cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5063/f1qn64xj
title: Alaskan commercial salmon fishing statistical areas, 2017

description: Participants in Alaska commercial fisheries are required to report the statistical area where their harvest occurs. In combination with reports on the harvest species, poundage and etc., these data are useful to analyze and visualize spatial patterns in harvest. This data set defines the current valid statistical areas that may be used on ADF&G fish tickets for salmon and miscellaneous finfish. This data set should NOT be used for navigation or for determining compliance with ADF&G Commercial Fishing Regulations. Please consult the ADF&G Commercial Fisheries Regulations for the official definitions of regulatory boundaries. NOTE: These data attempt to depict statistical area boundaries as used for management during a specific time period. In some cases, statistical area boundaries used in practice may differ from those described in regulations, reports, maps, and other aids. Up to date published layers and historical areas can be found on Commercial Fishing GIS Data Downloads section on the ADF&G website (http://www.adfg.alaska.gov/index.cfm?adfg=maps.commercial_fishing_gis). This project received funding under award NA15NMF4270272 from NOAA Fisheries Service, in cooperation with the Saltonstall-Kennedy Grant Program.
DOI: 10.5281/zenodo.1320734
title: Data repository - Spatial reconstruction of single enterocytes uncovers broad zonation along the intestinal villus axis

description: Data associated with the manuscript entitled "Spatial reconstruction of single enterocytes uncovers broad zonation along the intestinal villus axis". Files: table_A_LCM_TPM_values.tsv: Gene expression levels of microdissected villus quintiles. First column is the ensemble gene id. Next 15 columns are the raw Kallisto TPM values for villus segments 1 (bottom) to 5 (top) for three different mice (a to c). Additional columns include the external gene name, description, and gene biotype. table_B_scRNAseq_UMI_counts.tsv: Raw UMI counts of cells that were utilized in this study. Analysis is based on raw data from the NCBI GEO datasets GSM2644349 and GSM2644350. Each of the columns represents a single cell, column headers are the corresponding cell barcodes and enable retrieval of tSNE coordinates from table_C_scRNAseq_tsne_coordinates_zones.tsv. Values represent raw UMI counts. table_C_scRNAseq_tsne_coordinates_zones.tsv: tSNE coordinates and reconstructed zones of cells that were utilized in this study. Tab separated text file. Analysis is based on raw data from the NCBI GEO datasets GSM2644349 and GSM2644350. Columns: cell_id: cell barcode, corresponds to column header of Table S2. Seurat tSNE coordinate 1 and tSNE coordinate 2. Last column is the inferred zone (Crypt, V1..V6). table_D_zonation_reconstruction.tsv: Zonation table of reconstructed scRNAseq data. Tab separated text file. Columns: Gene names: gene id, mean expression in each of the crypt zone and 6 villus zones, standard error of the means in the Crypt zone and 6 villus zones, p-value and q-value for the zonation profiles. raw_data.zip: The raw and intermediary data for runnning the scripts in https://github.com/aemoor/Code_spatial_reconstruction_enterocytes
DOI: 10.5066/p963sdey
title: Elevation and Pebble Count Data for 5 New Sites in Glaciated Setting of Pennsylvania and Southern New York, 2016

description: This dataset contains elevation and pebble count data for 5 new sites located at streamflow-gaging stations in the glaciated setting of Pennsylvania and southern New York. Sites were surveyed in 2016 and the elevation data represent topographic features (bankfull, thalweg, etc.) along longitudinal and cross sectional areas of stream reaches. The pebble counts were collected within each cross section. Drainage areas from StreamStats for 70 streamflow-gaging stations in Pennsylvania are also provided.
DOI: 10.7910/dvn/hnnmqt/0l57my
title: clean_panel_wpc.tab

description: data on enrollment and spending for the Wisconsin Parental Choice Program
DOI: 10.7910/dvn/hnnmqt/zv0mut
title: stata.tar.gz

description: American Factfinder files modified for easy importation into Stata
DOI: 10.5063/f12v2d9f
title: Lithology per SASAP region and Hydrolic Unit (HUC8) boundaries for Alaskan watersheds

