Context. This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 million cells.

Content. The data published in this repository correspond to a first release, i.e. a diachronic slice of one register every 8 to 9 years. Unfortunately, the remaining data are currently under embargo. Their publication will take place as soon as possible, and at the latest by the end of 2023. In the meantime, the data presented here correspond to a large subset of 2,844 pages, which already allows to investigate most research hypotheses.

Description. The population censuses, digitized by the Archives of the city of Lausanne, continuously cover the evolution of the population in Lausanne throughout the 19th century, starting in 1805, with only one long interruption from 1814 to 1831. Highly detailed, they are an invaluable source for studying migration, economic and social history, and traces of cultural exchanges not only with Bern, but also with France and Italy. Indeed, the system of tracing family origin, specific to Switzerland, allows to follow the migratory movements of families long before the censuses appeared. The bourgeoisie is also an essential economic tracer. In addition, censuses extensively describe the organization of the social fabric into family nuclei, around which gravitate various boarders, workers, servants or apprentices, often living in the same apartment with the family.

Production. The structure and richness of censuses have also provided an opportunity to develop automatic methods for processing structured documents. The processing of censuses includes several steps, from the identification of text segments to the restructuring of information as digital tabular data, through Handwritten Text Recognition and the automatic segmentation of the structure using neural networks. Please note that the detailed extraction methodology, as well as the complete evaluation of performance and reliability is published in:

Petitpierre R., Rappo L., Kramer M. (2023). An end-to-end pipeline for historical censuses processing. International Journal on Document Analysis and Recognition (IJDAR). doi: 10.1007/s10032-023-00428-9

Data structure. The data are structured in rows and columns, with each row corresponding to a household. Multiple entries in the same column for a single household are separated by vertical bars ⟨|⟩. The center point ⟨·⟩ indicates an empty entry. For some columns (e.g., street name, house number, owner name), an empty entry indicates that the last non-empty value should be carried over. The page number is in the last column.

Liability. The data presented here are not curated nor verified. They are the raw results of the extraction, the reliability of which was thoroughly assessed in the above-mentioned publication. We insist on the fact that for any reuse of this data for research purposes, the implementation of an appropriate methodology is necessary. This may typically include string distance heuristics, or statistical methodologies to deal with noise and uncertainty.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area. Census Tracts 2010 reviewed 05/15/2015

Source: United States Census Bureau

Effective Date:

Last Update: 05/15/2015

Update Cycle: As needed, Census is completed every 10 years.

More Metadata

This GIS layer contains the geographical boundaries of the 2010 census tracts for Loudoun County, Virginia. The 2010 Census tract boundaries are used for Census Bureau statistical data tabulation purposes, including the 2010 Decennial Census and American Community Surveys.

Census tracts are part of the sub-county census geography hierarchy of tracts, block groups, and blocks. The three census geographies nest to each other, forming a hierarchy of census tract, followed by block groups, and then blocks, with blocks being the smallest. A census tract consists of one or more census block groups and is a cluster of census blocks within the same census tract. Tracts are uniquely identified within a County by a six digit number. The last two digits will be zeros unless earlier divisions of the census tract occurred as a result of population growth.

Loudoun County's tracts were delineated by Loudoun County Government during the Census Bureau's Participant Statistical Areas Program for the 2010 Census. The 2010 Census tract layer has been modified from the Census Bureau's Tiger line file. Users should be aware that the Census's Tiger line data is devised from a mix of national and local GIS data sets. When the Tiger line data is overlaid with Loudoun County Government's detailed GIS layers it can be determined that the Census Bureau's Tiger line boundaries in some cases are slightly off from the actual location of the physical features, natural features, and governmental units such as town boundaries that they are designated to follow. The 2010 Loudoun census tract layer was generated by Loudoun County so that the tract boundaries would overlay with the features in Loudoun County's GIS data sets that the boundary are designated to follow.

More Metadata

This GIS layer contains the geographical boundaries of the 2010 census blocks for Loudoun County, Virginia. The 2010 Census block boundaries were used for statistical data collection and tabulation purposes for the 2010 Decennial Census. Census blocks are the smallest geographic area for publishing data from the decennial Census.

The 2010 Census block layer has been modified from the Census Bureau's Tiger line file. Users should be aware that the Census's Tiger line data is devised from a mix of national and local GIS data sets. When the Tiger line data is overlaid with Loudoun County Government's detailed GIS layers it can be determined that the Census Bureau's Tiger line boundaries in some cases are slightly off from the actual location of the physical features, natural features, and governmental units such as town boundaries that they are designated to follow. The 2010 Loudoun Census block layer was generated by Loudoun County so that the block boundaries would overlay with the features in Loudoun County's GIS data sets that the boundary are designated to follow.

As per Cognitive Market Research's latest published report, the Global Genealogy Products and Services Market size will be USD 5,093.64 Million by 2028. Genealogy Products and Services Industry's Compound Annual Growth Rate will be 7.97% from 2023 to 2030.

The North America Genealogy Products and Services market size will be USD 2,008.93 Million by 2028.

Market Dynamics of Genealogy Products and Services

Key Drivers for Genealogy Products and Services

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Mobile Applications and Research Tools for On-the-Go: There is an increasing trend towards mobile-optimized platforms, allowing users to investigate family trees, upload documents, and engage with relatives directly from their smartphones. Introduction of Genealogy Products and Services

Genealogy is study of family and their history, tracing lineages, obtaining information about family, ancestors and it comprises DNA testing cemetery records, family tree creation, newspapers, online records, blogs, links that provides access to database for obtaining information about family members.

There are various institutions, advanced applications that are mobile based used for finding information about ancestors. The market is growing rapidly with adoption of emerging technologies that boost its growth in the market.

There is increasing technological advancement in the genealogical studies and its benefits in effectively find out information about ancestors has gained popularity across globe that drives the growth of genealogy products and service market.

For instance, there are various technological incorporation and ensure cost effective research that helps in tracing lineages, information about ancestors. The major companies are adopting DNA testing services and they merged genealogical research with genetic testing that helps in obtaining information about families. They have database, online records that has detailed information about ancestors. They use modern applications such as Ancestry, electronic database, blogs, that provide accurate database and genetic representation of family tree used in genetic services.

There are various benefits such as genealogical data provides medical history of...

Abstract

The primary mission of the 2006 Population and Housing Census (PHC) of Nigeria was to provide data for policy-making, evidence-based planning and good governance. The Government at all tiers, researchers, the academia, civil society organizations and the international agencies will find the sets of socio-demographic data useful in formulating developmental policies and planning. The 2006 data will certainly provide benchmarks for monitoring the Millennium Development Goals (MDGs). Enumeration in the 2006 PHC was conducted between March 21st and 27th 2006. It was designed to collect information on the quality of the population and housing, under the following broad categories: demographic and social, education, disability, household composition, economic activity, migration, housing and amenities, mortality and fertility. The results of the exercise are being released as per the Commission's Tabulation Plan which began with the release of the total enumerated persons by administrative areas in the country in the Official Gazette of the Federal Republic of Nigeria No.2, Vol 96 of February 2,2009 and followed with the release of Priority Tables that provide some detailed characteristics of the population of Nigeria by State and LGA.

