Abstract

Gallup Worldwide Research continually surveys residents in more than 150 countries, representing more than 98% of the world's adult population, using randomly selected, nationally representative samples. Gallup typically surveys 1,000 individuals in each country, using a standard set of core questions that has been translated into the major languages of the respective country. In some regions, supplemental questions are asked in addition to core questions. Face-to-face interviews are approximately 1 hour, while telephone interviews are about 30 minutes. In many countries, the survey is conducted once per year, and fieldwork is generally completed in two to four weeks. The Country Dataset Details spreadsheet displays each country's sample size, month/year of the data collection, mode of interviewing, languages employed, design effect, margin of error, and details about sample coverage.

Gallup is entirely responsible for the management, design, and control of Gallup Worldwide Research. For the past 70 years, Gallup has been committed to the principle that accurately collecting and disseminating the opinions and aspirations of people around the globe is vital to understanding our world. Gallup's mission is to provide information in an objective, reliable, and scientifically grounded manner. Gallup is not associated with any political orientation, party, or advocacy group and does not accept partisan entities as clients. Any individual, institution, or governmental agency may access the Gallup Worldwide Research regardless of nationality. The identities of clients and all surveyed respondents will remain confidential.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING AND DATA COLLECTION METHODOLOGY With some exceptions, all samples are probability based and nationally representative of the resident population aged 15 and older. The coverage area is the entire country including rural areas, and the sampling frame represents the entire civilian, non-institutionalized, aged 15 and older population of the entire country. Exceptions include areas where the safety of interviewing staff is threatened, scarcely populated islands in some countries, and areas that interviewers can reach only by foot, animal, or small boat.

Telephone surveys are used in countries where telephone coverage represents at least 80% of the population or is the customary survey methodology (see the Country Dataset Details for detailed information for each country). In Central and Eastern Europe, as well as in the developing world, including much of Latin America, the former Soviet Union countries, nearly all of Asia, the Middle East, and Africa, an area frame design is used for face-to-face interviewing.

The typical Gallup Worldwide Research survey includes at least 1,000 surveys of individuals. In some countries, oversamples are collected in major cities or areas of special interest. Additionally, in some large countries, such as China and Russia, sample sizes of at least 2,000 are collected. Although rare, in some instances the sample size is between 500 and 1,000. See the Country Dataset Details for detailed information for each country.

FACE-TO-FACE SURVEY DESIGN

FIRST STAGE In countries where face-to-face surveys are conducted, the first stage of sampling is the identification of 100 to 135 ultimate clusters (Sampling Units), consisting of clusters of households. Sampling units are stratified by population size and or geography and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size, otherwise simple random sampling is used. Samples are drawn independent of any samples drawn for surveys conducted in previous years.

There are two methods for sample stratification:

METHOD 1: The sample is stratified into 100 to 125 ultimate clusters drawn proportional to the national population, using the following strata: 1) Areas with population of at least 1 million 2) Areas 500,000-999,999 3) Areas 100,000-499,999 4) Areas 50,000-99,999 5) Areas 10,000-49,999 6) Areas with less than 10,000

The strata could include additional stratum to reflect populations that exceed 1 million as well as areas with populations less than 10,000. Worldwide Research Methodology and Codebook Copyright © 2008-2012 Gallup, Inc. All rights reserved. 8

METHOD 2:

A multi-stage design is used. The country is first stratified by large geographic units, and then by smaller units within geography. A minimum of 33 Primary Sampling Units (PSUs), which are first stage sampling units, are selected. The sample design results in 100 to 125 ultimate clusters.

SECOND STAGE

Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day, and where possible, on different days. If an interviewer cannot obtain an interview at the initial sampled household, he or she uses a simple substitution method. Refer to Appendix C for a more in-depth description of random route procedures.

THIRD STAGE

Respondents are randomly selected within the selected households. Interviewers list all eligible household members and their ages or birthdays. The respondent is selected by means of the Kish grid (refer to Appendix C) in countries where face-to-face interviewing is used. The interview does not inform the person who answers the door of the selection criteria until after the respondent has been identified. In a few Middle East and Asian countries where cultural restrictions dictate gender matching, respondents are randomly selected using the Kish grid from among all eligible adults of the matching gender.