description: This dataset was created to identify the dominant rock type of each SASAP region and each HUC8 watershed of Alaska. The Global Lithology Map (GliM) from the University of Hamburg (Hartmann, Jörg; Moosdorf, Nils (2012): Global Lithological Map Database v1.0 (gridded to 0.5° spatial resolution). PANGAEA, https://doi.org/10.1594/PANGAEA.788537, License: Creative Commons Attribution 3.0 Unported) was combined with the "sasap_regions.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2c1c26fc-bfb9-4b6a-8d4a-0be8e61c4deb) to create "Lithology_shp_regions.zip", a shapefile that contains measurements of the area covered by certain lithologies in each SASAP region. It was also combined with the "sasap_watersheds_gapfix.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2b5ab57e-38ec-4bc9-8290-f080ec0befb4) to create "Lithology_shp_watersheds.zip", a shapefile that contains measurements of the area covered by certain lithologies in each Alaskan watershed. CSV versions of the resulting shapefiles are also archived. The included python script, which was used to merge the data, outlines the process in more detail.
DOI: 10.5063/f16m3515
title: Elevation per SASAP region and Hydrolic Unit (HUC8) boundary for Alaskan watersheds

description: This dataset was created to assess regions and watersheds of Alaska for mean elevation, minimum elevation, maximum elevation, median elevation, standard deviation of elevation, range of elevation and coefficient of variation of elevation in each SASAP region and each HUC8 watershed of Alaska. Three DEM's were mosaicked to make an Alaska-wide tiff. These include separate files for Alaska, the Yukon, and British Columbia. They were combined with the "sasap_regions.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2c1c26fc-bfb9-4b6a-8d4a-0be8e61c4deb) to create the shapefile, "regions_elevation_shp.zip" and with the "sasap_watersheds_gapfix.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2b5ab57e-38ec-4bc9-8290-f080ec0befb4) to create the shapefile "watersheds_elevation_shp.zip". CSV versions of the resulting shapefiles are also archived. The included python script, which was used to merge the data, outlines the process in more detail.
DOI: 10.5063/f1bc3wr3
title: Hydrologic Unit (HUC8) Boundaries for Alaskan Watersheds

description: The United States is divided and sub-divided into successively smaller hydrologic units which are classified into four levels: regions, sub-regions, accounting units, and cataloging units. The hydrologic units are arranged or nested within each other, from the largest geographic area (regions) to the smallest geographic area (cataloging units). Each hydrologic unit is identified by a unique hydrologic unit code (HUC) consisting of two to eight digits based on the four levels of classification in the hydrologic unit system. A shapefile (or geodatabase) of watersheds for the state of Alaska and parts of western Canada was created by merging two datasets: the U.S. Watershed Boundary Dataset (WBD) and the Government of Canada's National Hydro Network (NHN). Since many rivers in Alaska are transboundary, the NHN data is necessary to capture their watersheds. The WBD data can be found at https://catalog.data.gov/dataset/usgs-national-watershed-boundary-dataset-wbd-downloadable-data-collection-national-geospatial- and the NHN data can be found here: https://open.canada.ca/data/en/dataset/a4b190fe-e090-4e6d-881e-b87956c07977. The included python script was used to subset and merge the two datasets into the single dataset, archived here.
DOI: 10.5063/f1f47mbf
title: Alaskan fishing industry employee counts by month, grouped by region and fish species from 2000-2016

description: The two data files in this package detail monthly Alaskan fishing employee count data. 'AKAvgMonthlyReg_Long.csv' contains employee count data spanning 2000-2016 and is region-specific, while 'AKAvgMonthlySpec_Long.csv' spans 2003-2016 and counts employees by fish species industry (i.e. the species of fish their work involves). Using Tabula, 'AKAvgMonthlyReg_Long.csv' was extracted from http://live.laborstats.alaska.gov/seafood/statewide/AKAvgMonthlyReg.pdf and 'AKAvgMonthlySpec_Long.csv' was extracted from http://live.laborstats.alaska.gov/seafood/statewide/AKAvgMonthlySpec.pdf. The R script "reformat.R" tidies up these two datasets and reformats them into long-form.
DOI: 10.5063/f1z31wvh
title: Slope per SASAP region and Hydrolic Unit (HUC8) boundary for Alaskan watersheds

description: This dataset was created to assess regions and watersheds of Alaska for mean slope, minimum slope, maximum slope, median slope, standard deviation of slope, range of slope and coefficient of variation of slope in each SASAP region and each HUC8 watershed of Alaska. Three DEM's were mosaicked to make an Alaska-wide tiff. These include separate files for Alaska, the Yukon, and British Columbia. They were combined with the "sasap_regions.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2c1c26fc-bfb9-4b6a-8d4a-0be8e61c4deb) to create the shapefile, "regions_slope_shp.zip" and with the "sasap_watersheds_gapfix.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2b5ab57e-38ec-4bc9-8290-f080ec0befb4) to create the shapefile "watersheds_slope_shp.zip". CSV versions of the resulting shapefiles are also archived. The included python script, which was used to merge the data, outlines the process in more detail.
DOI: 10.5066/p9ohs27f
title: Adaptive management in native grasslands managed by the U.S. Fish and Wildlife Service: Implications for grassland birds, 2011-2013 data release

