", "START": "Start-up and other early stage", "LATER": "Later stage venture", "EXPO": "Exports", "IMPO": "Imports", "M_INV_ONLY": "ICT inventions by men (only)", "F_INV_ONLY": "ICT inventions by women (only)", "M_F_INV": "ICT inventions by men and women", "Y11": "11 years old", "Y13": "13 years old", "Y15": "15 years old", "Y11_13_15": "11, 13 and 15 years old", "TQ_T": "Overall Truth Quest score", "TQ_CD": "Contextual deception", "TQ_DISINFO": "Disinformation", "TQ_MISINFO": "Misinformation", "TQ_PROP": "Propaganda", "TQ_SATIRE": "Satire", "TQ_TRUTH": "Truth", "TQ_ENV": "Environment", "TQ_HEALTH": "Health", "TQ_IA": "International Affairs", "AI_POSITIVE": "Perception of AI: Positive", "AI_NEGATIVE": "Perception of AI: Negative", "AI_NEUTRAL": "Perception of AI: Neither positive nor negative", "TQ_SCORE_AI_POSITIVE": "Truth Quest score (100 = best performance) for AI-labelled news for those with a positive perception of AI", "TQ_SCORE_AI_NEGATIVE": "Truth Quest score (100 = best performance) for AI-labelled news for those with a negative perception of AI", "TQ_SCORE_POSITIVE": "Overall Truth Quest score (100 = best performance) for those with a positive perception of AI", "TQ_SCORE_NEGATIVE": "Overall Truth Quest score (100 = best performance) for those with a negative perception of AI", "AI_GEN": "AI-generated news", "HUM_GEN": "Human-generated news", "Y_GE18": "All individuals aged 18 or older", "Y18T34": "Individuals aged 18-34", "Y35T54": "Individuals aged 35-54", "Y_GE55": "Individuals aged 55 or older", "I_ISCED11_0T2": "Individuals with primary, low secondary or no education", "I_ISCED11_3T4": "Individuals with upper secondary or post-secondary education", "I_ISCED11_5T8": "Individuals with tertiary education", "I_INC_TOP20": "Individuals living in high-income households (top 20%)", "I_INC_MID60": "Individuals living in middle-income households (mid  60%)", "I_INC_BOT20": "Individuals living in low-income households (bottom 20%)", "TQ_PUBLIC_TV": "Public TV", "TQ_PRIVATE_TV": "Private TV", "TQ_PUBLIC_RADIO": "Public radio", "TQ_PRIVATE_RADIO": "Private radio", "TQ_PRINT": "Print publications", "TQ_WEB": "News websites or apps", "TQ_SOCIAL_MEDIA": "Social media", "STARTUPS_F": "All female", "STARTUPS_M": "All male", "STARTUPS_FM": "Female and male", "STARTUPS_DIGITAL": "Digital-related activities", "STARTUPS_T": "Total economy", "ICT_T": "ICT (all stages)", "EWASTE_DIFF": "Unmanaged e-waste; kg per capita", "INV_TOT": "Inventions", "RTA": "Revealed technological advantage", "BROWSE_SOCIAL_MEDIA": "Social media browsing", "PLAY_VIDEO_GAMES": "Video games", "BROWSE_INTERNET": "Internet browsing", "COMMUNICATE_SOCIAL_MEDIA": "Social media communication", "TUTORIALS": "Tutorials and podcasts", "SEARCH_INFO": "Practical information search", "EDIT_CONTENT": "Content creation", "CT_LOW_ALL": "Creative Thinking score for students with low or no use", "CT_MODERATE_ALL": "Creative Thinking score for students with moderate use", "CT_INTENSE_ALL": "Creative Thinking score for students with intense use", "CT_LOW_GIRLS": "Creative Thinking score for girls with low or no use", "CT_MODERATE_GIRLS": "Creative Thinking score for girls with moderate use", "CT_INTENSE_GIRLS": "Creative Thinking score for girls with intense use", "CT_LOW_BOYS": "Creative Thinking score for boys with low or no use", "CT_MODERATE_BOYS": "Creative Thinking score for boys with moderate use", "CT_INTENSE_BOYS": "Creative Thinking score for boys with intense use", "CT_LOW_BOTTOM25": "Creative Thinking score for students in the lowest