TELEPHONE SURVEY DESIGN

In countries where telephone interviewing is employed, random-digit-dial (RDD) or a nationally representative list of phone numbers is used. In select countries where cell phone penetration is high, a dual sampling frame is used. Random respondent selection is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day. Appointments for callbacks that fall within the survey data collection period are made.

PANEL SURVEY DESIGN

Prior to 2009, United States data were collected using The Gallup Panel. The Gallup Panel is a probability-based, nationally representative panel, for which all members are recruited via random-digit-dial methodology and is only used in the United States. Participants who elect to join the panel are committing to the completion of two to three surveys per month, with the typical survey lasting 10 to 15 minutes. The Gallup Worldwide Research panel survey is conducted over the telephone and takes approximately 30 minutes. No incentives are given to panel participants. Worldwide Research Methodology and Codebook Copyright © 2008-2012 Gallup, Inc. All rights reserved. 9

Research instrument

QUESTION DESIGN

Many of the Worldwide Research questions are items that Gallup has used for years. When developing additional questions, Gallup employed its worldwide network of research and political scientists1 to better understand key issues with regard to question development and construction and data gathering. Hundreds of items were developed, tested, piloted, and finalized. The best questions were retained for the core questionnaire and organized into indexes. Most items have a simple dichotomous ("yes or no") response set to minimize contamination of data because of cultural differences in response styles and to facilitate cross-cultural comparisons.

The Gallup Worldwide Research measures key indicators such as Law and Order, Food and Shelter, Job Creation, Migration, Financial Wellbeing, Personal Health, Civic Engagement, and Evaluative Wellbeing and demonstrates their correlations with world development indicators such as GDP and Brain Gain. These indicators assist leaders in understanding the broad context of national interests and establishing organization-specific correlations between leading indexes and lagging economic outcomes.

Gallup organizes its core group of indicators into the Gallup World Path. The Path is an organizational conceptualization of the seven indexes and is not to be construed as a causal model. The individual indexes have many properties of a strong theoretical framework. A more in-depth description of the questions and Gallup indexes is included in the indexes section of this document. In addition to World Path indexes, Gallup Worldwide Research questions also measure opinions about national institutions, corruption, youth development, community basics, diversity, optimism, communications, religiosity, and numerous other topics. For many regions of the world, additional questions that are specific to that region or country are included in surveys. Region-specific questions have been developed for predominantly Muslim nations, former Soviet Union countries, the Balkans, sub-Saharan Africa, Latin America, China and India, South Asia, and Israel and the Palestinian Territories.

The questionnaire is translated into the major conversational languages of each country. The translation process starts with an English, French, or Spanish version, depending on the region. One of two translation methods may be used.

METHOD 1: Two independent translations are completed. An independent third party, with some knowledge of survey research methods, adjudicates the differences. A professional translator translates the final version back into the source language.

METHOD 2: A translator

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.

What is the Counter-Trafficking Data Collaborative?

The Counter-Trafficking Data Collaborative is the first global data hub on human trafficking, publishing harmonized data from counter-trafficking organizations around the world. Launched in November 2017, the goal of CTDC is to break down information-sharing barriers and equip the counter-trafficking community with up to date, reliable data on human trafficking.

The global victim of trafficking dataset

The CTDC global victim of trafficking dataset is the largest of its kind in the world, and currently exists in two forms. The data are based on case management data, gathered from identified cases of human trafficking, disaggregated at the level of the individual. The cases are recorded in a case management system during the provision of protection and assistance services, or are logged when individuals contact a counter-trafficking hotline. The number of observations in the dataset increases as new records are added by the contributing organizations. The global victim of trafficking dataset that is available to download from the website in csv format has been mathematically anonymized, and the complete, non k-anonymized version of the dataset is displayed throughout the website through visualizations and charts showing detailed analysis.

Where do the data come from?

The data come from a variety of sources. The data featured in the global victim of trafficking dataset come from the assistance activities of the contributing organizations, including from case management services and from counter-trafficking hotline logs.

How are the global datasets created?

Each dataset has been created through a process of comparing and harmonizing existing data models of contributing partners and data classification systems. Initial areas of compatibility were identified to create a unified system for organizing and mapping data to a single standard. Each contributing organization transforms its data to this shared standard and any identifying information is removed before the datasets are made available.

How is the individual-level data protected?

