Description

From website:

The Statistical Abstract of the United States, published since 1878, is the authoritative and comprehensive summary of statistics on the social, political, and economic organization of the United States.

Use the Abstract as a convenient volume for statistical reference, and as a guide to sources of more information both in print and on the Web

Sources of data include the Census Bureau, Bureau of Labor Statistics, Bureau of Economic Analysis, and many other Federal agencies and private organizations

Sections include:

• Accommodation, Food, & Other Services
• Agriculture
• Arts, Recreation, & Travel
• Banking, Finance, & Insurance
• Births, Deaths, Marriages, & Divorces
• Business Enterprise
• Construction & Housing
• Education
• Elections
• Energy & Utilities
• Federal Gov’t Finances & Employment
• Foreign Commerce & Aid
• Geography & Environment
• Health & Nutrition
• Income, Expenditures, Poverty, & Wealth
• Information & Communications
• International Statistics
• Labor Force, Employment, & Earnings
• Law Enforcement, Courts, & Prisons
• Manufactures
• National Security & Veterans Affairs
• Natural Resources
• Population
• Prices
• Puerto Rico & the Island Areas
• Science & Technology
• Social Insurance & Human Services
• State & Local Gov’t Finances & Employment
• Transportation
• Wholesale & Retail Trade

Openness: OPEN

• License: US government so public domain.
• Access: ok. Most data provided as xls or pdf but no bulk.
  • www: yes. Browse and then get individual items as xls or pdf. Note one can get some of this information in more convenient form from http://www.usgovernmentspending.com/ (download series page).
  • bulk: no.

This collection contains a snapshot of the learning resource metadata from ESIP's Data management Training Clearinghouse (DMTC) associated with the closeout (March 30, 2023) of the Institute of Museum and Library Services funded (Award Number: LG-70-18-0092-18) Development of an Enhanced and Expanded Data Management Training Clearinghouse project. The shared metadata are a snapshot associated with the final reporting date for the project, and the associated data report is also based upon the same data snapshot on the same date.

The materials included in the collection consist of the following:

• esip-dev-02.edacnm.org.json.zip - a zip archive containing the metadata for 587 published learning resources as of March 30, 2023. These metadata include all publicly available metadata elements for the published learning resources with the exception of the metadata elements containing individual email addresses (submitter and contact) to reduce the exposure of these data.
• statistics.pdf - an automatically generated report summarizing information about the collection of materials in the DMTC Clearinghouse, including both published and unpublished learning resources. This report includes the numbers of published and unpublished resources through time; the number of learning resources within subject categories and detailed subject categories, the dates items assigned to each category were first added to the Clearinghouse, and the most recent data that items were added to that category; the distribution of learning resources across target audiences; and the frequency of keywords within the learning resource collection. This report is based on the metadata for published resourced included in this collection, and preliminary metadata for unpublished learning resources that are not included in the shared dataset.

The metadata fields consist of the following:

Fieldname	Description
abstract_data	A brief synopsis or abstract about the learning resource
abstract_format	Declaration for how the abstract description will be represented.
access_conditions	Conditions upon which the resource can be accessed beyond cost, e.g., login required.
access_cost	Yes or No choice stating whether othere is a fee for access to or use of the resource.
accessibililty_features_name	Content features of the resource, such as accessible media, alternatives and supported enhancements for accessibility.
accessibililty_summary	A human-readable summary of specific accessibility features or deficiencies.
author_names	List of authors for a resource derived from the given/first and family/last names of the personal author fields by the system
author_org - name - name_identifier - name_identifier_type	- Name of organization authoring the learning resource. - The unique identifier for the organization authoring the resource. - The identifier scheme associated with the unique identifier for the organization authoring the resource.
authors - givenName - familyName - name_identifier - name_identifier_type	- Given or first name of person(s) authoring the resource. - Last or family name of person(s) authoring the resource. - The unique identifier for the person(s) authoring the resource. - The identifier scheme associated with the unique identifier for the person(s) authoring the resource, e.g., ORCID.
citation	Preferred Form of Citation.
completion_time	Intended Time to Complete
contact - name - org - email	- Name of person(s) who has/have been asserted as the contact(s) for the resource in case of questions or follow-up by resource user. - Name of organization that has/have been asserted as the contact(s) for the resource in case of questions or follow-up by resource user. - (excluded) Contact email address.
contributor_orgs - name - name_identifier - name_identifier_type - type	- Name of organization that is a secondary contributor to the learningresource. A contributor can also be an individual person. - The unique identifier for the organization contributing to the resource. - The identifier scheme associated with the unique identifier for the organization contributing to the resource. - Type of contribution to the resource made by an organization.
contributors - familyName - givenName - name_identifier - name_identifier_type	- Last or family name of person(s) contributing to the resource. - Given or first name of person(s) contributing to the resource. - The unique identifier for the person(s) contributing to the resource. - The identifier scheme associated with the unique identifier for the person(s) contributing to the resource, e.g., ORCID.
contributors.type	Type of contribution to the resource made by a person.
created	The date on which the metadata record was first saved as part of the input workflow.
creator	The name of the person creating the MD record for a resource.
credential_status	Declaration of whether a credential is offered for comopletion of the resource.
ed_frameworks - name - description - nodes.name	- The name of the educational framework to which the resource is aligned, if any. An educational framework is a structured description of educational concepts such as a shared curriculum, syllabus or set of learning objectives, or a vocabulary for describing some other aspect of education such as educational levels or reading ability. - A description of one or more subcategories of an educational framework to which a resource is associated. - The name of a subcategory of an educational framework to which a resource is associated.
expertise_level	The skill level targeted for the topic being taught.
id	Unique identifier for the MD record generated by the system in UUID format.
keywords	Important phrases or words used to describe the resource.
language_primary	Original language in which the learning resource being described is published or made available.
languages_secondary	Additional languages in which the resource is tranlated or made available, if any.
license	A license for use of that applies to the resource, typically indicated by URL.
locator_data	The identifier for the learning resource used as part of a citation, if available.
locator_type	Designation of citation locatorr type, e.g., DOI, ARK, Handle.
lr_outcomes	Descriptions of what knowledge, skills or abilities students should learn from the resource.
lr_type	A characteristic that describes the predominant type or kind of learning resource.
media_type	Media type of resource.
modification_date	System generated date and time when MD record is modified.
notes	MD Record Input Notes
pub_status	Status of metadata record within the system, i.e., in-process, in-review, pre-pub-review, deprecate-request, deprecated or published.
published	Date of first broadcast / publication.
publisher	The organization credited with publishing or broadcasting the resource.
purpose	The purpose of the resource in the context of education; e.g., instruction, professional education, assessment.
rating	The aggregation of input from all user assessments evaluating users' reaction to the learning resource following Kirkpatrick's model of training evaluation.
ratings	Inputs from users assessing each user's reaction to the learning resource following Kirkpatrick's model of training evaluation.
resource_modification_date	Date in which the resource has last been modified from the original published or broadcast version.
status	System generated publication status of the resource w/in the registry as a yes for published or no for not published.
subject	Subject domain(s) toward which the resource is targeted. There may be more than one value for this field.
submitter_email	(excluded) Email address of

Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and recreation access across the nation. The PAD-US 3.0 Combined Fee, Designation, Easement feature class (with Military Lands and Tribal Areas from the Proclamation and Other Planning Boundaries feature class) was modified to remove overlaps, avoiding overestimation in protected area statistics and to support user needs. A Python scripted process ("PADUS3_0_CreateVectorAnalysisFileScript.zip") associated with this data release prioritized overlapping designations (e.g. Wilderness within a National Forest) based upon their relative biodiversity conservation status (e.g. GAP Status Code 1 over 2), public access values (in the order of Closed, Restricted, Open, Unknown), and geodatabase load order (records are deliberately organized in the PAD-US full inventory with fee owned lands loaded before overlapping management designations, and easements). The Vector Analysis File ("PADUS3_0VectorAnalysisFile_ClipCensus.zip") associated item of PAD-US 3.0 Spatial Analysis and Statistics ( https://doi.org/10.5066/P9KLBB5D ) was clipped to the Census state boundary file to define the extent and serve as a common denominator for statistical summaries. Boundaries of interest to stakeholders (State, Department of the Interior Region, Congressional District, County, EcoRegions I-IV, Urban Areas, Landscape Conservation Cooperative) were incorporated into separate geodatabase feature classes to support various data summaries ("PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.zip") and Comma-separated Value (CSV) tables ("PADUS3_0SummaryStatistics_TabularData_CSV.zip") summarizing "PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.zip" are provided as an alternative format and enable users to explore and download summary statistics of interest (Comma-separated Table [CSV], Microsoft Excel Workbook [.XLSX], Portable Document Format [.PDF] Report) from the PAD-US Lands and Inland Water Statistics Dashboard ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-statistics ). In addition, a "flattened" version of the PAD-US 3.0 combined file without other extent boundaries ("PADUS3_0VectorAnalysisFile_ClipCensus.zip") allow for other applications that require a representation of overall protection status without overlapping designation boundaries. The "PADUS3_0VectorAnalysis_State_Clip_CENSUS2020" feature class ("PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.gdb") is the source of the PAD-US 3.0 raster files (associated item of PAD-US 3.0 Spatial Analysis and Statistics, https://doi.org/10.5066/P9KLBB5D ). Note, the PAD-US inventory is now considered functionally complete with the vast majority of land protection types represented in some manner, while work continues to maintain updates and improve data quality (see inventory completeness estimates at: http://www.protectedlands.net/data-stewards/ ). In addition, changes in protected area status between versions of the PAD-US may be attributed to improving the completeness and accuracy of the spatial data more than actual management actions or new acquisitions. USGS provides no legal warranty for the use of this data. While PAD-US is the official aggregation of protected areas ( https://www.fgdc.gov/ngda-reports/NGDA_Datasets.html ), agencies are the best source of their lands data.

Ecological theories often encompass multiple levels of biological organization, such as genes, individuals, populations, and communities. Despite substantial progress toward ecological theory spanning multiple levels, ecological data rarely are connected in this way. This is unfortunate because different types of ecological data often emerge from the same underlying processes and, therefore, are naturally connected among levels. Here, we describe an approach to integrate data collected at multiple levels (e.g., individuals, populations) in a single statistical analysis. The resulting integrated models make full use of existing data and might strengthen links between statistical ecology and ecological models and theories that span multiple levels of organization. Integrated models are increasingly feasible due to recent advances in computational statistics, which allow fast calculations of multiple likelihoods that depend on complex mechanistic models. We discuss recently developed integrated models and outline a simple application using data on freshwater fishes in south-eastern Australia. Available data on freshwater fishes include population survey data, mark-recapture data, and individual growth trajectories. We use these data to estimate age-specific survival and reproduction from size-structured data, accounting for imperfect detection of individuals. Given that such parameter estimates would be infeasible without an integrated model, we argue that integrated models will strengthen ecological theory by connecting theoretical and mathematical models directly to empirical data. Although integrated models remain conceptually and computationally challenging, integrating ecological data among levels is likely to be an important step toward unifying ecology among levels.

