This dataset is about countries in Central Asia. It has 5 rows. It features 66 columns including ISO 3 country code, ISO 2 country code, country full name, and currency.

The dataset contains details on all publications on Central Asia published in the People's Republic of China between 1992 and 2022. The data was manually scraped from the CNKI (China National Knowledge Infrastructure, 中国知网). For our search, we used the keywords: “Central Asia” matched with keywords for each of the five Central Asian countries. We then collated the output in an excel file paired with the following variables: author, title, type of publication, journal/publisher, year, abstract, source and keywords. The data was scraped in Mandarin and later automatically translated into English. The present version of the database contains 10,563 publications.To cite:Maracchione, Frank and Jardine, Bradley. (2024). "Central Asian Studies in the People’s Republic of China: A Structural Topic Model", Central Asian Survey.

This dataset is about 2019-2023 earthquakes in Central Asia.

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Time - Tashkent time Source ----> The information was taken from this site

#Uzbekistan #Kazakhstan #Kyrgyzstan #Tajikistan #Turkmenistan #Afghanistan #China

Regional layer of transportation infrastructure in Central Asia. The dataset has been developed based on transportation data collected from Openstreetmap and validated based on local data.

Occurrence dataset: A relatively large (~1500) dataset of fossil mammal occurrence data for the Paleocene, Eocene and Oligocene (66 Ma - 23 Ma) of Mongolia and Northern China above 30 degrees North. Occurrence data comprises species or genus name, specimen information where possible, geological unit specimen was found in, age (range) of specimen and/or geological unit and any other relevant information. Data taken from multiple sources. The majority comes from the Palaeobiology Database (PBDB), an open-access community dataset of global fossil occurrences (and some trait data) for all time periods and taxonomic groups. Our dataset used only the mammal records from our study region and time period. A very small amount of data (10's of occurrences) was taken from the NOW (New and Old Worlds) Database of fossil mammals (NOW database), another open-access community dataset. This database contains only mammal occurrence and trait data for fossil mammals throughout geological history and across the world. Additional occurrence data (~100) was collected first hand from the literature by Dr Gemma Benevento.

Body Size dataset: Lower first molar (m1) length and width (which can be used to estimate mammal body size) was collected for approximately 60% of the individual species in the occurrence dataset (~430 species).

Land cover is a key variable in the context of climate change. In particular, crop type information is essential to understand the spatial distribution of water usage and anticipate the risk of water scarcity and the consequent danger of food insecurity. This applies to arid regions such as the Aral Sea Basin (ASB), Central Asia, where agriculture relies heavily on irrigation. Here, remote sensing is valuable to map crop types, but its quality depends on consistent ground-truth data. Yet, in the ASB, such data is missing. Addressing this issue, we collected thousands of polygons on crop types, 97.7% of which in Uzbekistan and the remaining in Tajikistan. We collected 8,196 samples between 2015 and 2018, 213 in 2011 and 26 in 2008. Our data compiles samples for 40 crop types and is dominated by “cotton” (40%) and “wheat”, (25%). These data were meticulously validated using expert knowledge and remote sensing data and relied on transferable, open-source workflows that will assure the consistency of future sampling campaigns.

This dataset is about countries per year in Central Asia. It has 320 rows. It features 3 columns: country, and male population.

Regional layer of population distribution in Central Asia. Developed as part of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia)

Facing the sustainable agricultural development of the five Central Asian countries, with the goal of land resources, in order to explore the land resources evaluation in Central Asia under the climate change in the past 20 years and the land resources situation in Central Asia under the climate change in the next 30 years, we collected the land resources evaluation elements in Central Asia, including: soil elements (soil salinization degree, soil texture, soil organic matter content, soil pH value, soil total nitrogen), terrain elements (elevation, slope) Climatic elements (rainfall, temperature, solar radiation). Topographic elements and soil elements are based on 2020. Climate elements include 2000, 2010, 2020, and the average precipitation and temperature in 2030 and 2050 under the future SSP5-8.5 scenarios estimated by the ESM1 climate model in CMIP6, with a spatial resolution of 0.01 ° × 0.01°。 The data set can provide basic data support for the future development and utilization of land resources and agricultural development of the five Central Asian countries.

