The data lexicon provides an application that promotes transparency across all of FEMA for common data terms used by defining common data terms and providing additional context. The data lexicon contains descriptive information on key attributes of datasets such as:rnrnTitle of requested termrnReason for requested termrnStatus of requested termrnUser who requested the term

Dataset for the AP Research project on Term Limits and their Relationship with Economic and Governmental Indicators. Used correlational analysis to compare de facto and de jure term limits with various economic and developmental variables.

According to reformers, legislative term limits should increase voter turnout by enhancing electoral competitiveness for legislative seats. However, this claim has been largely untested. The only existing study of the effect of legislative term limits on voter turnout, to date, finds that turnout in California did not increase after the imposition of term limits and may have decreased turnout. Yet, it is unclear whether this result generalizes to other states. This study employs a comparative state analysis of both aggregate turnout and district-level turnout rates in state legislative elections. We find that term limits significantly increase voting rates in state legislative elections.

The Long-Term Composite Rate is the unweighted average of bid yields on all outstanding fixed-coupon bonds neither due nor callable in less than 10 years. Dataset updated daily every weekday.

The main goals of the National Post-acute and Long-term Care Study (NPALS) are to: (1) Estimate the supply of paid, regulated long-term care services providers; (2) Estimate key policy-relevant characteristics and practices of these providers; (3) Estimate the number of long-term care services users; (4) Estimate key policy-relevant characteristics of long-term care services users; (5) Produce national and state estimates where feasible within confidentiality and reliability standards; (6) Compare across provider sectors; and (7) Monitor trends over time.

NPALS used a two-stage probability-based sample design. In the first stage, a stratified random sample of providers were selected among adult day service centers (ADSCs); in the second stage, current services users (participants in ADSCs) were randomly selected.

The provider questionnaire included survey items on provider characteristics such as ownership, size, services offered, selected practices, and staffing; questions about aggregate user characteristics (age and race) were included. The services user datasets include user demographics, health conditions, limitations with activities of daily living, number of prescription medications, adverse events, and services used. This is the services user or participant level data file.

We show that the conditional distribution of forecasted GDP growth depends on financial conditions in a panel of 11 advanced economies. Financial conditions have a larger effect on the lower 5th percentile of conditional growth—which we call growth-at-risk (GaR)—than the median. In addition, the term structure of GaR reflects that when initial financial conditions are loose, downside risks are lower in the near-term but increase in later quarters. This intertemporal tradeoff for loose financial conditions is amplified when credit-to-GDP growth is rapid. Using granular instrumental variables, we also provide evidence that the relationship from loose financial conditions to future downside risks is causal. Our results suggest that models of macrofinancial linkages should incorporate the endogeneity of higher-order moments to systematically account for downside risks to growth in the medium run.

Note: The Board of Governors has discontinued the Survey of Terms of Business Lending (STBL) and the associated E.2 release. The final STBL was conducted in May 2017, and the final E.2 was released on August 2, 2017. The STBL has been replaced by a new Small Business Lending Survey that commenced in February 2018. The new survey is being managed and administered by the Federal Reserve Bank of Kansas City. Results from this new survey can be found here.

Long-term Industry Projections for a 10-year time horizon are produced for the State and its labor market regions to provide individuals and organizations with an insight into future industry trends to make informed decisions on individual career and organizational program development. Long-term projections are revised every year. Data are not available for geographies below the labor market regions. Detail may not add to summary lines due to suppression of confidential data.

10-Year Forward Term Premium: 35 years of historical data from 1990 to 2025.