socio-economic quartile with low or no use", "CT_MODERATE_BOTTOM25": "Creative Thinking score for students in the lowest socio-economic quartile with moderate use", "CT_INTENSE_BOTTOM25": "Creative Thinking score for students in the lowest socio-economic quartile with intense use", "CT_LOW_TOP25": "Creative Thinking score for students in the highest socio-economic quartile with low or no use", "CT_MODERATE_TOP25": "Creative Thinking score for students in the highest socio-economic quartile with moderate use", "CT_INTENSE_TOP25": "Creative Thinking score for students in the highest socio-economic quartile with intense use", "MATHS_LOW_ALL": "Mathematics score for students with low or no use", "MATHS_MODERATE_ALL": "Mathematics score for students with moderate use", "MATHS_INTENSE_ALL": "Mathematics score for students with intense use", "MATHS_LOW_GIRLS": "Mathematics score for girls with low or no use", "MATHS_MODERATE_GIRLS": "Mathematics score for girls with moderate use", "MATHS_INTENSE_GIRLS": "Mathematics score for girls with intense use", "MATHS_LOW_BOYS": "Mathematics score for boys with low or no use", "MATHS_MODERATE_BOYS": "Mathematics score for boys with moderate use", "MATHS_INTENSE_BOYS": "Mathematics score for boys with intense use", "MATHS_LOW_BOTTOM25": "Mathematics score for students in the lowest socio-economic quartile with low or no use", "MATHS_MODERATE_BOTTOM25": "Mathematics score for students in the lowest socio-economic quartile with moderate use", "MATHS_INTENSE_BOTTOM25": "Mathematics score for students in the lowest socio-economic quartile with intense use", "MATHS_LOW_TOP25": "Mathematics score for students in the highest socio-economic quartile with low or no use", "MATHS_MODERATE_TOP25": "Mathematics score for students in the highest socio-economic quartile with moderate use", "MATHS_INTENSE_TOP25": "Mathematics score for students in the highest socio-economic quartile with intense use", "READING_LOW_ALL": "Reading score for students with low or no use", "READING_MODERATE_ALL": "Reading score for students with moderate use", "READING_INTENSE_ALL": "Reading score for students with intense use", "READING_LOW_GIRLS": "Reading score for girls with low or no use", "READING_MODERATE_GIRLS": "Reading score for girls with moderate use", "READING_INTENSE_GIRLS": "Reading score for girls with intense use", "READING_LOW_BOYS": "Reading score for boys with low or no use", "READING_MODERATE_BOYS": "Reading score for boys with moderate use", "READING_INTENSE_BOYS": "Reading score for boys with intense use", "READING_LOW_BOTTOM25": "Reading score for students in the lowest socio-economic quartile with low or no use", "READING_MODERATE_BOTTOM25": "Reading score for students in the lowest socio-economic quartile with moderate use", "READING_INTENSE_BOTTOM25": "Reading score for students in the lowest socio-economic quartiles with intense use", "READING_LOW_TOP25": "Reading score for students in the highest socio-economic quartile with low or no use", "READING_MODERATE_TOP25": "Reading score for students in the highest socio-economic quartile with moderate use", "READING_INTENSE_TOP25": "Reading score for students in the highest socio-economic quartile with intense use", "SCIENCE_LOW_ALL": "Science score for students with low or no use", "SCIENCE_MODERATE_ALL": "Science score for students with moderate use", "SCIENCE_INTENSE_ALL": "Science score for students with intense use", "SCIENCE_LOW_GIRLS": "Science score for girls with low or no use", "SCIENCE_MODERATE_GIRLS": "Science score