The O*NET Database contains hundreds of standardized and occupation-specific descriptors on almost 1,000 occupations covering the entire U.S. economy. The database, which is available to the public at no cost, is continually updated by a multi-method data collection program. Sources of data include: job incumbents, occupational experts, occupational analysts, employer job postings, and customer/professional association input.

Data content areas include:

• Worker Characteristics (e.g., Abilities, Interests, Work Styles)
• Worker Requirements (e.g., Education, Knowledge, Skills)
• Experience Requirements (e.g., On-the-Job Training, Work Experience)
• Occupational Requirements (e.g., Detailed Work Activities, Work Context)
• Occupation-Specific Information (e.g., Job Titles, Tasks, Technology Skills)

[begin excerpt from Integrating the Aprsworld Database Into Your Application]

The aprsworld.net project was started in March 2001 by James Jefferson Jarvis, KB0THN. The goal from the beginning has ben to parse the APRS internet stream into data that can be stored in a relational database system.

As the time of writing (September 2003) about 1 million raw APRS packets traverse the internet stream each day. Each one of these packets is parsed and inserted into the appropriate table of the aprsworld.net database. These results in about 5 million inserts a day, with an average of about 60 inserts / queries per second. The database grows by about 6 gigabytes per month.

By using the aprsworld.net database you can save the trouble of collecting, parsing, and storing this large ammount of data. Simple operations like finding the last position of a APRS station are extremely easy - and more complex dataminning operations are possible with minimum effort.

[end excerpt]

aprsworld-to-XML Interface

This script provides an XML interface to aprsworld.net, so you don't need to have direct access to the aprsworld or findu databases, or know SQL, in order to get generalized and standardly formatted APRS data directly from the Internet into your application. Free code libraries for parsing XML are easy to find for almost any programming environment.

As new minor versions of this script are made available, they will reside in their own directory containing the version number, so you can safely link to a script without future upgrade changes affecting anything. (bugfix-level versions will not have their own directory)

The net absorption in the data center market in the United States has soared since 2020. In 2024, the net absorption peaked at *** gigawatts, up from about *** gigawatt in the previous year. Net absorption is the capacity that was rented minus the capacity that became available during the period. In 2024, Atlanta recorded the highest net absorption among the leading markets in the United States.

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

.NET.KG Whois Database, discover comprehensive ownership details, registration dates, and more for .NET.KG TLD with Whois Data Center.

Resource Title: NDVI_raw . File Name: NDVI_raw.xlsxResource Description: Raw bimonthly NDVI values for Grass-Cast sites. Resource Title: ANPP. File Name: ANPP.xlsxResource Description: Dataset for annual aboveground net primary productivity (ANPP). Excel sheet is broken into two tabs, 1) 'readme' describing the data, 2) 'ANPP' with the actual data. Resource Title: Grass-Cast_sitelist . File Name: Grass-Cast_sitelist.xlsxResource Description: This provides a list of sites-studies that are currently incorporated into the Database as well as meta-data and contact info associated with the data sets. Includes a 'readme' tab and 'sitelist' tab. Resource Title: Grass-Cast_AgDataCommons_overview. File Name: Grass-Cast_AgDataCommons_download.htmlResource Description: Html document that shows database overview information. This document provides a glimpse of the data tables available within the data resource as well as respective meta-data tables. The R script (R markdown, .Rmd format) that generates the html file, and can be used to upload the Grass-Cast associated Ag Data Commons data files can be downloaded at the 'Grass-Cast R script' zip folder. The Grass-Cast files still need to be locally downloaded before use, but we are looking to make a download automated.