Geographic coverage

National

Analysis unit

Individuals Households

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Census 2006 Processing: The Technology and Methodology:-

Unlike the data capture method used for the country’s previous censuses, where information from the census forms are typed into the computer system, data capture for census 2006 was carried out by OMR/OCR/ICR systems where questionnaires are scanned through high speed optical scanners. The choice of the scanning system was because it is faster and more accurate than the data keying method.

OMR/OCR/ICR Technology

Definition of terms

• OMR (Optical Mark Recognition) - This means the ability of the scanning machine to detect pencil marks made on the questionnaires by the Enumerators in accordance with the responses given by the respondents.
• OCR (Optical Character Recognition) - This means the ability of the scanning machine to recognize machine printed characters on the questionnaires.
• ICR (Intelligent Character Recognition) - This means the ability of the scanner to recognize characters hand written by the Enumerators in accordance with the responses given by the respondents.

Processing Procedures of Census 2006 at the DPCs:- Data processing took place in the Commission’s seven (7) Data Processing Centres located in different geographical zones in the country. There was absolute uniformity in the processing procedures in the seven DPCs.

(a) Questionnaire Retrieval/Archiving Questionnaires from the fields were taken directly from the Local Government Areas to designated DPCs. The forms on arrival at the DPCs were counted, archived and labeled. Retrieval of the questionnaires at the DPCs were carried out based on the EA frame received from the Cartography Department. Necessary Transmittal Forms are completed on receipt of the Forms at the DPCs. The Transmittal Forms are also used to keep track of questionnaires movement within the DPC.

(b) Forms Preparation The scanning machine has been designed to handle A4 size paper. And the Census form being twice that size has to be split into two through the dotted lines at the middle of the form. This forms preparation procedure is to get the questionnaires, for each Enumeration Areas (EAs), ready for scanning. There is a Batch Header to identify each batch.

(c) Scanning Each Batch on getting to the Scanning Room was placed on joggers (a vibrating machine)to properly align the forms, and get rid of dust or particles that might be on the forms.

The forms are thereafter fed into the scanner. There were security codes in form of bar codes on each questionnaire to identify its genuineness. There was electronic editing and coding for badly coded or poorly shaded questionnaires by the Data Editors. Torn, stained or mutilated forms are rejected by the scanner. These categories of forms were later manually keyed into the system.

Re-archiving of Scanned Forms:- Scanned forms were placed in their appropriate marked envelopes in batches, and thereafter returned to the Archiving Section for re-archiving.

Data Output from the Scanning Machine:- The OMR/OCR Software interprets the output from the scanner and translates it into an XML file from where it is further translated into the desired ASCII output that is compatible for use by the CSPro Package for further processing and tabulation.

Data back-up and transfer:- After being sure that the data are edited for each EA batch in an LGA, data then was exported to the SAN (Storage Area Network) of the Server. Two copies of images of the questionnaires for each EA copied to the LTO tapes as backup and then transferred to the Headquarters. The ASCII data files for each LGA are zipped and encrypted, and thereafter transfer to the Data Validation Unit (DVU) at the Headquarters in Abuja.

Data appraisal

Data collation and validation:- The Data Validation Unit at the Headquarters was responsible for collating these data into EAs, LGAs, States and National levels. The data are edited/validated for consistency errors and invalid entries. The Census and Survey Processing (CSPro) software is used for this process. The edited, and error free data are thereafter processed into desired tables.

Activities of the Data Validation unit (DVU):-

Decryption of each LGA Data File Concatenation/merging of Data Files Check each EA batch file for EA completeness within an LGA and State Check for File/Data Structure Check for Range and Invalid Data items Check for Blank and empty questionnaire Check for inter and intra record consistency Check for Skip Patterns Perform Data Validation and Imputation Generate Statistics Report of each function/activity Generate Statistical Tables on LGA, State and National levels.

The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

This table contains data on household income and poverty status from the American Community Survey 2006-2010 database for tracts. The American Community Survey (ACS) is a household survey conducted by the U.S. Census Bureau that currently has an annual sample size of about 3.5 million addresses. ACS estimates provides communities with the current information they need to plan investments and services. Information from the survey generates estimates that help determine how more than $400 billion in federal and state funds are distributed annually. Each year the survey produces data that cover the periods of 1-year, 3-year, and 5-year estimates for geographic areas in the United States and Puerto Rico, ranging from neighborhoods to Congressional districts to the entire nation. This table also has a companion table (Same table name with MOE Suffix) with the margin of error (MOE) values for each estimated element. MOE is expressed as a measure value for each estimated element. So a value of 25 and an MOE of 5 means 25 +/- 5 (or statistical certainty between 20 and 30). There are also special cases of MOE. An MOE of -1 means the associated estimates do not have a measured error. An MOE of 0 means that error calculation is not appropriate for the associated value. An MOE of 109 is set whenever an estimate value is 0. The MOEs of aggregated elements and percentages must be calculated. This process means using standard error calculations as described in "American Community Survey Multiyear Accuracy of the Data (3-year 2008-2010 and 5-year 2006-2010)". Also, following Census guidelines, aggregated MOEs do not use more than 1 0-element MOE (109) to prevent over estimation of the error. Due to the complexity of the calculations, some percentage MOEs cannot be calculated (these are set to null in the summary-level MOE tables).

The name for table 'ACS10INCTRMOE' was added as a prefix to all field names imported from that table. Be sure to turn off 'Show Field Aliases' to see complete field names in the Attribute Table of this feature layer. This can be done in the 'Table Options' drop-down menu in the Attribute Table or with key sequence '[CTRL]+[SHIFT]+N'. Due to database restrictions, the prefix may have been abbreviated if the field name exceded the maximum allowed characters.

Graph and download economic data for Median Household Income in the United States (MEHOINUSA646N) from 1984 to 2024 about households, median, income, and USA.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

This dataset has been clipped to the Broward County extent from the Census dataset available through the United States Department of Treasury Community Development Financial Institutions (CDFI) Fund.

OPPORTUNITY ZONES RESOURCES: downloaded from Census : https://www.cdfifund.gov/Pages/Opportunity-Zones.aspx

The authority to implement IRC 1400Z-1 and 1400Z-2 has been delegated to the IRS. The CDFI Fund is supporting the IRS with the Opportunity Zone nomination and designation process under IRC 1400Z-1 only. In addition to an initial set of proposed regulations and guidance on how the Qualified Opportunity Zone (QOZ) tax benefits under IRC 1400Z-2 (including the certification of Qualified Opportunity Funds (QOFs) and eligible investments in QOZs) will be administered, Treasury and IRS have issued a second set of proposed regulations relating to gains that may be deferred as a result of a taxpayer's investment in a QOF, special rules for an investment in a QOF held by a taxpayer for at least 10 years, and updates to portions of previously proposed regulations under section 1400Z-2 to address various issues, including: the definition of “substantially all.” You may submit comments on the proposed regulations electronically via the Federal Rulemaking Portal at www.regulations.gov (IRS REG-115420-18 or IRS REG 120186-18).Concurrent with the second set of proposed regulations, Treasury and IRS published a request for information (RFI), asking for detailed comments regarding ways to assess QOF investments including asset class, identification of Qualified Opportunity Zones and the impact and outcomes on those Qualified Opportunity Zones. You may submit comments on the RIF electronically via the Federal Rulemaking Portal at www.regulations.gov (TREAS-DO-2019-0004). IRS also has posted a list of Frequently Asked Questions about Opportunity Zones on the irs.gov Tax Reform pages. You will want to monitor the Tax Reform page at the IRS website for additional Opportunity Zone information and other Tax Reform information. For any other questions, please call (800) 829-1040.