The USDA Long-Term Agroecosystem Research was established to develop national strategies for sustainable intensification of agricultural production. As part of the Agricultural Research Service, the LTAR Network incorporates numerous geographies consisting of experimental areas and locations where data are being gathered. Starting in early 2019, two working groups of the LTAR Network (Remote Sensing and GIS, and Data Management) set a major goal to jointly develop a geodatabase of LTAR Standard GIS Data Layers. The purpose of the geodatabase was to enhance the Network's ability to utilize coordinated, harmonized datasets and reduce redundancy and potential errors associated with multiple copies of similar datasets. Project organizers met at least twice with each of the 18 LTAR sites from September 2019 through December 2020, compiling and editing a set of detailed geospatial data layers comprising a geodatabase, describing essential data collection areas within the LTAR Network. The LTAR Standard GIS Data Layers geodatabase consists of geospatial data that represent locations and areas associated with the LTAR Network as of late 2020, including LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This geodatabase was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. The creation of the geodatabase began with initial requests to LTAR site leads and data managers for geospatial data, followed by meetings with each LTAR site to review the initial draft. Edits were documented, and the final draft was again reviewed and certified by LTAR site leads or their delegates. Revisions to this geodatabase will occur biennially, with the next revision scheduled to be published in 2023. Resources in this dataset:Resource Title: LTAR Standard GIS Data Layers, 2020 version, File Geodatabase. File Name: LTAR_Standard_GIS_Layers_v2020.zipResource Description: This file geodatabase consists of authoritative GIS data layers of the Long-Term Agroecosystem Research Network. Data layers include: LTAR site locations, LTAR site points of contact and street addresses, LTAR experimental boundaries, LTAR site "legacy region" boundaries, LTAR eddy flux tower locations, and LTAR phenocam locations.Resource Software Recommended: ArcGIS,url: esri.com Resource Title: LTAR Standard GIS Data Layers, 2020 version, GeoJSON files. File Name: LTAR_Standard_GIS_Layers_v2020_GeoJSON_ADC.zipResource Description: The contents of the LTAR Standard GIS Data Layers includes geospatial data that represent locations and areas associated with the LTAR Network as of late 2020. This collection of geojson files includes spatial data describing LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This dataset was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. Resource Software Recommended: QGIS,url: https://qgis.org/en/site/

This dataset has been published by the Commissioner of Revenue of the City of Virginia Beach and data.vbgov.com. The mission of data.vbgov.com is to provide timely and accurate City information to increase government transparency and access to useful and well organized data by the general public, non-governmental organizations, and City of Virginia Beach employees.

Temperature and salinity of sea water entering the Milford NOAA Laboratory has been being collected since 1948. From 1948-1974 the temperature data was collected at the dock station. From 1974 to present the temperature data has been collected from a tank inside the laboratory once per day. The salinity data has been collected from 1974 to present once per day from a tank inside the laboratory...

These data describe the estimated species abundances and individual sizes of fishes surveyed in late July or early August of each year by researchers associated with the Moorea Coral Reef Long Term Ecological Research site. This study began in 2005, and the dataset is updated annually. Divers using SCUBA estimate the number and total length (total body length to the greatest precision possible) of all mobile and semi-cryptic fishes observed on four 50m long transects within each of the three principal habitat types, fore reef, back reef, and fringing reef, found around Moorea. These three habitats are each surveyed at six permanently marked sites, two sites on each of Moorea's three shores, yielding a total of 18 unique habitats (3) by location (6) combinations and 72 transects. Estimated total lengths are converted to estimates of species biomass using published length-weight relationships for each species. Data from the initial survey conducted in 2005 are presented in a separate data table as the protocol used in 2005 differed from the standard protocol adopted in 2006, and no estimates of fish body lengths were made in 2005. These data are a component of the MCR LTER core time series program and provide insight into the spatial and temporal patterns of reef fish abundance and biomass around the island of Moorea, French Polynesia.

Andrews Forest precipitation has been measured continuously using various rain gage types since 1951. Most of these rain gages are standard (non-recording) gages with 7.5 or 8 inch orifices or large capacity storage gages intended for sites with limited access collected irregularly over longer intervals. Recording rain gages have also been established to collect higher temporal resolutions (e.g., 5 minute or 15 minute) and also used as a means of parsing (“prorating”) these periodic interval measurements from these standard and storage gages into daily totals. This data set includes an inventory of all rain gages that have operated within the Andrews as well as one site in the nearby Wildcat RNA and one in the town of Blue River. The inventory includes information regarding the date range of operation, gage location, type of gage, the rain network within which it was established, general availability of data and descriptive notes. A second table includes all of the raw measurement data for these non-recording gages over every interval where data were taken, and additionally includes the corresponding recording gage and its measurement total used to prorate data into a daily record. A third table includes the prorated daily data for all of these standard and storage gages as well as the true daily totals for two recording rain gages. A fourth table includes high temporal resolution for one early recording gage at Forks and the Mack Creek recording gage. Note that while precipitation data associated with the 6 benchmark stations are included in this rain gage inventory (Entity 1), the daily and high temporal resolution data for these sites are available through a separate meteorological data set, database code MS001.