"MEOP (Marine Mammals Exploring the Oceans Pole to Pole) is a consortium of international researchers dedicated to sharing animal-derived data and knowledge about the polar oceans. Since 2004, several hundred thousands profiles of temperature and salinity have been collected by instrumented animals. The use of elephant seals has been particularly effective to sample the Southern Ocean and the North Pacific. Other seal species have been successfully used in the North Atlantic, such as hooded seals. These hydrographic data have been assembled in a quality-controlled database, the MEOP-CTD database. These data are profiles of temperature (°C). Each profile is located in space and time. It must be emphasised that the dataset of each individual CTD-SRDL has been edited and corrected separately, as a given CTD-SRDL has its own specificities in terms of data accuracy and quality of the estimated correction. A post-processing procedure is applied on hydrographic data in order to ensure the best possible data quality. For more details, please visit https://www.meop.net/database/data-processing-and-validation.html." cdm_altitude_proxy=PRES cdm_data_type=TimeSeriesProfile cdm_profile_variables=time,latitude,longitude cdm_timeseries_variables=PLATFORM_NUMBER citation="We recommend the following citation for these data: Marine Mammals Exploring the Oceans Pole to Pole (MEOP). [YEAR]. Animal-borne Temperature Profiles (TEMP). Available at https://www.meop.net/database/meop-databases/meop-ctd-database.html. Accessed via [project] on YYYY-MM-DD. Please also refer to https://www.meop.net/database/how-to-cite.html on how to acknowledge these data appropriately." Conventions=CF-1.6 Sea-mammals-1.1, COARDS, ACDD-1.3 data_DOI=https://www.seanoe.org/data/00343/45461/ data_format_original=netCDF data_mode=D data_update=2024-03-08 data_update_frequence=≥ yearly data_url=https://www.seanoe.org/data/00343/45461/ distribution_statement=Follow MEOP data policy standards, cf. http://www.meop.net/the-dataset/data-access.html. Data available free of charge. User assumes all risk for use of data. User must display citation in any publication or product using data. User must contact PI prior to any commercial use of data Easternmost_Easting=179.9984 featureType=TimeSeriesProfile format_version=1.1 geospatial_lat_max=87.7764 geospatial_lat_min=-78.66 geospatial_lat_units=degrees_north geospatial_lon_max=179.9984 geospatial_lon_min=-179.9998 geospatial_lon_units=degrees_east history=Marine mammal observation infoUrl=https://www.meop.net/database/meop-databases/meop-ctd-database.html institution=MEOP (Marine Mammals Exploring the Oceans Pole to Pole) keywords_vocabulary=GCMD Science Keywords naming_authority=EMODnet Physics Northernmost_Northing=87.7764 number_light_profiles=0.0 owner=MEOP consortium (Marine Mammals Exploring the Oceans Pole to Pole) owner_url=http://www.meop.net platform_type=organism references=https://www.seanoe.org/data/00343/45461/ source=In situ observations sourceUrl=(local files) Southernmost_Northing=-78.66 standard_name_vocabulary=CF Standard Name Table v85 subsetVariables=PLATFORM_NUMBER,nation,location,species time_coverage_end=2024-02-22T12:45:00Z time_coverage_start=2004-01-27T11:49:00Z variables=DC_REFERENCE, DATA_STATE_INDICATOR, DATA_MODE, INST_REFERENCE, WMO_INST_TYPE, JULD, JULD_QC, JULD_LOCATION, LATITUDE, LONGITUDE, POSITION_QC, POSITIONING_SYSTEM, PROFILE_PRES_QC, PROFILE_PSAL_QC, PROFILE_TEMP_QC, PRES, PRES_QC, PRES_ADJUSTED, PRES_ADJUSTED_QC, PRES_ADJUSTED_ERROR, TEMP, TEMP_QC, TEMP_ADJUSTED, TEMP_ADJUSTED_QC, TEMP_ADJUSTED_ERROR, PSAL, PSAL_QC, PSAL_ADJUSTED, PSAL_ADJUSTED_QC, PSAL_ADJUSTED_ERROR, PARAMETER, SCIENTIFIC_CALIB_EQUATION, SCIENTIFIC_CALIB_COEFFICIENT, PRES_INTERP, TEMP_INTERP, PSAL_INTERP Westernmost_Easting=-179.9998