Abstract

The harmonized data set on health, created and published by the ERF, is a subset of Iraq Household Socio Economic Survey (IHSES) 2012. It was derived from the household, individual and health modules, collected in the context of the above mentioned survey. The sample was then used to create a harmonized health survey, comparable with the Iraq Household Socio Economic Survey (IHSES) 2007 micro data set.

----> Overview of the Iraq Household Socio Economic Survey (IHSES) 2012:

Iraq is considered a leader in household expenditure and income surveys where the first was conducted in 1946 followed by surveys in 1954 and 1961. After the establishment of Central Statistical Organization, household expenditure and income surveys were carried out every 3-5 years in (1971/ 1972, 1976, 1979, 1984/ 1985, 1988, 1993, 2002 / 2007). Implementing the cooperation between CSO and WB, Central Statistical Organization (CSO) and Kurdistan Region Statistics Office (KRSO) launched fieldwork on IHSES on 1/1/2012. The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

The survey has six main objectives. These objectives are:

1. Provide data for poverty analysis and measurement and monitor, evaluate and update the implementation Poverty Reduction National Strategy issued in 2009.
2. Provide comprehensive data system to assess household social and economic conditions and prepare the indicators related to the human development.
3. Provide data that meet the needs and requirements of national accounts.
4. Provide detailed indicators on consumption expenditure that serve making decision related to production, consumption, export and import.
5. Provide detailed indicators on the sources of households and individuals income.
6. Provide data necessary for formulation of a new consumer price index number.

The raw survey data provided by the Statistical Office were then harmonized by the Economic Research Forum, to create a comparable version with the 2006/2007 Household Socio Economic Survey in Iraq. Harmonization at this stage only included unifying variables' names, labels and some definitions. See: Iraq 2007 & 2012- Variables Mapping & Availability Matrix.pdf provided in the external resources for further information on the mapping of the original variables on the harmonized ones, in addition to more indications on the variables' availability in both survey years and relevant comments.

Geographic coverage

National coverage: Covering a sample of urban, rural and metropolitan areas in all the governorates including those in Kurdistan Region.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

The survey was carried out over a full year covering all governorates including those in Kurdistan Region.

Kind of data

Sample survey data [ssd]

Sampling procedure

----> Design:

Sample size was (25488) household for the whole Iraq, 216 households for each district of 118 districts, 2832 clusters each of which includes 9 households distributed on districts and governorates for rural and urban.

----> Sample frame:

Listing and numbering results of 2009-2010 Population and Housing Survey were adopted in all the governorates including Kurdistan Region as a frame to select households, the sample was selected in two stages: Stage 1: Primary sampling unit (blocks) within each stratum (district) for urban and rural were systematically selected with probability proportional to size to reach 2832 units (cluster). Stage two: 9 households from each primary sampling unit were selected to create a cluster, thus the sample size of total survey clusters was 25488 households distributed on the governorates, 216 households in each district.

----> Sampling Stages:

In each district, the sample was selected in two stages: Stage 1: based on 2010 listing and numbering frame 24 sample points were selected within each stratum through systematic sampling with probability proportional to size, in addition to the implicit breakdown urban and rural and geographic breakdown (sub-district, quarter, street, county, village and block). Stage 2: Using households as secondary sampling units, 9 households were selected from each sample point using systematic equal probability sampling. Sampling frames of each stages can be developed based on 2010 building listing and numbering without updating household lists. In some small districts, random selection processes of primary sampling may lead to select less than 24 units therefore a sampling unit is selected more than once , the selection may reach two cluster or more from the same enumeration unit when it is necessary.

Mode of data collection

Face-to-face [f2f]

Research instrument

----> Preparation:

The questionnaire of 2006 survey was adopted in designing the questionnaire of 2012 survey on which many revisions were made. Two rounds of pre-test were carried out. Revision were made based on the feedback of field work team, World Bank consultants and others, other revisions were made before final version was implemented in a pilot survey in September 2011. After the pilot survey implemented, other revisions were made in based on the challenges and feedbacks emerged during the implementation to implement the final version in the actual survey.

----> Questionnaire Parts:

The questionnaire consists of four parts each with several sections: Part 1: Socio – Economic Data: - Section 1: Household Roster - Section 2: Emigration - Section 3: Food Rations - Section 4: housing - Section 5: education - Section 6: health - Section 7: Physical measurements - Section 8: job seeking and previous job

Part 2: Monthly, Quarterly and Annual Expenditures: - Section 9: Expenditures on Non – Food Commodities and Services (past 30 days). - Section 10 : Expenditures on Non – Food Commodities and Services (past 90 days). - Section 11: Expenditures on Non – Food Commodities and Services (past 12 months). - Section 12: Expenditures on Non-food Frequent Food Stuff and Commodities (7 days). - Section 12, Table 1: Meals Had Within the Residential Unit. - Section 12, table 2: Number of Persons Participate in the Meals within Household Expenditure Other Than its Members.