List of designated Qualified Opportunity Zones (QOZs): This spreadsheet was updated December 14, 2018, to include two additional census tracts in Puerto Rico that, based on 2012-2016 American Community Survey data, meet the statutory criteria for a Low-Income Community and are deemed as designated QOZs. Based on nominations of eligible census tracts by the Chief Executive Officers of each State, Treasury has completed its designation of Qualified Opportunity Zones. Each State nominated the maximum number of eligible tracts, per statute, and these designations are final. The statute and legislative history of the Opportunity Zone designations, under IRC § 1400Z, do not contemplate an opportunity for additional or revised designations after the maximum number of zones allowable have been designated in a State or Territory. Based on IRC 1400Z-1, designations are based upon the boundaries of the tract at the time of the designation in 2018, and do not change over the period of the designation, even if the boundaries of an individual census tract are redefined in future Census releases.

Source: United States Census Bureau

Effective Date:

Last Update:12/14/2018

Update Cycle: As needed, Census occurs once every decade

Abstract

The 1996 Papua New Guinea household survey is designed to measure the living standards of a random sample of PNG households. As well as looking at the purchases, own-production, gift giving/receiving and sales activities of households over a short period (usually 14 days), the survey also collects information on education, health, nutrition, housing conditions and agricultural activities. The survey also collects information on community level access to services for education, health, transport and communication, and on the price levels in each community so that the cost of living can be measured.

There are many uses of the data that the survey collects, but one main aim is for the results to help government, aid agencies and donors have a better picture of living conditions in all areas of PNG so that they can develop policies and projects that help to alleviate poverty. In addition, the survey will provide a socio-economic profile of Papua New Guinea, describing the access that the population has to agricultural, educational, health and transportation services, their participation in various economic activities, and household consumption patterns.

The survey is nationwide and the same questionnaire is being used in all parts of the country, including the urban areas. This fact can be pointed out if households find that some of the questions are irrelevant for their own living circumstances: there are at least some Papua New Guinean households for which the questions will be relevant and it is only by asking everyone the same questions that living standards can be compared.

Geographic coverage

The survey covers all provinces except Noth Solomons.

Analysis unit

• Household
• Individual
• Community

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Listing Form and Selection of the Sample Listing of households is the first job to be done after the team has settled in and completed the introductions to the community. Listing is best done by the whole team working together. This way they all get to know the community and its lay-out. However, if the census unit is too large this wastes too much time. So before beginning asks how many households there are, very roughly, in the census unit (noting that teams are supplied with the number of households that were there in the 1990 census). If the answer is 80 or more, divide the team into two and have each half-team work on one sector of the community/village. See the section below on what to do when the listing work is divided up.

If the census unit is a "line-up point" that does not correspond to any single village or community the number of households will often exceed 200 and frequently they are also quite dispersed. In this case it is not practical to attempt to list the whole census unit, so a decision is made in advance to split the census unit into smaller areas (perhaps groupings of clans). First, a local informant must communicate the boundaries of the census unit and for natural or administrative sub-units with the larger census unit (such as hamlets; or canyons/valleys). The sub-units should be big enough to allow for the selection of a set of households (about 30 or more), but should not be so large that excessive transport time will be needed each day just to find the household. Once the subunit is defined, its boundaries should be clearly described. Then one of the smaller units is randomly selected and the procedures outlined above are then followed to complete the listing. Note: only one of the sub-units are listed, sample chosen, and interviews undertaken.

The most important thing in the listing is to be sure that you list all the households and only the households belonging to the named village or census unit (or subset of the census unit if it is a line-up point). In rural areas, explain to village leaders at the beginning: "We have to write down all the households belonging to (Name) village." In case of doubt, always ask: "Does this household belong to (Name) village?" In the towns, the selected area is shown on a map. Check that the address where you are listing is within the same area shown.

Also explain: "We only write down the name of the head of household. When we have the list of all the households, we will select 12 by chance, for interview."

Procedure for Listing The listing team walks around in every part of the village, accompanied by a guide who is a member of the village. If possible, find a person who conducted the 1990 Census in this community or someone with similar knowledge of the community and ask them to be your guide. Make sure you go to all parts of the village, including outlying hamlets. In hamlets, on in any place far from the centre, always check: "Do these people belong to (Name) village?"

In every part of the village, ask the guide about every house: "Who lives in this house? What is the name of the household head?" Note that you do not have to visit every household. At best, you just need to see each house but you do not need to go inside it or talk to anyone who lives there. Even the rule of seeing each house may be relaxed if there are far away household for which good information can be provided by the guide.

Enter the names of household heads in the lines of the listing form. One line is used for each household. As the lines are numbered, the procedure gives a number to each household. When you come to the last house, check with the guide: "Are you sure we have seen all the houses in the village?"

NOTE: It does not matter in what order you list the households as long as they are all listed. After the listing is complete, check that all lines are numbered consecutively with no gaps, from start to finish. The number on the last line should be exactly the number of households listed.

Note: If the list is long (say more than 30 households) interviewer may encounter difficulties when looking for their selected household. One useful way to avoid this is to show the approximately the place in the list here certain landmarks come. This can be done by writing in the margin, CHURCH or STORE or whatever. You can also indicate where the lister started in a hamlet, for example.

Sample Selection The sampling work is done by the supervisor. The first steps are done at the foot of the first page of the listing form. The steps to be taken are as follows:

1. Fill in the numbers asked for at the foot of the last listing page, as follows:
2. M: enter the total number of households listed (same as last household number shown).
3. Interval L: calculate (M / 15) to the nearest whole number.
4. R: This is a random number with 3-digit decimals between 0.000 and 0.999.

5. MR: multiply M by R and round to the nearest whole number. (If decimal 0.5, round up).

6. MR gives the 1st selection. (Exception: If MR=0, L gives the first selection.) Enter S against this line in the selection column of the list.

7. Count down the list, beginning after the 1st selection, a distance of L lines to get the 2nd selection, then another L to get the 3rd, etc. When you come to the bottom of the list, jump back to the top as if the list were circular. Stop after the 15th selection. Mark the 13th, 14th, and 15th selections "RES" (for reserve). Mark the 1st - 12th selection "S" (for selection).