This dataset covers all relevant information on every Afrotropical moth species. The zoogeographic area covered can be defined as the Africa continent south of the Sahara (i.e. excl. Morocco, Algeria, Tunisia, Libya and Egypt), the islands in the Atlantic Ocean: Amsterdam Island, Ascension, Cape Verde Archipelago, Inaccessible Island, St. Helena, São Tomé and Principe, Tristan da Cunha, and the islands in the Indian Ocean: Comores (Anjouan, Grande Comore, Mayotte, Mohéli), Madagascar, Mascarene Islands (La Réunion, Mauritius, Rodrigues), Seychelles (Félicité, Mahé, Praslin, Silhouette, a.o.). Furthermore, also those moth species occurring in the transition zone to the Palaearctic fauna have been included, namely most of the Arabia Peninsula (Kuwait, Oman, Saudi Arabia, United Arab Emirates, Yemen with Socotra) but not Iraq, Jordan and further north. Also, some Saharan species have been included (e. g. Hoggar Mts. in Algeria, Tibesti Mts. in South Libya). Utmost care was taken that the data incorporated in the database are correct. We decline any responsibility in case of damage to soft- or hardware based on information used in this website. Persons retrieving information from this website for their own research or for applied aspects such as pest control programmes, should acknowledge the usage of data from this website in the following format: De Prins, J. & De Prins, W. 2011. Afromoths, online database of Afrotropical moth species (Lepidoptera). World Wide Web electronic publication (www.afromoths.net)

Macedonia MK: Net Official Flows from UN Agencies: UNICEF data was reported at 0.640 USD mn in 2016. This records a decrease from the previous number of 0.980 USD mn for 2015. Macedonia MK: Net Official Flows from UN Agencies: UNICEF data is updated yearly, averaging 0.720 USD mn from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 1.360 USD mn in 1996 and a record low of 0.480 USD mn in 2000. Macedonia MK: Net Official Flows from UN Agencies: UNICEF data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Macedonia – Table MK.World Bank: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor).). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), , United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), Wolrd Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), and International Labour Organization (ILO). Data are in current U.S. dollars.; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline.; Sum;

Bosnia and Herzegovina Net Official Flows from UN Agencies: SDGFUND data was reported at 0.750 USD mn in 2022. Bosnia and Herzegovina Net Official Flows from UN Agencies: SDGFUND data is updated yearly, averaging 0.750 USD mn from Dec 2022 (Median) to 2022, with 1 observations. The data reached an all-time high of 0.750 USD mn in 2022 and a record low of 0.750 USD mn in 2022. Bosnia and Herzegovina Net Official Flows from UN Agencies: SDGFUND data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bosnia and Herzegovina – Table BA.World Bank.WDI: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO), United Nations Institute for Disarmament Research (UNIDIR), United Nations Capital Development Fund (UNCDF), WHO-Strategic Preparedness and Response Plan (SPRP), United Nations Women (UNWOMEN), Covid-19 Response and Recovery Multi-Partner Trust Fund (UNCOVID), Joint Sustainable Development Goals Fund (SDGFUND), Central Emergency Response Fund (CERF), WTO-International Trade Centre (WTO-ITC), United National Conference on Trade and Development (UNCTAD), and United Nations Industrial Development Organization (UNIDO). Data are in current U.S. dollars.;Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: https://data-explorer.oecd.org/.;Sum;

China Food: Total Asset: Net Fixed data was reported at 251,571.000 RMB mn in 2010. This records an increase from the previous number of 213,975.000 RMB mn for 2009. China Food: Total Asset: Net Fixed data is updated yearly, averaging 74,332.707 RMB mn from Dec 1993 (Median) to 2010, with 18 observations. The data reached an all-time high of 251,571.000 RMB mn in 2010 and a record low of 25,335.000 RMB mn in 1993. China Food: Total Asset: Net Fixed data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Industrial Sector – Table CN.BHB: Food.

History of Work

Here you find the History of Work resources as Linked Open Data. It enables you to look ups for HISCO and HISCAM scores for an incredible amount of occupational titles in numerous languages.

Data can be queried (obtained) via the SPARQL endpoint or via the example queries. If the Linked Open Data format is new to you, you might enjoy these data stories on History of Work as Linked Open Data and this user question on Is there a list of female occupations?.