Part 3: Income and Other Data: - Section 13: Job - Section 14: paid jobs - Section 15: Agriculture, forestry and fishing - Section 16: Household non – agricultural projects - Section 17: Income from ownership and transfers - Section 18: Durable goods - Section 19: Loans, advances and subsidies - Section 20: Shocks and strategy of dealing in the households - Section 21: Time use - Section 22: Justice - Section 23: Satisfaction in life - Section 24: Food consumption during past 7 days

Part 4: Diary of Daily Expenditures: Diary of expenditure is an essential component of this survey. It is left at the household to record all the daily purchases such as expenditures on food and frequent non-food items such as gasoline, newspapers…etc. during 7 days. Two pages were allocated for recording the expenditures of each day, thus the roster will be consists of 14 pages.

Cleaning operations

----> Raw Data:

Data Editing and Processing: To ensure accuracy and consistency, the data were edited at the following stages: 1. Interviewer: Checks all answers on the household questionnaire, confirming that they are clear and correct. 2. Local Supervisor: Checks to make sure that questions has been correctly completed. 3. Statistical analysis: After exporting data files from excel to SPSS, the Statistical Analysis Unit uses program commands to identify irregular or non-logical values in addition to auditing some variables. 4. World Bank consultants in coordination with the CSO data management team: the World Bank technical consultants use additional programs in SPSS and STAT to examine and correct remaining inconsistencies within the data files. The software detects errors by analyzing questionnaire items according to the expected parameter for each variable.

----> Harmonized Data:

• The SPSS package is used to harmonize the Iraq Household Socio Economic Survey (IHSES) 2007 with Iraq Household Socio Economic Survey (IHSES) 2012.
• The harmonization process starts with raw data files received from the Statistical Office.
• A program is generated for each dataset to create harmonized variables.
• Data is saved on the household and individual level, in SPSS and then converted to STATA, to be disseminated.

Response rate

Iraq Household Socio Economic Survey (IHSES) reached a total of 25488 households. Number of households refused to response was 305, response rate was 98.6%. The highest interview rates were in Ninevah and Muthanna (100%) while the lowest rates were in Sulaimaniya (92%).

• The Ministry of the Interior and Safety publishes the 'Administrative Safety Statistical Yearbook' every year by compiling statistical data from the headquarters of the Ministry of the Interior and Safety and its affiliated organizations in accordance with the 'Ministry of the Interior and Safety Statistics Management Regulations'. - The statistical information by field included in the 'Administrative Safety Statistical Yearbook' is provided as an open API so that it can be used in various fields in both the public and private sectors. - The open API in question is statistics on 'PC video conferencing utilization' among the 'digital government' included in the 'Administrative Safety Statistical Yearbook'. It provides statistical information on the number of PC video conferences opened by organization (central government, local government) and year. - In addition, the 'Administrative Safety Statistical Yearbook' can be downloaded in PDF format from the Ministry of the Interior and Safety website at Policy Data > Statistics > Statistical Yearbook/Statistics by Subject.

The Statistical Abstract is the Nation's best known and most popular single source of statistics on the social, political, and economic organization of the country. The print version of this reference source has been published since 1878 while the compact disc version first appeared in 1993. This disc is designed to serve as a convenient, easy-to-use statistical reference source and guide to statistical publications and sources. The disc contains over 1,400 tables from over 250 different gove rnmental, private, and international organizations. The 1999 CD reflects improved and enhanced data on the disc and the software used for accessing the information. The enrichments to the data and their access include: a link for table of contents page to a PDF of The Census web site. This enable the user to have direct links to the Statistical Abstract and its supplements and other features, such as Statistics in Brief and Frequently Requested Tables. A link to the table of contents from the first text page of each section facilitates quick movement between sections of the book. New PDFs provide more explanation of several major economic series including the Federal Budget, the National Income and Product Accounts (NIPA), the Consumer Price Index (CPI)and Producer Price Index (PPI), and the new North American Industry Classification System (NAICS). Another PDF provides information on the Federal court system. Links to these supplemental materials are provided from each appropriate table. A separate PDF presents a compilation of tables showing major economic indices, as selected by the Council of Economic Advisors. Maps of each state and their metro areas and component counties, maps outlining National Park sites throughout the country, a map of the United States with major transportation facilities and routes, a U.S.map locating coal mines and facilities, and one depicting the distribution of forest land have been added. As usual, updates have been made to most of the more than 1,500 tables and charts that were on the previous disc with new or more recent data. The spreadsheet files, which are available in both Excel and Lotus formats, will usually have more information than the tables displayed in the book or Adobe Acrobat files. The 1999 year introduced over 100 new tables covering a wide range of subject areas. Several sections have preliminary data from the 1997 Economic Census, which presents industry statistics for the first time based on the North American Industry Classification System (NAICS). Comparative data for 1992 and 1997, based on the Standard Industrial Classification (SIC), are also presented. Tables 872 and 873 in Section 17, Business, present summary data for industries. Other new tables cover such topics as the foreign-born population, health care expenditures, the medicare trust fund, violence in schools, presale handgun checks, recycling programs, defense- related employment and spending, workplace violence, ownership of mutual funds, computer use, results of the 1997 Census of Agriculture, and mail order catalogue sales. In addition to the above new tables, a new section has been developed, the 20th Century Statistics. This section introduces data beginning in 1900 on a broad range of subjects, including population, vital statistics, health, education, income, labor force, communications, agriculture, defense, and other areas. The Industrial Outlook tables, previously in Section 31, have been deleted for lack of updates. For a complete list of new tables, see Appendix VI,p.947. The Adobe Acrobat Reader and Search engine, Version 4.0, is on the disc. The Acrobat Reader allows users to view, navigate, search, and print on demand any of the pages from the book. Note to Users: This CD is part of a collection located in the Data Archive of the Odum Institute for Research in Social Science, at the University of North Carolina at Chapel Hill. The collection is located in Room 10, Manning Hall. Users may check the CDs out subscribing to the honor system. Items can be checked out for a period of two weeks. Loan forms are located adjacent to the collection.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

The dataset includes a decision matrix, with the most recent available data representing performance values of 16 selected countries with regard to 25 criteria of healthcare system efficiency collected in 2023. The data was collected from the following sources: websites of OECD Health Statistics, Eurostat, and World Health Organization. Data is available in PDF, XLSX, and TEX format. XLSX and TEX files are provided in a folder named data.zip.