In order to investigate the variation characteristics of agricultural water resources vulnerability in Central Asia, an index system was established with 18 indicators from three components, namely exposure, sensitivity and adaptation, according to the scheme of vulnerability assessment. Based on the socio-economic, topography, land cover and soil data, agricultural water resources vulnerability were calculated using the Equal-Weights and Principal Component Analysis (PCA) method. Each original raster data is resampled, starting from the upper-left corner of the original grid, and extending to the adjacent right and lower grids in turn, and every four grids (0.5 °) are merged into one grid, taking the median data as the center point value corresponding to four grid of geographic coordinates. The extreme values of the grids could be eliminated. The data sets includes 1992-1996, 1997-2001, 2002-2006, 2007-2011, 2012-2017and 1992-2017with a spatial resolution of 0.5°*0.5°. It is expected to provide basic data support for agricultural water supply and demand, development and utilization analysis in five central Asian countries.

Central Asia, site of the historic Silk Road trade network, has long been a conduit for the movement of people, energy, and mineral resources between Europe and Asia. Once part of the former Soviet Union, this region was and continues to be an important producer of base and precious metals, rare metals (RM), including niobium, tantalum, and beryllium, and a past producer of rare earth elements (REE). The Tien Shan and Pamir Mountains regions, encompassing parts of Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan, are of significant interest for mineral exploration as these regions are thought to host substantial undeveloped and undiscovered resources of REE and RM. Based on this legacy, and as an emerging REE and RM producing region, the Central Asian countries are implementing mining sector reforms to create a more attractive investment environment for domestic and foreign mining interests. During the most recent increase in REE prices, beginning in 2009 and culminating in a dramatic price spike in 2011, much mineral exploration activity for REE was undertaken in Kazakhstan, Kyrgyzstan, and Tajikistan. In order to assess the mineral potential for REE in Central Asia, the U.S. Geological Survey began in 2012 compiling an inventory of REE-RM occurrences in that region. These occurrences range in development status from mineral showings to previously developed deposits. Completed in 2016, the inventory consists of 384 REE-RM occurrences, including 160 in Kazakhstan, 75 in Kyrgyzstan, 60 in Tajikistan, 2 in Turkmenistan, and 87 in Uzbekistan. The inventory dataset includes detailed information on location, mineral deposit type, geology, production, resources, and development status. Four important groups of REE-RM mineral deposit types were recognized: (1) carbonatite and alkaline igneous rock-related deposits; (2) pegmatite and skarn/greisen deposits; (3) weathered-crust deposits, including laterite, derived from weathering of other REE-RM mineral deposits; and (4) sediment-hosted uranium deposits. This inventory is released as a database in two formats, a Microsoft Excel workbook and an ESRI ArcGIS 10.5 point feature class dataset built from the Excel workbook. The Excel workbook also includes data field definitions, explanations of the terminology and abbreviations, and references.

This dataset is about books. It has 1 row and is filtered where the book is The political economy of non-western migration regimes : Central Asian migrant workers in Russia and Turkey. It features 7 columns including author, publication date, language, and book publisher.

This dataset is about countries per year in Central Asia. It has 320 rows. It features 4 columns: country, health expenditure per capita, and fertility rate.

This data set updates and expands the NOAA Global Historical Climate Network (GHCN) of quality controlled meteorological records, focusing on the Northern Tien Shan and Pamir Mountain Ranges of Central Asia. It is compiled primarily from meteorological measurements conducted by the National Hydrometeorological Services (NHMS) of the Central Asian countries. Precipitation data are monthly sums bias corrected for gauge type and for wetting, but not for wind. The correction factors, K1 for gauge type, K2 for wind, and K3 for wetting, are included as separate files. Temperature data are monthly means, for example, the mean of daily temperatures for that month, where daily temperature is defined as the average of all observations for each calendar day. For many stations, average maximum and average minimum temperature are supplied as well. These are derived from daily maximum and minimum temperatures. The station metadata for this data set are station histories, population, vegetation, and topography. Data were subjected to rigorous quality control and homogenieity assessment procedures, consistent with those used for the GHCN.There are records from 298 stations. The period of record covered by each station is variable, and in the period from 1985 to 1995, there was a sharp reduction in the number of operating stations. The earliest record is from 1879. Records are updated through 2003 where data are available. Most stations have almost 100 years of observations. Records are from stations in Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan.The data are stored as tab-delimited ASCII text format, Microsoft Excel, and PDF, and are availabe via FTP.