for girls with moderate use", "SCIENCE_INTENSE_GIRLS": "Science score for girls with intense use", "SCIENCE_LOW_BOYS": "Science score for boys with low or no use", "SCIENCE_MODERATE_BOYS": "Science score for boys with moderate use", "SCIENCE_INTENSE_BOYS": "Science score for boys with intense use", "SCIENCE_LOW_BOTTOM25": "Science score for students in the lowest socio-economic quartile with low or no use", "SCIENCE_MODERATE_BOTTOM25": "Science score for students in the lowest socio-economic quartile with moderate use", "SCIENCE_INTENSE_BOTTOM25": "Science score for students in the lowest socio-economic quartile with intense use", "SCIENCE_LOW_TOP25": "Science score for students in the highest socio-economic quartile with low or no use", "SCIENCE_MODERATE_TOP25": "Science score for students in the highest socio-economic quartile with moderate use", "SCIENCE_INTENSE_TOP25": "Science score for students in the highest socio-economic quartile with intense use", "APS": "Adaptive problem solving", "L_4": "Level 4", "L_5": "Level 5", "CT_LOW_MID": "CT_LOW_MID", "CT_MODERATE_MID": "CT_MODERATE_MID", "CT_INTENSE_MID": "CT_INTENSE_MID", "MATHS_LOW_MID": "MATHS_LOW_MID", "MATHS_MODERATE_MID": "MATHS_MODERATE_MID", "MATHS_INTENSE_MID": "MATHS_INTENSE_MID", "READING_LOW_MID": "READING_LOW_MID", "READING_MODERATE_MID": "READING_MODERATE_MID", "READING_INTENSE_MID": "READING_INTENSE_MID", "SCIENCE_LOW_MID": "SCIENCE_LOW_MID", "SCIENCE_MODERATE_MID": "SCIENCE_MODERATE_MID", "SCIENCE_INTENSE_MID": "SCIENCE_INTENSE_MID", "LOW_ALL": "All 15-year-old students with low or no use", "MODERATE_ALL": "All 15-year-old students with moderate use", "INTENSE_ALL": "All 15-year-old students with intense use", "LOW_GIRLS": "Girls with low or no use", "MODERATE_GIRLS": "Girls with moderate use", "INTENSE_GIRLS": "Girls with intense use", "LOW_BOYS": "Boys with low or no use", "MODERATE_BOYS": "Boys with moderate use", "INTENSE_BOYS": "Boys with intense use", "LOW_BOTTOM25": "Students in the lowest socio-economic quartile with low or no use", "MODERATE_BOTTOM25": "Students in the lowest socio-economic quartile with moderate use", "INTENSE_BOTTOM25": "Students in the lowest socio-economic quartile with intense use", "LOW_TOP25": "Students in the highest socio-economic quartile with low or no use", "MODERATE_TOP25": "Students in the highest socio-economic quartile with moderate use", "INTENSE_TOP25": "Students in the highest socio-economic quartile with intense use", "LOW_MID": "Students in the middle socio-economic quartiles with low or no use", "MODERATE_MID": "Students in the middle socio-economic quartiles with moderate use", "INTENSE_MID": "Students in the middle socio-economic quartiles with intense use", "_Z": "Not applicable", "AVG_TIME_ALL": "Average time of all 15-year-old students", "AVG_TIME_GIRLS": "Average time of girls", "AVG_TIME_BOYS": "Average time of boys", "AVG_TIME_BOTTOM25": "Students in the lowest socio-economic quartile", "AVG_TIME_TOP205": "Students in the highest socio-economic quartile", "AVG_TIME_MID": "Students in the middle socio-economic quartiles", "AVG_TIME_TOP25": "Students in the highest socio-economic quartile" }, "CL_UNIT_MEASURE_TOOLKIT": { "B1G_GR_R": "Annual real value added growth", "JB": "Number of jobs", "IX_P_H": "Relative productivity per hour worked; other non-agriculture business sector activities = 1.0", "PT_SER_DIG_D_P6_MAN": "Share of domestically produced digital-intensive services embodied in manufacturing exports", "PT_EMP": "Share of employment", "PT_B1GQ": "Share of