NEW version - CHANGE notes

This version is dated Apr 2025 and is not backwards compatible with the previous version (Feb 2021). The major changes are: - incredible simplification of graph representation (from 81 to 12); - use of sdo (https://schema.org/) rather than schema (http://schema.org); - replacement of prov:wasDerivedFrom with sdo:isPartOf to link occupational titles to originating datasets; - etl files (used for conversion to Linked Data) now publicly available via https://github.com/rlzijdeman/rdf-hisco; - update of issues with language tags; - specfication of language tags for english (eg. @en-gb, instead of @en); - new preferred API: https://api.druid.datalegend.net/datasets/HistoryOfWork/historyOfWork-all-latest/sparql (old API will be deprecated at some point: https://api.druid.datalegend.net/datasets/HistoryOfWork/historyOfWork-all-latest/services/historyOfWork-all-latest/sparql ) .

There are bound to be some issues. Please leave report them here.

Figure 1. Part of model illustrating the basic relation between occupations, schema.org and HISCO. https://druid.datalegend.net/HistoryOfWork/historyOfWork-all-latest/assets/601beed0f7d371035bca5521" alt="hisco-basic">

Figure 2. Part of model illustrating the relation between occupation, provenance and HISCO auxiliary variables. https://druid.datalegend.net/HistoryOfWork/historyOfWork-all-latest/assets/601beed0f7d371035bca551e" alt="hisco-aux">

The PISUNA-net Local Observations database was developed to record, archive, and share indigenous and local knowledge and expertise on natural resources and resource use on the western and northern coasts of Greenland.

In 2023, over half of the Italian digital population received an alert that their data was breached. Of these, 77.5 percent of the received alerts referred to data compromise on the dark web. In comparison, only 22.5 percent of breached data were found on the index web, also called surface net.

The HANPP Collection: Human Appropriation of Net Primary Productivity as a Percentage of Net Primary Productivity represents a map identifying regions in which human consumption of NPP is greatly in excess of production by local ecosystems. Humans appropriate net primary productivity through the consumption of food, paper, wood and fiber, which alters the composition of the atmosphere, levels of biodiversity, energy flows within food webs and the provision of important ecosystem services. Net primary productivity (NPP), the net amount of solar energy converted to plant organic matter through photosynthesis, can be measured in Units of elemental carbon and represents the primary food energy source for the world's ecosystems.

Net primary productivity (NPP) over global grasslands is crucial for understanding the terrestrial carbon cycling and for the assessments of wild herbivores food security. During the past few decades, numerous field investigations have been conducted to estimate grassland NPP since the measuring criterion released by the International Biological Program. However, a comprehensive NPP database, particularly for belowground NPP (BNPP), in global grasslands is rare to date. Here, field NPP measurements from 438 publications (1957–2018) in global grasslands were collected, critically filtered, and incorporated in a comprehensive global database with observations for aboveground NPP (ANPP), BNPP, total NPP (TNPP), and BNPP fraction (fBNPP). Associated information on geographical locations, climatic records, grassland types, land use patterns, manipulations subjected to manipulative experiments, sampling year of study sites as well as NPP measurement methods are also documented. This database ...

Foreign direct investment, net inflows (% of GDP) in Spain was reported at 2.6513 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Spain - Foreign direct investment, net inflows (% of GDP) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Data#3 reported AUD21.89M in Net Income for its fiscal semester ending in June of 2024. Data for Data#3 | DTL - Net Income including historical, tables and charts were last updated by Trading Economics this last August in 2025.

.NET.RU Whois Database, discover comprehensive ownership details, registration dates, and more for .NET.RU TLD with Whois Data Center.