Step 1

Counter-trafficking case data contains highly sensitive information, and maintaining privacy and confidentiality is of paramount importance for CTDC. For example, all explicit identifiers, such as names, were removed from the global victim dataset and some data such as age has been transformed into age ranges. No personally identifying information is transferred to or hosted by CTDC, and organizations that want to contribute are asked to anonymize in accordance to the standards set by CTDC.

Step 2

In addition to the safeguard measures outlined in step 1 the global victim dataset has been anonymized to a higher level, through a mathematical approach called k-anonymization. For a full description of k-anonymization, please refer to the definitions page.

IOM collects and processes data in accordance to its own Data Protection Policy. The other contributors adhere to relevant national and international standards through their policies for collecting and processing personal data.

How to interpret the data?

These data reflect the victims assisted/identified/referred/reported to the contributing organizations, which may not represent all victims identified within a country. Nevertheless, the larger the sample size for a given country (or, the more victims displayed on the map for a given country), the more representative the data are likely to be of the identified victim of trafficking population.

A larger number of identified victims of trafficking does not imply that there is a larger number of undetected victims of trafficking (i.e. a higher prevalence of trafficking).

In addition, samples of identified victims of trafficking cannot be considered random samples of the wider population of victims of trafficking (which includes unidentified victims), since counter-trafficking agencies may be more likely to identify some trafficking cases rather than others. However, with this caveat in mind, the profile of identified victims of trafficking tends to be considered as indicative of the profile of the wider population, given that the availability of other data sources is close to zero.

How does human trafficking case data relate to prevalence data?

There are currently no global or regional estimates of the prevalence of human trafficking. National estimates have been conducted in a few countries but they are also based on modelling of existing administrative data from identified cases and should therefore only be considered as basic baseline estimates. Historically, producing estimates of the prevalence of trafficking based on the collection of new primary data through surveys, for example, has been difficult. This is due to trafficking’s complicated legal definition and the challenges of a...

In this study we use long-term satellite, climate, and crop observations to document the spatial distribution of the recent stagnation in food grain production affecting the water-limited tropics (WLT), a region where 1.5 billion people live and depend on local agriculture that is constrained by chronic water shortages. Overall, our analysis shows that the recent stagnation in food production is corroborated by satellite data. The growth rate in annually integrated vegetation greenness, a measure of crop growth, has declined significantly (p < 0.10) in 23% of the WLT cropland area during the last decade, while statistically significant increases in the growth rates account for less than 2%. In most countries, the decade-long declines appear to be primarily due to unsustainable crop management practices rather than climate alone. One quarter of the statistically significant declines are observed in India, which with the world’s largest population of food-insecure people and largest WLT croplands, is a leading example of the observed declines. Here we show geographically matching patterns of enhanced crop production and irrigation expansion with groundwater that have leveled off in the past decade. We estimate that, in the absence of irrigation, the enhancement in dry-season food grain production in India, during 1982–2002, would have required an increase in annual rainfall of at least 30% over almost half of the cropland area. This suggests that the past expansion of use of irrigation has not been sustainable. We expect that improved surface and groundwater management practices will be required to reverse the recent food grain production declines. MDPI and ACS Style Milesi, C.; Samanta, A.; Hashimoto, H.; Kumar, K.K.; Ganguly, S.; Thenkabail, P.S.; Srivastava, A.N.; Nemani, R.R.; Myneni, R.B. Decadal Variations in NDVI and Food Production in India. Remote Sens. 2010, 2, 758-776. AMA Style Milesi C., Samanta A., Hashimoto H., Kumar K.K., Ganguly S., Thenkabail P.S., Srivastava A.N., Nemani R.R., Myneni R.B. Decadal Variations in NDVI and Food Production in India. Remote Sensing. 2010; 2(3):758-776. Chicago/Turabian Style Milesi, Cristina; Samanta, Arindam; Hashimoto, Hirofumi; Kumar, K. Krishna; Ganguly, Sangram; Thenkabail, Prasad S.; Srivastava, Ashok N.; Nemani, Ramakrishna R.; Myneni, Ranga B. 2010. "Decadal Variations in NDVI and Food Production in India." Remote Sens. 2, no. 3: 758-776.