Achieving the health and well-being related Sustainable Development Goals (SDGs) and the World Health Organization’s (WHO) Triple Billion Targets depends on informed decisions that are based on concerted data collection and monitoring efforts. Even though data availability has been increasing in recent years, significant gaps still remain for routine surveillance to guide policies and actions. The COVID-19 crisis has shown that more and better data and strengthened health information systems are needed to inform timely decisions that save lives. Traditional sources of data such as nationally representative surveys are not adequate for addressing this challenge alone. Additionally, the funding required to measure all health and well-being related SDG indicators and Triple Billion Targets using only traditional sources of data is a challenge to achieving efficient, timely and reliable monitoring systems. Citizen science, public participation in scientific research and knowledge production, can contribute to addressing some of these data gaps efficiently and sustainably when designed well, and ultimately, could contribute to the achievement of the health and well-being related SDGs and Triple Billion Targets. Through a systematic review of health and well-being related indicators, as well as citizen science initiatives, this paper aims to explore the potential of citizen science for monitoring health and well-being and for mobilizing action toward the achievement of health and well-being related targets as outlined in the SDG framework and Triple Billion Targets. The results demonstrate that out of 58 health and well-being related indicators of the SDGs and Triple Billion Targets covered in this study, citizen science could potentially contribute to monitoring 48 of these indicators and their targets, mostly at a local and community level, which can then be upscaled at a national level with the projection to reach global level monitoring and implementation. To integrate citizen science with official health and well-being statistics, the main recommendation is to build trusted partnerships with key stakeholders including National Statistical Offices, governments, academia and the custodian agencies, which is mostly the WHO for these health and well-being related targets and indicators.

Blockchain IoT Market size was valued at USD 418.66 Million in 2022 and is poised to grow from USD 630.79 Million in 2023 to USD 16,753.39 Million by 2031, at a CAGR of 50.67% during the forecast period (2025-2032).

Abstract

The Government of Iraq, with support from UNICEF finalized and launched a Multiple Indicator Cluster Survey (MICS 6) in 2018. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Data and information from MICS6 provides credible and reliable evidence for the Government of Iraq to monitor the National Development Plan and establish baselines and monitor progress towards Sustainable Development Goals (SGDs). It helps the government and its stakeholders to understand disparities and the wider development challenges in the country.

The 2018 Iraq MICS has as its primary objectives:

• To provide high quality data for assessing the situation of children, adolescents, women and households in Iraq;

• To furnish data needed for monitoring progress towards national goals, as a basis for future action;

• To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable;

• To validate data from other sources and the results of focused interventions;

• To generate data on national and global SDG indicators;

• To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention.

Geographic coverage

The sample for the Iraq MICS 2018 was designed to provide estimates at the national, regional and governorates level, for urban and rural areas. Specifically the sample for the Iraq MICS 2018 survey includes 2 regions - Kurdistan and South/Central Iraq and 18 governorates - Duhok, Nainawa, Sulaimaniya, Kirkuk, Erbil, Diala, Anbar, Baghdad, Babil, Karbalah, Wasit, Salahaddin, Najaf, Qadissiyah, Muthana, Thiqar, Musan, and Basra.

Analysis unit

• Individuals

• Households

Universe

The MICS survey considers the households and their members in all urban and rural areas of Iraq as the Universe. Thus, the Universe for Iraq consists of all persons in the country residing in various geographic locations considering all special ethnic or economic groups in the rural and urban areas of Iraq. For the purposes of this survey, Internally Displaced Persons living in United Nations/government notified camps, military installations, and non-residential units such as business establishments were not considered in the scope of the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING FRAME

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The last census in Iraq was carried out in 1998 and the sampling frame was developed during that time. The most recent update of this sampling frame was done in 2009 which was used by Central Statistical Office (CSO) for the selection of the Clusters in Iraq region. On the other hand, the Kurdistan Region Statistical Office (KRSO) has updated the 2009 sampling frame for the 3 main cities of Kurdish region and their periphery and used it to draw the Clusters. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs). A listing of households was conducted in each sample EA, and a sample of households was selected at the second stage.

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size has been calculated using the prevalence rates of key indicators from the 2011 MICS. For the purpose of identifying the optimal sample size for 2018 MICS, all the factors such as time, cost, domain of estimation, sampling and non-sampling errors were taken into account, as well as the desired level of precision of the key prevalence indicator. The sample size was calculated at the governorate level. It was decided that 2018 MICS will provide the estimates at the governorate level, so the indicative sample size has been calculated using governorate as the domain for the geographic representation. The formula for calculating the sample size is described in Appendix A of report available in related materials.

A number of meetings were held in the CSO to finalize the sample size, and various refinements were studied using the referred formula. As a result of these discussions the MICS Technical Committee reached a consensus on a sample size of 1,080 households for each governorate of Iraq, where each governorate was divided into 90 sample clusters and 12 households were selected per cluster (90 clusters x 12 households = 1,080 households). Baghdad was sub-divided into two administrative areas, therefore 19 total individual domains were used for a total sample size of 20,520 households (19 domains x 1,080 households).