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1996 Papua New Guinea Household Survey questionnaire consists of three basic parts:

Household questionnaire first visit: asks a series of questions about the household, discovering who lives there, what they do, their characteristics, where they live, and a little about what kinds of things they consume. This questionnaire consists of the following sections. - Section 1. Household Roster - Section 2. Education - Section 3. Income Sources - Section 4. Health - Section 5. Foods in the Diet - Section 6. Housing Conditions - Section 7. Agricultural Assets, Inputs and Services - Section 8. Anthropometrics - Section 9. Household Stocks

Consumption recall (second visit questionnaire): is focused primarily on assessing the household's expenditure, gift giving and recieving, production, and level of wealth. The information in the first and second visits will provide information that can determine the household's level of consumption, nutrition, degree of food security, and ways in which it organizes its income earning activities. This questionnaire consists of the following sections. - Section 1. Purchases of Food - Section 2. Other Frequent Purchases - Section 3. Own-production of Food - Section 4. Gifts Received: Food and Frequent Purchases (START) - Section 5. Annual Expenses and Gifts - Section 6. Inventory of Durable Goods - Section 7. Inward Transfers of Money - Section 8. Outward Transfers of Money - Section 9. Prices - Section 10. Repeat of Anthropometric Measurements - Section 11. Quality of Life

Community Questionnaire: which is completed by the interview team in consultation with community leaders. This questionnaire also includes market price surveys that are carried out by the team when they are working in the community. Associated with this is a listing of all households in the community, which has to be done prior to the selection of the 12 households. This questionnaire consists of the following sections. - Section A. Listing of Community Assets - Section B. Education - Section C. Health - Section D. Town or Government Station - Section E: Transport and Communications - Section F. Prices - Section G. Changes in Economic Activity, Infrastructure, and Services

Abstract

Overview of the Census The National Population and Housing Census 2024 was conducted in line with international best practices and guided by the need to produce accurate, relevant, and timely data. Covering all households and individuals across the country, this census marks a significant milestone in Uganda’s journey towards data-driven development. The specific objectives of the NPHC 2024 were: i) To ascertain size, structure and distribution of the population ii) To gather data on housing conditions and access to basic services iii) To monitor changes in key social and economic indicators since the previous Census iv) To update census maps and lists of Enumeration Areas for effective execution of the census, construction of efficient area sampling frames for subsequent surveys and geographical maps at the lowest level. v) To establish the statistical infrastructure for future operations at the lowest Local Government level. vi) To further enhance the capacity of UBOS staff to undertake future censuses and large-scale sample surveys. vii) Inform policies and programmes aimed at improving the quality of life of all Ugandans

Uses of National Population and Housing Censuses The findings of the 2024 Census will be instrumental in shaping Uganda’s development agenda. They provide a basis for: a) Planning: Facilitating evidence based National and Local Government planning processes. b) Resource Allocation: Enabling equitable distribution of resources across programmes and Local Governments. c) Program Design: Informing interventions in social services such as health, education, infrastructure, and housing, to mention a few. d) Monitoring Progress: Tracking Uganda’s advancements towards achieving socio-economic transformation as envisioned in Vision 2040, the National Development Plans, as well as regional, continental and global development initiatives.

Key Findings 1. Population Size and Growth: Uganda’s population as of May 2024 was 45,905,417 persons, reflecting an average annual growth rate of 2.9 percent since the last Census in 2014. 2. Demographic Composition: A half of the population is under the age of 18. Five in every one hundred persons are aged 60 and above. 3. Housing and Living Conditions: i) Eight in ten (81.1%) households have access to improved water sources ii) Slightly over a half (53.4%) of households have access to electricity (25.3% from grid and 28.1% from solar). 4. Literacy: Seventy four percent of persons aged 10 and above were able to read and write meaningfully in any language. 5. Well-being and Health: i) One third (33.1%) of the households were in subsistence economy. ii) Twelve percent of persons aged 10 and above had experienced at least some form of probable general psychological distress. 6. Labour Force (15 years and above): i) The working age group was 25,494,490 persons (57.4% of the population). ii) The unemployment rate was 12.3 percent. iii) The share of Youth (15-24 years) Not in Employment, Education or Training (NEET) was 4,001,528 persons (42.6%)

Geographic coverage

National coverage

Analysis unit

The units of analysis for the NPHC 2024 include; - Individuals - Households - Housing

Universe

The census was done on a de facto basis i.e. every person was enumerated where he/she spent the Census Reference Night of 9th May 2024.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaires for the National Population and Housing Census 2024 structured and included: - HOUSEHOLD: Characteristics of household members, housing and household characteristics, agriculture, deaths in the household, and information on physical address.

-INSTITUTION: Characteristics of institution members.

Abstract

The 2010 Saint Lucia Population and Housing Census is conducted by the Central Statistical Office staff. The island-nation of Saint Lucia recorded an overall household population increase of 5 percent from May 2001 to May 2010 based on estimates derived from a complete enumeration of the population of Saint Lucia during the conduct of the recently completed 2010 Population and Housing Census. Saint Lucia's total resident population as at midnight on Census Day, the 10th May 2010 stood at 166,526 persons. Saint Lucia's total population including non-resident persons was estimated to be 173,720, the total number of non-resident persons was 7,194. The preliminary count of Saint Lucia's enumerated population was 151,864 persons reflecting a response rate to the census of 92%. The total resident population of St. Lucia is comprised of 82,926 males and 83,600 females. Out of this sum, there were 165,595 individuals residing in private households, 931 persons living in institutions.

A modern population and housing census is the process of collecting, compiling, analyzing, and publishing demographic, socio-economic, and environmental data pertaining to all persons in a country and the national housing stock at a specified time. A census is a form of national stocktaking. Since the census is a complete count of the population and living quarters, it provides detailed benchmark data on the size of the population, age structure, educational attainment, economic activity, disability, housing, and household amenities as well as other major socio-economic characteristics.

Geographic coverage

National Coverage includes all Administrative Districts and Political Constituencies

Analysis unit

• Households,
• Individuals.

Universe

The Census covered all de jure household members (usual residents of St Lucia based on the six month criteria). The fertility of all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household. The Census also collected data on dwelling and housing conditions of all resident householders. In the Census Visitation record all de jure household members were counted by sex, in addition, persons present in St Lucia at the time of the census who were not usual residents were also counted to produce the de facto population of St Lucia on census day May 10, 2010.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires were bound together into booklets. Each booklet contained a cover page (for identification and the Record of Visits), page 2 for Listing the names of the members of the Household and for any comments needed concerning any member of the household or any part of the enumeration. NATIONAL ARCHIVES, INTERNATIONAL MIGRATION and HOUSING spread over pages 3 to 5.

After these sections, three individual questionnaires (6 pages each) complete the booklet. These booklets provide for three (3) persons and are to be used for households consisting of three (3) or fewer persons. If the household comprises more than three persons, the main booklet plus the number of additional person questionnaires were required. For example,

For a 1, 2, 3-person household, use one booklet;

For a 4-person household, use one booklet plus one additional person questionnaire.

For a 5-person household, use one booklet plus two additional person questionnaires and so on.

The ED Number and the Household number contained on the front cover page of the main questionnaire was transferred to the top of the front page of EVERY person questionnaire whether or not it was an individual questionnaire within the main booklet or whether it was an individual questionnaire applicable to a household with more than three persons.