This dataset was managed for the aims of the project ECOSISTER (Ecosystem for Sustainable Transition in Emilia-Romagna), WP3 of Spoke 5 and provides the long-term records (from 1781 to 2013) of European eel (Anguilla anguilla L.) production in the Comacchio Lagoon (Italy).

he European eel spends most of its life as a yellow eel in freshwater, brackish, and coastal environments. Upon reaching sexual maturity, it undergoes metamorphosis into a silver eel and migrates back to the Sargasso Sea to spawn and die. The silver eels of Comacchio Lagoon were always caught in the lavorieri with approximately 100% efficiency and official estimates of the total biomass were being made every year for more than 200 years. The Regional Park of the Po Delta and the Management Agency for the Parks and Biodiversity of Delta del Po were founded in 1988 and took over the infrastructures, official documents and records of the previous company managing the fishery. These fishery historical records were organized and combined with new data to provide 1) Annual records of total weight of silver eels captured and 2) Annual records that present the variation of fishing area coverage, from 1781 to 2013.

The dataset is provided in two formats:

• Microsoft Excel XLSX file, including 3 sheets (Dataset, Fields and units, Taxonomy)

• CSV files (UTF-8), 3 files corresponding to the 3 sheets of the Excel file

The dataset includes 233 records with total weight of silver eels captured in the Comacchio lagoon, their annual density, and the fishing area coverage. The fields are described in Table 1.

All the dataset fields are described in the Excel sheet/CSV file “Fields and units”, while the taxonomic related information for Anguilla anguilla is provided in the Excel sheet/CSV file “Taxonomy”. Information extracted from the World Register of Marine Species (WoRMS; https://marinespecies.org/) is provided here (see details in Table 2).

Table 1. Fields in the dataset (NA=not available).

Field

Darwin Core term

Unit

Precision

Note

decimalLatitude

decimalLatitude

decimal degrees

± 0.00001

WGS84 (EPSG: 4326) - WAAS/EGNOS enabled GPS position

decimalLongitude

decimalLongitude

decimal degrees

± 0.00001

WGS84 (EPSG: 4326) - WAAS/EGNOS enabled GPS position

dateIdentified

dateIdentified

YYYY

NA

The year on which the data refere

Mass of silver eels (t)

organismQuantity

tons of eel

NA

Total silver eel catches

Abundance (kg/ha)

organismQuantity

kilograms of eels per hectare

NA

Abundance of silver eels

Fishing area (ha)

sampleSizeUnit

hectares

NA

Eel fishing area

Table 2. Provided taxonomic information.

Taxon

the name used in the dataset

ScientificName_accepted

the name accepted according WoRMS

AphiaID

Unique identifier in WoRMS

Kingdom

Taxonomic level

Phylum

Taxonomic level

Class

Taxonomic level

Order

Taxonomic level

Family

Taxonomic level

Genus

Taxonomic level

Species

Taxonomic level

This dataset permitted the analysis of local and global factors responsible for the collapse of the European eel through the publication of Aschonitis, V., Castaldelli, G., Lanzoni, M., Rossi, R., Kennedy, C., and Fano, E. A. (2017) Long-term records (1781–2013) of European eel (Anguilla anguilla L.) production in the Comacchio Lagoon (Italy): evaluation of local and global factors as causes of the population collapse. Aquatic Conserv: Mar. Freshw. Ecosyst., 27: 502–520. doi: 10.1002/aqc.2701.

The data were used to illustrate the population decline of eel in the most important eel fishery in the Mediterranean area, the Valli di Comacchio, followed by a detailed discussion of the potential role of major local factors (habitat loss, changes in local environmental conditions) and global factors (aquaculture and fisheries, climate change, habitat loss, pollution and parasitism) that may be responsible for the population decline of this important eel species.

The Valli di Comacchio which is also one of the most important areas for conservation. In fact, the Comacchio lagoon is included in the 2000 Nature network as IT4060002 “Valli di Comacchio” site and also in the Ramsar convention as important wetlands.

Furthermore, the Anguilla anguilla species is a critically endangered species, according to the IUCN, and is included in the 92/43/EEC Directive, therefore, information on its current population status and dynamics are necessary and can support the development of future conservation plans for eel species. It should also be pointed out that there is no long and detailed historical series on eel fishery, such as the one presented here, which is of quantitative value in describing the evolution of the eel population and due to the constant environmental condition of the area, also provides information on the amount of eel recruitment.