One-third of the sampled households was selected for water quality testing, which means 360 households per governorate or 6,840 (360 X 19) households for the overall survey. The subsample of 4 households for the water quality testing in each cluster are selected using systematic random sampling.

Each Governorate is further stratified into urban and rural areas, and the sample within each governorate is allocated proportionately to the urban and rural strata based on the population. The urban and rural areas within each governorate are the main sampling strata. Within each stratum, a specified number of clusters is selected systematically using probability proportionate to size (PPS) sampling methodology. After the selection of the clusters in each rural and urban stratum, a new listing of households was conducted in each sample cluster. Then a systematic random sample of 12 households per cluster is drawn from the listing for each rural and urban sample cluster.

SELECTION OF ENUMERATION AREAS (CLUSTERS):

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the Iraq 2009 sampling frame. The first stage of sampling was thus completed by selecting the required number of sample EAs (specified in Table SD.2) from each of the 19 sampling domains, separately for the urban and rural strata. However, there are a few areas belonging to two governorates that were not accessed due to security reasons. These governorates are Nainawa and Kirkuk. In Nainawa 5 districts were excluded (Ba'aj, Al-Hadar, Telafer, Sinjar and Makhmoor), while only Haweja district in Kirkuk was excluded. The excluded districts represent around 22% of the urban population and 51% of the rural population in Nainawa. The percentage of not accessed area in final sample for Kirkuk represents 5% of the Urban and 42% of the rural population, following the exclusion of Haweja district.

SELECTION OF HOUSEHOLDS:

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to Mhi (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 12 households in each enumeration area was carried out using random systematic selection procedures. The MICS6 spreadsheet template for systematic random selection of households was adapted for this purpose.

The Iraq 2018 MICS also included water quality testing for a subsample of households within each sample cluster. A subsample of 4 of the 12 selected households was selected in each sample cluster using random systematic sampling for conducting water quality testing, for both water in the household and at the source, including a chlorine test. The MICS6 household selection template includes an option to specify the number of households to be selected for the water quality testing, and the spreadsheet automatically selected the corresponding subsample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Five questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 4 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 5) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

The questionnaires were based on the MICS6 standard questionnaires. From the MICS6 model Arabic version, the questionnaires were customised and translated to two Kurdish dialects and were pre-tested in 3 governorates (Baghdad, Najaf and Basra) in South/Central Iraq region and 3 governorates (Duhok, Erbil & Sulaimaniya) in Kurdistan region of Iraq during Dec 2017/Jan 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

Cleaning operations

Data were received at the Central Statistical Organization (CSO) via Internet File Streaming System (IFSS), integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in details in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data

This data release documents the data and models used to assess flows, concentrations, and loads of highway and urban runoff and of stormwater within receiving streams in southern New England. There are more than 48,000 locations in southern New England where roads cross streams and many more locations where runoff from developed areas may discharge to receiving streams; information about runoff discharges and the quantity and quality of stormflow upstream and downstream of discharge points is needed to inform resource-management decisions. This analysis was done with a version 1.1.1 of the Stochastic Empirical Loading and Dilution Model (SELDM) that was populated with regional statistics for southern New England. SELDM uses basin properties and hydrologic statistics to simulate runoff from a site of interest, which may be a highway site or another developed (urban) area, and concurrent stormflow from an upstream basin to calculate downstream values, which are the sum of contributions from the site of interest and the upstream basin. Because there are few monitoring sites with data relative to the number of potential sites of interest, the probability that data will be available at a site of interest is low. Furthermore, much of the data available at monitored sites is not sufficient to characterize long-term stormwater-quality conditions because most water-quality monitoring sites have less than one year of data. The statistics for highway and upstream basin properties, hydrologic variables, and stormwater quality provided in this data release can be used to represent long-term conditions throughout southern New England. The simulated populations of flows, concentrations, and loads documented in this data release represent long-term conditions at representative sites of interest. This data release also documents results of sensitivity analyses designed to guide the selection of input variables for runoff quality simulations and selected example simulations that illustrate use of simulation results for decision making. The methods and statistics in this study were developed for use with SELDM but may be used with other models. The information provided here can be used for robust decision making by highway practitioners, regulators, and decisionmakers. The project described in this data release was conducted in cooperation with the Federal Highway Administration and the Connecticut, Massachusetts, and Rhode Island Departments of Transportation. The data release contains twenty-one compressed (zip) files, one ReadMe file pertaining to the data release as a whole (ReadMe.txt), and a diagram to illustrate the organization of the zip files and subfolders (ReadMeDiagram.pdf). Please refer to ReadMe files within the zip files and subfolders for more detailed metadata pertaining to the data, statistics, and software provided.

In 2024, the number of data compromises in the United States stood at 3,158 cases. Meanwhile, over 1.35 billion individuals were affected in the same year by data compromises, including data breaches, leakage, and exposure. While these are three different events, they have one thing in common. As a result of all three incidents, the sensitive data is accessed by an unauthorized threat actor. Industries most vulnerable to data breaches Some industry sectors usually see more significant cases of private data violations than others. This is determined by the type and volume of the personal information organizations of these sectors store. In 2024 the financial services, healthcare, and professional services were the three industry sectors that recorded most data breaches. Overall, the number of healthcare data breaches in some industry sectors in the United States has gradually increased within the past few years. However, some sectors saw decrease. Largest data exposures worldwide In 2020, an adult streaming website, CAM4, experienced a leakage of nearly 11 billion records. This, by far, is the most extensive reported data leakage. This case, though, is unique because cyber security researchers found the vulnerability before the cyber criminals. The second-largest data breach is the Yahoo data breach, dating back to 2013. The company first reported about one billion exposed records, then later, in 2017, came up with an updated number of leaked records, which was three billion. In March 2018, the third biggest data breach happened, involving India’s national identification database Aadhaar. As a result of this incident, over 1.1 billion records were exposed.