STRUCTURE OF THE INDIVIDUAL QUESTIONNAIRE

The individual questionnaire starts at Section 3. The questions are divided into eleven groups, each having a central theme and given a section number as follows:

Section 3: Personal Characteristics (for all persons) Section 4: Birthplace & Residence (for all persons) Section 5: Disability (for all persons) Section 6: Health (for all persons) Section 7: Education and Internet Access (for all persons) Section 8: Professional, Technical & Vocational Training (for persons 15 years and over) Section 9: Economic Activity (for persons 15 years and over) Section 10: Income and Livelihood (for females 15 years and over) Section 11: Marital Status and Union Status (for persons 15 years and over) Section 12: Fertility (for persons 15 years and over) Section 13: Where Spent Census Night (for all persons)

Cleaning operations

Data editing took place at a number of stages throughout the processing, including (See External Resource for more information on this item):

a) Field Editing by interviewers and field supervisors The guidelines for the conduct of these edits were laid out in PART IX: Checking Your Questionnaires for Errors in the Enumerators Manual. These instructions are repeated in the supervisors manual and also stated in the contract for payment of enumerators and supervisors. A number of elements of the edits outlined formed the basis for the payment of enumerators and supervisors.

b) Office editing and questionnaire re-numbering When a full set of questionnaires from a completed ED was recieved by the office, persons assigned as census evaluators had the responsibility to review the content of each Questionnaire to check for completeness. They were required to perform checks on the questionnaires and the visitation records for the key geographic variables and perform other checks in line with the requirements of a Census Evaluation form which laid out quality standards for the approval of a completed ED for payment. The Census evaluation form is provided as an external resource for information.

c) Data Capture, Editing and Coding during scanning and data verification The data was captured using TELEform V10.4.1 and the data from the forms was exported to a SQL Server 2005 database as was all other census related information captured on forms, such as the census 2010 Evaluation form, referred to previously, the census visitation record etc.

The names of the SQL Server Databases are as follows: 1) Census2010 containing Tables: Census2010Persons, Census2010House, Census2010Visit, Census2010Evaluation, Census2010ApplicationForms, CensusTestScores, Census2010Institutions 2) Census2010_Validated contained data which was validated on several metrics outline in a VBA program built into the TELEform v10.4 software used to capture the data after scanning.

The correction of geographic variables was completed during this process. The scanner operator would manually enter the ED code for the batch being scanned, he would also enter the first and last household for the batch manually. Later the verifier would independantly verify the ED and the household number entered by the enumerator against the values entered by the scanner operator to ensure that they were either the same as in the case of the ED number or within the range of households expected in the batch as in the case of the household number. This was done using VBA validation code written within the TELEform 10.4.1 software used for the scanning and capture of the data from the Census.

Computer Assisted Coding was built into the TELEform template, this method assisted the enumerator using keywords to identify the code for the entry of the appropriate settlement, industry or occupation code. A listing of the codes used is attached to this document as an external resource. Occupation codes are in the international format of ISCO-08 while the industry code applied is based on ISIC Rev4.

d) Structure checking and completeness in Foxpro

The data was exported to MS Access and then on to MS Foxpro where some basic editing was done.

1) This involved the conversion of descriptions of settlement, ISCO and ISIC data collected in fields to codes 2) Standardizing the lenghts and format of all fields in the dataset in preparation for conversion to CSPRO ASCII data format 3) Transposing data on Migration, deaths, disability and births in the last 12 months to variables in the household and person files 4) Removal of blank and very incomplete records 5) Removal of all duplicates and the cleaning of all inconsistent records between the household and the person file. 6) Creation of CSPRO 4.0 compatible format data file for use in further editing and cleaning

e) Detailed variable level editing using CSPRO 4.0 and hotdecking Detailed programs were developed to clean census data on critical variables in the housing section of the questionnaire such as Type of Dwelling, household assets etc, demographic variables such as age, sex, education and economic activiity variables were cleaned in the first version of the CSPRO 4.0 *.bch program file developed. After the first version of the cleaning program was complete the Statistical Office published the Preliminary Census 2010 Report (Updated April 2010). The first version of this publication released in January contained only data on population counts from the census visitation records. The updated April 2010 Preliminary Census report contained information on all the main variables cleaned in the first version of the cleaning program. The CSPRO 4.0 program employed the use of many 3-dimensional hotdecking programs to correct for items not stated or recorded.

f) Checking of data files using the Tabulation Features of CSPRO 4.0 and SPSS 19 Crosstabulations of variables were used to identify inconsistent data and improve CSPRO 4.0 editing programs

Detailed documentation of

Abstract

The Census of Agriculture & Fisheries (AGC 2011) is a national government operation geared towards the collection and compilation of statistics in the agriculture sector of the country. The collected data will constitute the bases from which policymakers and planners will formulate plans for the country's development.

The first Census of Agriculture (CoA) in the Cook Islands was conducted in 1988 and the second in 2000. Both censuses were supported technically by FAO. The Cook Islands also has a long history of population census taking at 5-yearly intervals in years ending in 1 and 6. Traditionally the Census of Population and Dwellings (CoPD) has included questions on agricultural activity at the household level, types of crops grown, livestock numbers, farm machinery and involvement in fishing and pearl farming activities. Section 3 of this report looks at data collected in the CoPD 2011 related to agricultural, fishing and pearl farming activities

Geographic coverage

National coverage.

Analysis unit

Household; Holding; Parcel; Individual.

Universe

The census covered all households, agricultural operators, agricultural establishments, fishing operators and pearl farmers.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

The census of population and dwellings had 4 categories of agricultural activity, namely: subsistence only, commercial only, subsistence and commercial and no agriculture. For those engaged in agricultural activity a further breakdown was collected, namely: vegetables, fruit, flowers and other. The census of agriculture also had 4 categories but for crop growing only, namely, non-agricultural, minor agricultural, subsistence and commercial. The differences in these classifications and the types of agriculture included make comparisons difficult, however, it is useful to evaluate the two sets of data and draw conclusions as to the extent of agricultural activity in the cook islands from these two sources.

The questionnaires used for the census of agriculture 2000 and the census of population and dwellings 2006, related to agriculture, were reviewed and efforts made to avoid duplication. In particular, the question on the numbers of livestock kept by the household was dropped from the census of population and dwellings as this data was being collected in the census of agriculture. Likewise, information on machinery and equipment was dropped from the census of agriculture as this was being collected in the census of population and dwelling. Questions on the extent of involvement in agricultural activity at the household level were maintained in both censuses as was the extent of involvement in fishing and pearl farming. This provided a useful coverage check for the census of agriculture, in particular, although it was noted that there were definitional differences between the two censuses especially related to flower cultivation which was considered an agricultural activity in the census of population and dwellings but not in the census of agriculture. At the individual level, data on labour inputs was recorded in the census of agriculture by age and sex but other data at the individual level has then to be obtained through linkages to the census of population and dwellings through the person and household number.