Included in this dataset are SNP and fasta data for the Pea Single Plant Plus Collection (PSPPC) and the PSPPC augmented with 25 P. fulvum accessions. These 6 datasets can be roughly divided into two groups. Group 1 consists of three datasets labeled PSPPC which refer to SNP data pertaining to the USDA Pea Single Plant Plus Collection. Group 2 consists of three datasets labeled PSPPC + P. fulvum which refer to SNP data pertaining to the USDA PSPPC with 25 accessions of Pisum fulvum added. SNPs for each of these groups were called independently; therefore SNP names that are shared between the PSPPC and PSPPC + P. fulvum groups should NOT be assumed to refer to the same locus. For analysis, SNP data is available in two widely used formats: hapmap and vcf. These formats can be successfully loaded into TASSEL v. 5.2.25 (http://www.maizegenetics.net/tassel). Explanations of fields (columns) in the VCF files are contained within commented (##) rows at the top of the file. Descriptions of the first 11 columns in the hapmap file are as follows: rs#- Name of locus (i.e. SNP name) alleles- Indicates the SNPs for each allele at the locus chrom- Irrelevant for these datasets, since markers are unordered. pos- Irrelevant for these datasets, since markers are unordered. strand- Irrelevant for these datasets, since markers are unordered assembly#- required field for hapmap format. NA for these datasets center- required field for hapmap format. NA for these datasets protLSID- required field for hapmap format. NA for these datasets assayLSID- required field for hapmap format. NA for these datasets panel- required field for hapmap format. NA for these datasets QCcode- required field for hapmap format. NA for these datasets The fasta sequences containing the SNPs are also available for such downstream applications as development of primers for platform-specific markers. For more information about this dataset, contact Clarice Coyne at Clarice.Coyne@usda.gov or coynec@wsu.edu. Resources in this dataset:Resource Title: PSPPC SNPs in hapmap format. File Name: PSPPC.hmp.txtResource Description: 66591 unanchored SNPs for the PSPPC collection in hapmap formatResource Software Recommended: TASSEL,url: http://www.maizegenetics.net/tassel Resource Title: PSPPC SNP FASTA Sequences. File Name: PSPPC.fa.txtResource Description: FASTA sequences for each allele of the PSPPC SNP datasetResource Title: PPSPPC + P. fulvum SNPs in hapmap format. File Name: PSPPC+fulvums.hmp.txtResource Description: 67400 SNPs from the PSPPC augmented with 25 P. fulvum accessions in hapmap format. SNP names are independent and unrelated to plain PSPPC SNP files.Resource Software Recommended: TASSEL,url: http://www.maizegenetics.net/tassel Resource Title: PSPPC + P. fulvum SNP FASTA Sequences. File Name: PSPPC+fulvums.fa.txtResource Description: FASTA sequences for each allele of the PSPPC + P. fulvum SNP dataset. SNP names are independent and unrelated to plain PSPPC SNP files.Resource Title: PSPPC + P. fulvum SNPs in vcf format. File Name: PSPPC+fulvums.vcf.txtResource Description: 67400 SNPs from the PSPPC augmented with 25 P. fulvum accessions in vcf format. SNP names are independent and unrelated to plain PSPPC SNP files.Resource Software Recommended: TASSEL,url: http://www.maizegenetics.net/tassel Resource Title: PSPPC SNPs in vcf format. File Name: PSPPC.vcf.txtResource Description: 66591 SNPs from the PSPPC in vcf formatResource Software Recommended: TASSEL,url: http://www.maizegenetics.net/tassel Resource Title: README. File Name: Data Dictionary.docxResource Description: These data are for the Pea Single Plant Plus Collection (PSPPC) and the PSPPC augmented with 25 P. fulvum accessions. The 6 datasets can be divided into two groups. Group 1 consists of 3 datasets labeled “PSPPC” which refer to SNP data pertaining to the USDA Pea Single Plant Plus Collection. Group 2 consists of 3 datasets labeled “PSPPC + P. fulvum” which refer to SNP data pertaining to the PSPPC with 25 accessions of Pisum fulvum added. SNPs for each of these groups were called independently; therefore any SNP name that is shared between the PSPPC and PSPPC + P. fulvum groups should NOT be assumed to refer to the same locus. For analysis, SNP data is available in two widely used formats: hapmap and vcf. These files were successfully loaded into the standalone version of TASSEL v. 5.2.25 (http://www.maizegenetics.net/tassel). Explanations of fields (columns) in the VCF files are contained within commented (##) rows at the top of the file. The first 11 columns required for the hapmap format are as follows: rs#- Name of locus (i.e. SNP name) alleles- Indicates the SNPs for each allele at the locus chrom- N/A, since markers are unordered. pos- N/A, since markers are unordered. strand- N/A, since markers are unordered assembly#- N/A center- N/A protLSID- N/A assayLSID- N/A panel- N/A QCcode- N/A The fasta sequences containing the SNPs are also available here for such downstream applications as development of primers for platform-specific markers.