GDP", "PT_JB": "Share of jobs", "PT_BERD": "Share of total business enterprise expenditure on R&D", "PT_P2": "Share of total intermediate consumption", "PT_B1G_XINFO_P3T6_INFO": "Share of total value added from non-information industries embodied in final demand for information industries products", "PT_B1G_GR": "Share of total value added growth", "KG_10P6USD_B1G": "Kilograms per million USD value added", "T_CO2E_10P3USD_B1G": "Tonnes of CO2 equivalent per thousand USD value added", "T_10P3USD_B1G": "Tonnes per thousand USD value added", "PT_ENT_EM": "Share of employer enterprises", "100HB": "Per 100 inhabitants", "GBIT_SB_M": "GB per month", "USD_10P6": "USD millions", "USD_10P9": "USD billions", "PT": "Share", "PT_ST_Y15T16": "Share of students aged 15-16", "PT_IP5": "Share of IP5 patent families", "PT_POP_Y16T65": "Share of adults", "PT_GRAD": "Share of graduates", "GRAD": "Graduates", "IX_MAX_RES": "Index: 1 = maximum restriction", "PT_ENT": "Share of businesses", "PT_POP": "Share of the population", "SB_100HB": "Subscriptions per 100 inhabitants", "PT_P51G": "Share of gross fixed capital formation", "PT_P3T6_INFO": "Share of total final demand for information industry products", "KG_PS": "Kg per capita", "KG_10P6USD_B1GQ": "Kg per 100k USD of GDP", "PT_WR": "Share of workers", "PT_DS": "Share of datasets present in each country", "IX_DIG_GOV": "Index: 1=highest digital government maturity", "PT_POP_Y16T74": "Share of individuals aged 16-74", "PT_POP_SEX_AGE": "Share of each age and gender group", "PT_POP_INT_3MH": "Share of Internet users who did not buy online in the last 3 months", "PT_POP_SUB": "Share of individuals in the same subgroup", "PT_POP_INT_SUB": "Share of Internet users in the same subgroup", "PT_HH": "Share of households", "PD": "Percentage points", "PT_TOP_DOC": "Share of the top 10% ranked documents in all fields", "PT_EMP_IND": "Share of total employed persons", "PT_EMP_SUB": "Share of total employed persons in the same subgroup", "PT_IND_W_ANY": "Share of individuals who, at work, use any type of computers, portable devices, computerised equipment or machinery", "IX": "Index", "SCORE": "Score", "PT_TRD_SERV_W": "Share of commercial services trade", "PT_POP_Y55T74": "Share of individuals aged 55-74", "PT_POP_INT": "Share of Internet users", "PT_POP_Y16T24": "Share of individuals aged 16-24", "PT_ST_Y11_13_15": "Share of students aged 11, 13 and 15", "TQ_SCORE": "Score (100 = best performance)", "PT_DEMO": "Share of each demographic group", "PT_ENT_VC": "Share of VC-funded start-ups", "ENT_VC": "Number of VC-funded start-ups", "PT_TT": "Share of total trade", "H_D": "Hours per day" }, "CL_OBS_STATUS_TOOLKIT": { "A": "Normal value", "B": "Time series break", "Q": "Missing value: suppressed", "D": "Definition differs", "E": "Estimated value", "B_E": "Break; Estimated value", "K": "Data included in another category", "M": "Missing value: data cannot exist", "W": "Includes data from another category", "O": "Missing value", "U": "Low reliability", "D_U": "Definition differs; Low reliability", "B_U": "Time series break; Low reliability", "B_D_U": "Time series break; Definition differs; Low reliability", "B_D": "Break; Difference in methodology", "Z": "Nil or less than 0.005", "X": "This score relating to the indicated 'period' is based on an underlying indicator value carried-forward from 'year_data'. See readme", "P": "Provisional", "C_UKB": "The data for the United Kingdom relate to England only.", "C_BE2": "The data for the Belgium relate to Flanders only.", "N": "Not significant" } } }