The household questionnaire was administered in each household, which collected various information on levels of agricultural activity, holdings detail (including name of operator, total area, number of separate parcels, location), crops currently growing and/or harvested (including crops currently growing, total area, number of plants,crops planted and/or harvested, total area, number of plants), proportion of income from agriculture, loans for agriculture purposes, fertilizers, agricultural chemicals, improved varieties, other selected activities during the last 12 months (including bee keeping, hydroponic, floriculture, handicrafts), traditional methods on food storage and planting, travelling with locally grown food, water usage

In addition to a household questionnaire, questions were administered in each household for holding which collected various information on holding iidentification, parcel details during the lasts 12 months (including location, area, land tenure, land use, months used), scattered plants/trees (including number of plants), labour input for persons 15 years and over working during the last month (including sex, age, status, type, average hours worked per week, wages per month, benefits and other paid job)

In addition to a holding questionnaire, questions were administered for parcels which collected various information (during the last 12 months) on plot details (including proportion to parcel area, crops grown, method of planting, number of plants and proportion for sale), crops planted and harvested (including area harvested, number of plants and proportion for sale)

In addition to a household questionnaire, questions were administered in each household for livestock which collected various information on type and number of livestock, type of operation, nature of disposal during the last 12 months (including kind of livestock, number disposed (including home use, feast/gifts, sold, slaughtered, live)

In addition to a household questionnaire, questions were administered in each household for fishing which collected various information on household members engaged, main purpose of fishing activity, household members (including average hours spent per week), details of fishing activities (including forms of fishing, number of people fishing, location, average number of fishing trips, average hours per fishing trip), boat details (including type of boat, length, engine), proportion of fish caught/collected and sold, proportion consumed

In addition to a household questionnaire, questions were administered in each household for pearl farming which collected various information (during the last 12 months) on farming details (including farm lines, spat collector lines, spat details, number of farm shells, labour input (including person number, sex, age, status, type, average hours worked per week, wages per month, benefits received, other paid job) , boat operation (including times used per week), type of equipment and facility, number of times per week, number owned, hired, borrowed), shelling details, proportion of income, loan details

The questionnnaires, that were developed in English, contain was divided into 5 forms: -Household Form: Levels of agricultural activity, List of agricultural holdings, Crops, Income from agricultural activities, Loans, Fertilizers, Other relevant questions. -Holding Form: Parcel details, Scattered plants/trees, Labour inputs. -Parcel Form: Number of sepearate plots, Plot details, Crops. -Livestock Form: Livestock details, Type of operation, Nature of disposal. -Fishing & Pearl Farming Form: Fisheries activities details, Pearl farm information, Labour inputs, Boats and other equipment used, Other relevant information.

Cleaning operations

The length and complexity of the census of agriculture forms made the exercise much more time consuming and virtually all records had to be edited. The data capture and data cleaning exercise for the census of agriculture took the best part of 12 months, including the adjustments following the re-enumeration of Aitutaki. Tabulation also proved to be challenging because of the need for considerable internal computation of areas and numbers of plants. The final database was then split up into a number of smaller databases designed for each set of tables. The tabulation was done using Microsoft EXCEL and ACCESS

In interpreting the results of the census of agriculture, account needs to be taken of the fact that households classified as having no agricultural or fishing activities in the census of population and dwellings were excluded from the census of agriculture, especially on Rarotonga. Other definitional differences between the two censuses should also be noted. The census of population and dwellings defined agricultural activity as crops, livestock and floriculture whereas the ensus of agriculture definition was primarily crops. Livestock and poultry raising was treated separately in the census of agriculture and flower growing was only included in the census of agriculture if it was a commercial activity or was carried out in conjunction with food crop activities.

Abstract

Censuses are principal means of collecting basic population and housing statistics required for social and economic development, policy interventions, their implementation and evaluation.The census plays an essential role in public administration. The results are used to ensure: • equity in distribution of government services • distributing and allocating government funds among various regions and districts for education and health services • delineating electoral districts at national and local levels, and • measuring the impact of industrial development, to name a few The census also provides the benchmark for all surveys conducted by the national statistical office. Without the sampling frame derived from the census, the national statistical system would face difficulties in providing reliable official statistics for use by government and the public. Census also provides information on small areas and population groups with minimum sampling errors. This is important, for example, in planning the location of a school or clinic. Census information is also invaluable for use in the private sector for activities such as business planning and market analyses. The information is used as a benchmark in research and analysis.

Census 2011 was the third democratic census to be conducted in South Africa. Census 2011 specific objectives included: - To provide statistics on population, demographic, social, economic and housing characteristics; - To provide a base for the selection of a new sampling frame; - To provide data at lowest geographical level; and - To provide a primary base for the mid-year projections.

Geographic coverage

National

Analysis unit

Households, Individuals

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

About the Questionnaire : Much emphasis has been placed on the need for a population census to help government direct its development programmes, but less has been written about how the census questionnaire is compiled. The main focus of a population and housing census is to take stock and produce a total count of the population without omission or duplication. Another major focus is to be able to provide accurate demographic and socio-economic characteristics pertaining to each individual enumerated. Apart from individuals, the focus is on collecting accurate data on housing characteristics and services.A population and housing census provides data needed to facilitate informed decision-making as far as policy formulation and implementation are concerned, as well as to monitor and evaluate their programmes at the smallest area level possible. It is therefore important that Statistics South Africa collects statistical data that comply with the United Nations recommendations and other relevant stakeholder needs.

The United Nations underscores the following factors in determining the selection of topics to be investigated in population censuses: a) The needs of a broad range of data users in the country; b) Achievement of the maximum degree of international comparability, both within regions and on a worldwide basis; c) The probable willingness and ability of the public to give adequate information on the topics; and d) The total national resources available for conducting a census.

In addition, the UN stipulates that census-takers should avoid collecting information that is no longer required simply because it was traditionally collected in the past, but rather focus on key demographic, social and socio-economic variables.It becomes necessary, therefore, in consultation with a broad range of users of census data, to review periodically the topics traditionally investigated and to re-evaluate the need for the series to which they contribute, particularly in the light of new data needs and alternative data sources that may have become available for investigating topics formerly covered in the population census. It was against this background that Statistics South Africa conducted user consultations in 2008 after the release of some of the Community Survey products. However, some groundwork in relation to core questions recommended by all countries in Africa has been done. In line with users' meetings, the crucial demands of the Millennium Development Goals (MDGs) should also be met. It is also imperative that Stats SA meet the demands of the users that require small area data.

Accuracy of data depends on a well-designed questionnaire that is short and to the point. The interview to complete the questionnaire should not take longer than 18 minutes per household. Accuracy also depends on the diligence of the enumerator and honesty of the respondent.On the other hand, disadvantaged populations, owing to their small numbers, are best covered in the census and not in household sample surveys.Variables such as employment/unemployment, religion, income, and language are more accurately covered in household surveys than in censuses.Users'/stakeholders' input in terms of providing information in the planning phase of the census is crucial in making it a success. However, the information provided should be within the scope of the census.

1. The Household Questionnaire is divided into the following sections:
2. Household identification particulars

3. Individual particulars Section A: Demographics Section B: Migration Section C: General Health and Functioning Section D: Parental Survival and Income Section E: Education Section F: Employment Section G: Fertility (Women 12-50 Years Listed) Section H: Housing, Household Goods and Services and Agricultural Activities Section I: Mortality in the Last 12 Months The Household Questionnaire is available in Afrikaans; English; isiZulu; IsiNdebele; Sepedi; SeSotho; SiSwati;Tshivenda;Xitsonga

4. The Transient and Tourist Hotel Questionnaire (English) is divided into the following sections:

5. Name, Age, Gender, Date of Birth, Marital Status, Population Group, Country of birth, Citizenship, Province.

6. The Questionnaire for Institutions (English) is divided into the following sections:

7. Particulars of the institution

8. Availability of piped water for the institution

9. Main source of water for domestic use

10. Main type of toilet facility

11. Type of energy/fuel used for cooking, heating and lighting at the institution

12. Disposal of refuse or rubbish

13. Asset ownership (TV, Radio, Landline telephone, Refrigerator, Internet facilities)

14. List of persons in the institution on census night (name, date of birth, sex, population group, marital status, barcode number)

15. The Post Enumeration Survey Questionnaire (English)

These questionnaires are provided as external resources.