(Additional information below)

The Myanmar Statistical Yearbook 2022 provides an updated compendium of statistics on demographic, geographic, and socio-economic conditions of Myanmar to national and international audiences.

The statistics are compiled mainly from administrative records of the relevant Ministries, Departments, Enterprises, and Private Agencies. It also includes data from Census and Surveys conducted by Government Ministries and the Central Statistical Organization.

Statistical Yearbooks in PDF since 2011

Data in Excel format since 2018

Health chapter for 2022

Information on climate, vital statistics, justice, education, labor, agriculture, forestry, etc. is available.

Global Hybrid Integration Platform Market size was valued at USD 31.69 Billion in 2022 and is poised to grow from USD 35.49 Billion in 2023 to USD 87.88 Billion by 2031, growing at a CAGR of 12% in the forecast period (2024-2031).

Abstract

To take care of the limitations of the earlier Time Use Studies in India and to meet the new emerging data requirements, Ministry of Statistics and Programme Implementation, Government of India, therefore, conducted a pilot Time Use Survey in 18620 households spread over six selected states , namely, Haryana, Madhya Pradesh, Gujarat, Orissa, Tamil Nadu and Meghalaya during the period July, 1998 to June, 1999.

Following were the main objectives of this survey:

1. To develop a conceptual framework and a suitable methodology for designing and conducting time use studies in India on a regular basis. Also, to evolve a methodology to estimate labour force/work force in the country and to estimate the value of unpaid work in the economy in a satellite account.

2. To infer policy/programme implications from the analysis of the data on (a) distribution of paid and unpaid work among men and women in rural and urban areas, (b) nature of unpaid work of women including the drudgery of their work and (c) sharing of household work by men and women for gender equity.

3. To analyze the time use pattern of the individuals to understand the nature of their work so as to draw inference for employment and welfare programmes for them.

4. To analyze the data of the time use pattern of the specific section of the population such as children and women to draw inferences for welfare policies for them.

5. To collect and analyze the time use pattern of people in the selected states in India in order to have a comprehensive information about the time spent by people on marketed and non-marketed economic activities covered under the 1993-SNA, non marketed non-SNA activities covered under the General Production Boundary and on personal care and related activities that cannot be delegated to others.

6. To use the data in generating more reliable estimates on work force and national income as per 1993 SNA, and in computing the value of unpaid work through separate satellite account,

Keeping in view the importance of the survey for India and our specific socio-economic situation similar to other developing countries, this survey was conducted using own financial, technical and manpower resources. Moreover, to ensure capacity building for conducting such surveys on a regular basis, this survey was conducted by utilizing the official statistical system machinery.

Geographic coverage

Six States and their Urban and Rural area

Analysis unit

Households

Universe

All residential Households of Six States.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design adopted in the survey was three stage stratified design. The first, second and third stages were the district, villages/urban blocks and households. Proper stratification of the districts in the selected states were done using the population density and proportion of tribal population to ensure capturing of the variability in the population. In the villages/urban blocks also sub-stratification was adopted to ensure representation of all types of households in the Survey.

The total number of households covered in the sample was 18,628 planned. The total sample size of 18,628 households were first distributed in proportion to the total number of estimated households as per the 1993-94 survey of the National Sample Survey Organisation. No. of first stage units (villages and sample blocks) were determined using the initial sample size to be allocated to each state and by assuming that in each f.s.u. , 12 households will be surveyed. The number of f.s.u. so arrived at was adjusted to be multiple of 8 as atleast 2 f.s.u. each may be covered in 4 sub-rounds.

Selection of villages : All the villages in the selected district were grouped in 3 categories namely large (population above 1200), medium (population between 400 to 1200) and small(population less than 400) . The total rural sample was distributed in three stratum in proportion to the population in the three stratum. In case any stratum was not applicable in a particular district, the allocated sample was distributed in the remaining stratum only. If more than one village was to be selected in the particular stratum , then villages-were selected using circular systematic sampling with probability proportional to the population. If all the three strata were present then minimum sample size allotted in each stratum was 2.

Selection of urban sample blocks : All the towns in the selected district were grouped in 3 categories namely large(population more than 2 lakhs), medium(population between 50000 to 2 lakhs) and small (population less than 50000) . The total urban sample was distributed in three stratum in proportion to the population in the three stratum. In case any stratum was not applicable in a particular district, the allocated sample was distributed in the remaining stratum only. If more than one sample block was to be selected in the particular stratum, then ufs blocks in each of the towns were presented by investigator unit and ufs blocks no. The requisite number of ufs blocks were then selected by using circular systematic sampling with equal probability. If all the three strata were present then minimum sample size allocated in each stratum was 2 due to this, in some cases, overall urban sample size allotted in a particular district might have increased.

As no previous survey was conducted on this topic and methodologies to be used were not firmed up, it was decided to conduct this survey on a pilot basis. However, to ensure the use of data collected in the pilot survey also, a proper sampling procedure was followed.