The data set of supply of agricultural water resources in Central Asian adopts the water balance method to calculate the precipitation and runoff depth on grid scale in five central Asian countries, respectively, and estimate the agricultural water resources supply in five central Asian countries. The data source is mainly the precipitation and runoff data products of NOAH model in GLDAS. Each original raster data of 0.25 ° is resampled, starting from the upper-left corner of the original grid, and extending to the adjacent right and lower grids in turn, and every four grids (0.5 °) are merged into one grid, taking the median data as the center point value corresponding to four grid of geographic coordinates. The extreme values of the grids could be eliminated. The data sets includes three time periods of 2000s (2001-2005), 2010s (2006-2010) and 2015s (2011-2015) with a spatial resolution of 0.5°*0.5°; The data of demand of agricultural water resources in Central Asia include irrigation water requirement of cotton and winter wheat in 2006, 2010 and 2016 over Central Asia. This was calculated by the equation of irrigation water requirement presented by FAO. It is expected to provide basic data support for distributed water cycle simulation, water supply and demand, development and utilization analysis in five central Asian countries.

The Regional Research Network „Water in Central Asia“ (CAWa) funded by the German Federal Foreign Office consists of 19 remotely operated multi-parameter stations (ROMPS) in Central Asia. These stations were installed by the German Research Centre for Geosciences (GFZ) in Potsdam, Germany in close cooperation with the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan, the national hydrometeorological services in Uzbekistan and Tajikistan, the Ulugh Beg Astronomical Institute in Tashkent, Uzbekistan, and the Kabul Polytechnic University, Afghanistan. The primary objective of these stations is to support the establishment of a reliable data basis of meteorological and hydrological data especially in remote areas with extreme climate conditions in Central Asia for applications in climate and water monitoring. Up to now, ten years of data are provided for an area of scarce station distribution and with limited open access data which can be used for a wide range of scientific or engineering applications. This dataset provides different types of raw hydrometeorological data such as air temperature, relative humidity, air pressure, wind speed and direction, precipitation, solar radiation, soil moisture and soil temperature as well as snow parameters and river discharge information for selected sites. The data has not undergone any quality control mechanism and should, therefore, be seen as raw data. A visual inspection of the data set has been made and some errors and quality degradation are listed in Zech et al. (2020) but does not claim to be complete. A quality control is strongly recommended by the authors before using the data. Each station data has its own storage directory at the data dissemination server named with the abbreviation (4-letter code) of the station. The data is sampled with a 5-minute interval and stored in hourly files separated by the type of data. These files are then archived as monthly files named with the station abbreviation, type of data, year and month. After one year, these monthly files are further archived to a yearly file. A detailed description for the stations is provided by the Station Exposure Descriptions. Further information about the dataset can be found in Zech et al. (2020). All data is compiled as ASCII data in two different formats which are explained in the documents GITW-SSP-FMT-GFZ-003.pdf (for the stations ALAI, ALA6, and SARY) and CAWA-SSP-FMT-GFZ-006.pdf (for all other stations). Monthly, the data will be dynamically extended as long as data can be acquired from the stations. Additionally, the near real-time data can be displayed and downloaded without any registration from the Sensor Data Storage System (SDSS) hosted at the Central-Asian Institute for Applied Geosciences (CAIAG) in Bishkek, Kyrgyzstan.

Compilation of data from published archaeological sources of both human and faunal stable isotopes across North Central Asia. The compilation includes a listing of georeferenced bioarchaeological samples with descriptions of archaeological context, chronology, and reference bibliography. Measurements of stable carbon and nitrogen isotopes on collagen and stable carbon and oxygen isotopes on bioapatite carbonate are given for each individual sample whenever available. This dataset allows for research into past human lifeways, paleo-environments/climate, and past animal management practices across North Central Asia.

This dataset contains the digitized treatments in Plazi based on the original journal article Turdiboev, Obidjon A., Shormanova, Aijamal A., Sheludyakova, Mariya B., Akbarov, Feruz, Drew, Bryan T., Celep, Ferhat (2022): Synopsis of the Central Asian Salvia species with identification key. Phytotaxa 543 (1): 1-20, DOI: 10.11646/phytotaxa.543.1.1, URL: http://dx.doi.org/10.11646/phytotaxa.543.1.1

Compilation of data from published archaeological sources of both human and faunal stable isotopes across North Central Asia. The compilation includes a listing of georeferenced bioarchaeological samples with descriptions of archaeological context, chronology, and reference bibliography. Measurements of stable carbon and nitrogen isotopes on collagen and stable carbon and oxygen isotopes on bioapatite carbonate are given for each individual sample whenever available. This dataset allows for research into past human lifeways, paleo-environments/climate, and past animal management practices across North Central Asia.

Regional layer of residential buildings in Central Asia. Developed as part of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia program. (https://www.gfdrr.org/en/program/SFRARR-Central-Asia)