Cleaning operations

Data editing and validation system The execution of each phase of Census operations introduces some form of errors in Census data. Despite quality assurance methodologies embedded in all the phases; data collection, data capturing (both manual and automated), coding, and editing, a number of errors creep in and distort the collected information. To promote consistency and improve on data quality, editing is a paramount phase in identifying and minimising errors such as invalid values, inconsistent entries or unknown/missing values. The editing process for Census 2011 was based on defined rules (specifications).

The editing of Census 2011 data involved a number of sequential processes: selection of members of the editing team, review of Census 2001 and 2007 Community Survey editing specifications, development of editing specifications for the Census 2011 pre-tests (2009 pilot and 2010 Dress Rehearsal), development of firewall editing specifications and finalisation of specifications for the main Census.

Editing team The Census 2011 editing team was drawn from various divisions of the organisation based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors. Census 2011 editing team was drawn from various divisions of the organization based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors.

The Census 2011 questionnaire was very complex, characterised by many sections, interlinked questions and skipping instructions. Editing of such complex, interlinked data items required application of a combination of editing techniques. Errors relating to structure were resolved using structural query language (SQL) in Oracle dataset. CSPro software was used to resolve content related errors. The strategy used for Census 2011 data editing was implementation of automated error detection and correction with minimal changes. Combinations of logical and dynamic imputation/editing were used. Logical imputations were preferred, and in many cases substantial effort was undertaken to deduce a consistent value based on the rest of the household’s information. To profile the extent of changes in the dataset and assess the effects of imputation, a set of imputation flags are included in the edited dataset. Imputation flags values include the following: 0 no imputation was performed; raw data were preserved 1 Logical editing was performed, raw data were blank 2 logical editing was performed, raw data were not blank 3 hot-deck imputation was performed, raw data were blank 4 hot-deck imputation was performed, raw data were not blank

Data appraisal

Independent monitoring and evaluation of Census field activities Independent monitoring of the Census 2011 field activities was carried out by a team of 31 professionals and 381 Monitoring

Graph and download economic data for New Privately-Owned Housing Units Started: Single-Family Units (HOUST1F) from Jan 1959 to Aug 2025 about housing starts, privately owned, 1-unit structures, family, housing, and USA.

Abstract

The 2009 Census falls within the 2010 Round of Pacific Census, ten years after the 1999 census.

The results of the 2009 census will be required to:

a. help produce high-quality information for planning, decision-making, and monitoring of development progress in Solomon Islands. This implies very heavy data requirements and these requirements are continuously increasing, particularly towards development planning, implementation monitoring and evaluation of Government policies outlined in NERDEP and the current Medium Term Development Strategies.

b. The data from the Census will also be used for monitoring the achievement of the Millennium Development Goals (MDG's) and other goals included in the International Conference for Population & Development (ICPD).

c. check whether the population policies, which were put in place after the 1986 census on the basis of 1976-86 population trends and then as reviewed in the early 2000s in respect of the 1999 population trends, proved effective, and

d. Establish a new benchmark and a new set of post-1999 population trends on which to base a reconsideration of existing (population) policies in the framework of sustained and sustainable development.

e. Also, the results of this census will help facilitate updating of constituencies in preparation to the 2010 national election of Solomon Islands.

f. Further to these, the results of the census will provide a sample Frame from which further household capability surveys which include a household income expenditure in 2010/2011, a second demographic and health survey (DHS) 2011/2012 and a Labour Force Survey before the next census can be undertaken.

g. The 2009 census will also provide the much needed village level data on population, resources and infrastructure for government's bottom-up approach development policy initiative.

Accepting the notion that a new census is required and that a number of overseas aid organisations will be able to support the government on an undertaking similar to the 1999 census, the following points are considered in more detail in this project proposal.

It is recommended that the present census interval should not exceed ten years and that the same month should be selected in 2009, for the period of enumeration as in 1999, mainly to ensure that seasonal factors would not reduce the comparability of the information provided by the two censuses. As a result of this recommendation, 22nd November 2009 is therefore proposed as the new census date. This date will be formally announced by the Prime Minister in line with the Census Act.

For making current administrative decisions and prepare longer term socio-economic development policies governments and private organisations need reliable up-to-date knowledge about available natural and human resources. In a country like Solomon Islands one of the most important statistical systems for obtaining the required socio-economic information is the population census. This does not only provide a numerical description of the population at a given census date - through comparison with previous census results - but also of the ongoing trends in a sustained and sustainable development of certain population characteristics such as changes in population growth, age composition, direction of mobility and levels of urbanisation, economic activities and educational status. Such knowledge may allow the development planner to devise policies that will stem the flow of trends considered not in line with development aims. Alternatively, trends considered fitting can be identified and fostered by the introduction of appropriate policies. The success thereof can then be assessed when a next census is held some ten years later.

Geographic coverage

The 2009 Population and Housing Census Covers 100% of geography as in Urban and Rural Areas for the Entire Country :

The Solomon Islands as a whole by:

• 10 Provinces
• Constituencies
• Wards
• Enumeration Areas
• Household Level

Analysis unit

1. Population ( Urban and Rural )
2. Household ( Urban and Rural )
3. Provincial records
4. National Records
5. Geography

Universe

The National Population and Housing Census 2009,covers the entire Population,the ones in the Hotels,Motels,Ships which was collected when all ship arrived at wharf during the Census times. It covers all overseas people living in and aorund Solomon Islands,Urban and Rural,excluded the Diplomats. In overroll:- This is any individual member of the household or institution who is present on the census night and is therefore counted in the census. This includes every young and old, male of female, expatriates or residents, tourist and locals alike.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Census - Not applicable for complete enumeration survey

This section only apply for Sample Surveys.

Mode of data collection

Face-to-face [f2f]

Research instrument

1. QUESTIONNAIRE AND SCANNING

The need to set up the questionnaire in terms of suitability for local printing have done, using a software package called in-design, or whatever is most appropriate, which will then allow “optimisation ” for scanning with check boxes, drop-out colours (colours which are then filtered out by the scanner) etc. It is important that the questions are laid out correctly to make sure the results of the scan are possible and legible and eligible or recorded. Prior to the pilot census, the questionnaire needs to be finalised and come up with something everyone is happy with, finalise it and then make sure it works (if questions/formatting needs amendments as a result of the pilot, such changes will of course be done).