Refer the attached document named 'Report' attached under external resource

Sampling deviation

There was no deviation from the original sample deviation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The final questionnaire used in the survey was evolved after a number of discussion with the academic experts and the practising survey statisticians. The final questionnaire consisted of following three parts: i. Schedule 0.1: Listing Questionnaire for the Rural Areas ii. Schedule 0.2: Listing Questionnaire for the Urban Areas iii. Schedule 0.3: Household Questionnaire which consist of following Blocks

(a) Block 0: Identification of Sample Households (b) Block 1: Household Characteristics (c) Block 2: Particulars of Household Members (d) Block 3: Time Disposition of Persons on Selected Days of the Week

A copy of the questionnaire is attached as external resource

Cleaning operations

The date entry and validation work of the Survey was handled by the States for which data entry and validation packages were supplied by the Central Statistical Organization. A Workshop was also organized to sort out the various problems faced by the States in the use of these packages. For evolving the data entry and validation package, the help of Data Processing Division of the National Sample Survey Organization was taken. The validated data was sent by States to the CSO and the final processing of the data was done by the Computer Centre of the Department. In spite of severe problem faced ion the operation of main-frame computer at the Computer Center, data processing work of the Survey completed by the end of November, 99.

Response rate

The total number of households covered in the sample was 18.591 as against 18,620 originally planned. 68 % of the households was in rural areas. Therefore, the non-response at 0.1 % was negligible.

Sampling error estimates

The standard error estimates may be calculated on the basis of sub-sample wise estimates of stratum totals.

For Detail refere to Page no 18 of the Report of The Time Use Survey 1998.

A majority of businesses responding to a 2023 survey said that investment in data and analytics was a top priority. However, only ** percent said that their efforts to improve data quality had been successful, highlighting an ongoing challenge faced by organizations across industry sectors.

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Understanding how much inorganic fertilizer (referred to as fertilizer) is applied to different crops at national, regional and global levels is an essential component of fertilizer consumption analysis and demand projection. Good information on fertilizer use by crop (FUBC) is rarely available because it is difficult to collect and time-consuming to process and validate. To fill this gap, a first global FUBC report was published in 1992 for the 1990/1991 period, based on an expert survey conducted jointly by the Food and Agriculture Organization (FAO) of the UN, the International Fertilizer Development Center (IFDC) and the International Fertilizer Association (IFA). Since then, similar expert surveys have been carried out and published every two to four years in the main fertilizer-consuming countries. Since 2008 IFA has led these efforts and, to our knowledge, remains the only globally available data set on FUBC. This dataset includes data (in CSV format) from a survey carried out by IFA to represent the 2017–18 period as well as a collation of all historic FUBC data. Methods Latest fertilizer use by crop survey data During 2020-2022 IFA collected and standardized FUBC data for the 2017-18 period, primarily through a survey of various country correspondents. As of May 2022 this is the most recent survey for FUBC data. Country correspondents were selected based on their knowledge for estimating fertilizer use, average fertilizer application rates and areas of crops for N, P2O5 and K2O for their respective country, and access to any locally available farm data. Country correspondents were asked to complete the questionnaire with the greatest detail possible, or to provide data for the crop breakdown available in their country. The task of aligning the data with FAO crop area statistics was particularly challenging, and sometimes impossible. Even when correspondents were able to mostly follow the provided crop breakdown, crops that are minor in a country’s agriculture were often included in a group of crops or other crops. For example, for most EU countries, the data provided by Fertilizers Europe follow the crop breakdown that is specific to their own annual survey. In this crop breakdown, rice is grouped with rye, triticale and oats, soybean is grouped with sunflower and linseed, and cotton is not identified. Historic fertilizer use by crop survey data For historic FUBC data the following sources had data manually extracted from the original pdf documents into a standardized format: · FUBC report number 1: FAO et al. (1992) · FUBC report number 2: FAO et al. (1994) · FUBC report number 3: FAO et al. (1996) · FUBC report number 4: FAO et al. (1999) · FUBC report number 5: FAO et al. (2002) · FUBC report number 6: Heffer (2009) · FUBC report number 7: Heffer (2013) · FUBC report number 8: Heffer et al. (2017) References FAO, IFA, IFDC. 1992. Fertilizer use by crop 1. Rome, Italy: Food and Agriculture Organization of the United Nations, 82 p. FAO, IFA, IFDC. 1994. Fertilizer use by crop 2. Rome, Italy: Food and Agriculture Organization of the United Nations, 64 p. FAO, IFA, IFDC. 1996. Fertilizer use by crop 3. Rome, Italy: Food and Agriculture Organisation of the United Nations, 74 p. FAO, IFA, IFDC. 1999. Fertilizer use by crop 4. Rome, Italy: Food and Agriculture Organisation of the United Nations, 78 p. FAO, IFA, IFDC, IPI, PPI. 2002. Fertilizer use by crop 5. Rome, Italy.: Food and Agriculture Organization of the United Nations, 67 p. Heffer P. 2009. Assessment of Fertilizer Use by Crop at the Global Level 2006/07 – 2007/08. Paris, France: International Fertilizer Association, 11 p. https://www.ifastat.org/consumption/fertilizer-use-by-crop. Heffer P. 2013. Assessment of Fertilizer Use by Crop at the Global Level. Paris, France, 10 p. https://www.ifastat.org/consumption/fertilizer-use-by-crop. Heffer P, Gruere A, Roberts T. 2017. Assessment of fertiliser use by crop at the global level. Paris, France: International Fertilizer Association, Institute IPN, 19 p. https://www.ifastat.org/plant-nutrition.