Comprehensive dataset of 8 Short-term adult educations in South Korea as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Portugal - Long-term unemployment by sex - quarterly data was 2.40 % of population in the labour force in March of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Portugal - Long-term unemployment by sex - quarterly data - last updated from the EUROSTAT on July of 2025. Historically, Portugal - Long-term unemployment by sex - quarterly data reached a record high of 9.90 % of population in the labour force in June of 2013 and a record low of 1.70 % of population in the labour force in June of 2020.

This occurrence dataset provides primary data on repeated tree measurement of two inventories on the permanent sampling plot (8.8 ha) established in the old-growth polydominant broadleaved forest stand in the “Kaluzhskie Zaseki” State Nature Reserve (center of the European part of Russian Federation). The time span between the inventories was 30 years, and a total of more than 11 000 stems were included in the study (11 tree species and 3 genera). During the measurements, the tree species (for some trees only genus was determined), stem diameter at breast height of 1.3 m (DBH), and life status were recorded for every individual stem, and some additional attributes were determined for some trees. Field data were digitized and compiled into the PostgreSQL database. Deep data cleaning and validation (with documentation of changes) has been performed before data standardization according to the Darwin Core standard.

Представлены первичные данные двух перечетов деревьев, выполненных на постоянной пробной площади (8.8 га), заложенной в старовозрастном полидоминантном широколиственном лесу в заповеднике “Калужские засеки”. Перечеты выполнены с разницей в 30 лет, всего исследовано более 11 000 учетных единиц (деревья 11-ти видов и 3-х родов). Для каждой учетной единицы определяли вид, диаметр на высоте 1.3 м и статус, для части деревьев также измеряли дополнительные характеристики. Все полевые данные были оцифрованы и организованы в базу данных в среде PostgreSQL. Перед стандартизацией данных в соответствии с Darwin Core выполнена их тщательная проверка, все внесенные изменения документированы.

This dataset globally (excluding frigid/polar zones) quantifies the different facets of variability in surface soil (0 – 30 cm) salinity and sodicity for the period between 1980 and 2018. This is realised by developing 4-D predictive models of Electrical Conductivity of saturated soil Extract (ECe) and soil Exchangeable Sodium Percentage (ESP) as indicators of soil salinity and sodicity. These machine learning-based models make predictions for ECe and ESP at different times, locations, and depths and by extracting meaningful statistics form those predictions, different facets of variability in the surface soil salinity and sodicity are quantified. The dataset includes 10 maps documenting different aspects of soil salinity and sodicity variations, and auxiliary data required for generation of those maps. Users are referred to the corresponding "READ_ME" file for more information about this dataset.

Slovenia - Long-term unemployment by sex - quarterly data was 1.20 % of population in the labour force in March of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Slovenia - Long-term unemployment by sex - quarterly data - last updated from the EUROSTAT on July of 2025. Historically, Slovenia - Long-term unemployment by sex - quarterly data reached a record high of 5.70 % of population in the labour force in March of 2014 and a record low of 1.00 % of population in the labour force in December of 2024.

Slovakia - Long-term unemployment by sex - quarterly data was 3.40 % of population in the labour force in March of 2025, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Slovakia - Long-term unemployment by sex - quarterly data - last updated from the EUROSTAT on July of 2025. Historically, Slovakia - Long-term unemployment by sex - quarterly data reached a record high of 11.80 % of population in the labour force in December of 2013 and a record low of 3.30 % of population in the labour force in June of 2024.