The questionnaire was finalised and a reliable printer to print the questionnaires was sought in advance through the tender bidding process. There are a whole series of things the Census office need to check here to make sure that the job gets done to a sufficient standard and that the scanning works well (good quality machines, paper, ink, air conditioned operating environment etc). There was no printing company in Honiara who can do this thus the printing done in Australia

In addition the questionnaire develop and were all in English language as people normally understand the english reading than the Solomons pidgin.The quetionnaire was design in Adobe Illustrator as to make sure the lines and writtings all well linned and parallel to what had written.Hence the census form have to have the right color which the scannning has to read and can easily collect the characters and values. As such the census forms had been well protected while in field and properly manage in a way which the forms will not distroyed easily by rain or sea. Hence,the census questionnaire covers Households and Housing.All Persons and GPS,more detailed in Scope section.

Cleaning operations

Data editing took place at a number of stages throughout the processing, including:

a) After Scanning data exported to CSPro4.0 edited done by data proccessing officer. b) Secondly the Data proccessing officer pass the data to Data verifiers c) Structure checking and completeness by verifiers in terms of wrong written numbers and spellings

d) Batch editing: - Variables out of range - Fertility Questions - Coding and Value sets - Editing of Variables..eg.age,date of birth and etc.

Detailed documentation of the editing of data can be found in the "Data processing guidelines" document provided as an external resource.

Sampling error estimates

Not apply for Census

Data appraisal

The 2009 Census data was involved people from SPC and SINSO for checking and assisting in terms of cleaning,and verifying.After Census dataset cleaned on 19/09/2011,Census dataset has checked my running tabulation on Male and female by villages,and checking Villages were all coded and no village coded with zero "0".mean makesure all villages has values and makesure the villages with same name coded with unique code where they located by their on provinces.

Abstract

The Government of Liberia and its development partners recognized agriculture as a pivotal sector in fostering economic growth, reducing poverty, and achieving food security. Since the post-war period (insert dates) , the government in collaboration with development partners, has made substantial investments to develop and expand the agriculture sector. Over the years, policymakers and data users in the agriculture sector have experienced significant challenges in obtaining the data needed to monitor and evaluate these interventions and make informed decisions on new interventions. To address these challenges, the Liberia Institute of Statistics and Geo-Information Services (LISGIS) and the Ministry of Agriculture (MoA) conducted several ad hoc agricultural surveys. While valuable, these surveys have often been limited in scope and unable to provide the comprehensive data needed for effective policymaking and planning. To support the sector more robustly, the government decided to undertake a comprehensive agricultural census:the Liberia Agriculture Census 2024, the second agricultural census in Liberia since 1971 and the first to be conducted digitally, aimed to collect structural and reliable data on various aspects of the agricultural sector.

The main objectives of the LAC-2024 was to:

· Reduce the existing data gap in Liberia's agriculture sector.

· Provide comprehensive data on the agriculture sector for policy formulation and evaluation of existing programmes.

· Enable LISGIS to establish an agriculture master sampling frame for future agricultural surveys and research.

· Identify the structural changes in the agriculture sector over time.

· Provide information on crop, livestock, poultry, and aquaculture activities.

· Determine the size, composition, practices and related characteristics of Liberia's agricultural holdings.

· Generate disaggregated agriculture statistics.

· Provide statistics for advocacy on Liberia's agriculture sector.

· Identify agricultural practices and constraints at the community level.

To achieve these objectives, the LAC-2024 was designed to collect structural data at the household, non-household and community levels. The data provided a wealth of information on the state of agriculture in Liberia. This documentation provides information on how data was collected at the household level. The documentation also provides useful information on the household anonymized dataset.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The universe for the Liberia Agriculture Census 2024 household level data collection is all households in Liberia having at least one member engaged in agricultural activity during the 2022/2023 farming season.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The Liberia Agriculture Census 2024 (LAC-2024) was a sampled census conducted in all 15 counties of Liberia. The sampling frame used for the LAC-2024 is based on the 2022 National Population and Housing Census (2022-NPHC), conducted by the LISGIS. The sample design for the census was a stratified cluster sample with enumeration areas (EAs) as clusters and farming households as units of interest. In line with budget availability, a large sample of 4,800 EAs was considered for the LAC-2024. These EAs had a total of 269,652 agricultural households in the frame. The sample was allocated by strata (districts, urban/rural) proportional to the numbers of farming households in the frame. In total, about 78.8% of the sample was allocated to rural areas. The stratified sample of EAs was selected with a probability proportional to the number of farming households at EA level. A complete listing of all households (both agricultural and non-agricultural) was carried out in the selected EAs and detailed questions were addressed to all households that practiced agricultural activities during the 2022/2023 farming season. The results of the LAC-2024 are representative at the district level.

For more information on the LAC-2024 sampling methodology, see the methodology section of the Liberia Agriculture Census 2024 Household Report (available in the downloads tab).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The LAC-2024 employed three questionnaires: the Household Questionnaire, the Community Questionnaire and the Non-Household Questionnaire. These three questionnaires were based on the 50x2030 Initiative standard model questionnaires. The Liberia Agriculture Census Technical Working Group (LAC-TWG), comprising technical staff from LISGIS,Ministry of Agriculture (MOA), National Fishery and Aquaculture Authority (NaFAA), Cooperative Development Agency (CDA) and the Ministry of Internal Affairs (MIA) worked with technicians from the 50x2030 Initiative to adapt the questionnaires to Liberia's context and realities. Suggestions and inputs were solicited from various stakeholders representing government ministries, agencies and commissions(termed MACs by LISGIS), nongovernmental and international organizations as well as academic institutions researching agricultural issues. All questionnaires were finalized in English. Some questions in the questionnaires were translated into simple Liberian English, to ease administration. The household questionnaire included type of agricultural activities practiced, household members characteristics, housing conditions, hired labour practices, agricultural parcels and plots characteristics, types of crops and methods of crop cultivation, inputs, tools and equipment used, type and number of livestock and poultry. The household questionnaire was administered to the household head or an adult member of the household with knowledge of the household and its agricultural activities. The primary respondent (i.e., the household member that provided most of the information for the questionnaire or a given module, household member, or crop) sometimes varied across modules.

Cleaning operations

The data was edited using CSpro software, version 7.7.3. The appropriate edit rules were established by programmers and subject matter specialists at LISGIS and MOA. In a few cases, manual editing was applied to recode the “other specify” category. The SPSS software was used for this purpose.

Response rate

92.8%

This layer shows census tracts that meet the following definitions: Census tracts with median household incomes at or below 80 percent of the statewide median income or with median household incomes at or below the threshold designated as low income by the Department of Housing and Community Development’s list of state income limits adopted under Healthy and Safety Code section 50093 and/or Census tracts receiving the highest 25 percent of overall scores in CalEnviroScreen 4.0 or Census tracts lacking overall scores in CalEnviroScreen 4.0 due to data gaps, but receiving the highest 5 percent of CalEnviroScreen 4.0 cumulative population burden scores or Census tracts identified in the 2017 DAC designation as disadvantaged, regardless of their scores in CalEnviroScreen 4.0 or Lands under the control of federally recognized Tribes.

Tabular data that powers basic monitoring dashboards for the total population, housing and jobs for the City of Seattle. Each record represents the totals for each year since 2000 (and 1995) through the most recently available data. Includes the change from the previous year.