description: This database contains records of grassland bird abundance and vegetation structure on tallgrass and mixed-grass prairies managed by the U.S. Fish and Wildlife Service (USFWS). Specifically, under the adaptive-management decision framework (Native Prairie Adaptive Management [NPAM] intiative), we surveyed breeding birds and sampled vegetation on 89 native prairie NPAM units managed by the U.S. Fish and Wildlife Service, including 55 units in 2011, 87 units in 2012, and 87 units in 2013. The NPAM units occurred in 19 USFWS refuge complexes and wetland management districts, including 14 complexes in USFWS Region 6 (North Dakota, South Dakota, and Montana) and five complexes in USFWS Region 3 (Minnesota).
DOI: 10.7910/dvn/duba3j/77f0tl
title: pratham_tarl_dataverse_files.zip

description: :unav
DOI: 10.7910/dvn/duba3j/itmll5
title: readme.pdf

description: :unav
DOI: 10.7910/dvn/duba3j/sw9kci
title: pratham_tarl_dataverse_files.zip

description: :unav
DOI: 10.7910/dvn/hnnmqt/10sae6
title: 1.tract_covars.do

description: Collects tract-level measures for use in constructing independent variables used in regression analysis
DOI: 10.7910/dvn/hnnmqt/4i46ob
title: wisconsin_tract_covars.tab

description: Tract-level measures of demographic characteristics
DOI: 10.7910/dvn/hnnmqt/5y0xwm
title: 5.tables_figures.do

description: Prepares data for regression analysis and generates tables and figures included in the paper
DOI: 10.7910/dvn/hnnmqt/c9rsi0
title: readme.txt

description: Description of data and scripts, and replication instructions
DOI: 10.7910/dvn/hnnmqt/qsahjx
title: ustracts2010.tab

description: DTA version of 2010 national census tracts gazeteer
DOI: 10.7910/dvn/hnnmqt/s6h1ng
title: raw.tar.gz

description: Raw American Factfinder files
DOI: 10.7910/dvn/hnnmqt/sxijqc
title: ustracts2000.tab

description: DTA version of 2000 national census tracts gazeteer
DOI: 10.7910/dvn/hnnmqt/t8npgk
title: wisconsin_tract_fpl_shares_faminc_famtype.tab

description: Tract-level counts of families in bins defined by income relative to poverty
DOI: 10.7910/dvn/ilz5ql/h55xz6
title: PUBLISH.zip

description: contains dofiles and datasets
DOI: 10.7910/dvn/lclkdt/lsbwrh
title: TextTables.do

description: :unav
DOI: 10.18141/1461471
title: Detailed Analysis of Geospatial Trends of Hydrocarbon Accumulations, Offshore Gulf of Mexico

description: Offshore TRS
DOI: 10.5063/f1pn93tm
title: Area burned by fire per SASAP region and Hydrolic Unit (HUC8) boundary for Alaskan watersheds

description: This dataset was created to assess the area burned in each SASAP region and each HUC8 watershed of Alaska. Twenty rasters with annual fire data from 1992 to 2011 were aggregated to create a binary index of 0 (not burned) and 1 (burned) pixels, producing a geospatial dataset of total land area burned over 20 years in Alaska. The original source of the rasters is "Lindgren, Michael, T. Kurkowski, A. Springsteen. Fire History - Area Burned - Annual. SNAP Data Archive. 2015. http://ckan.snap.uaf.edu/dataset/fire-history-area-burned-annual." This dataset was subset by two areas: 1) The region of Alaska (“sasap_regions.zip" shapefile, located here: https://knb.ecoinformatics.org/#view/urn:uuid:2c1c26fc-bfb9-4b6a-8d4a-0be8e61c4deb) to create the shapefile, "regions_slope_shp.zip”, 2) watershed ("sasap_watersheds_gapfix.zip" shapefile, located here: https://knb.ecoinformatics.org/#view/urn:uuid:2b5ab57e-38ec-4bc9-8290-f080ec0befb4) to create the shapefile "watersheds_slope_shp.zip". This package archives CSV and shapefile versions of the resulting datasets along with the Python script for the analysis.’
DOI: 10.5063/f1td9vhh
title: Percent landcover per SASAP region and Hydrolic Unit (HUC8) boundary for Alaskan watersheds

description: This dataset was created to assess the percentages of various landcovers in each SASAP region and each HUC8 watershed of Alaska (forest/shrub/barren/wetland). The 2010 National Land Cover Dataset ( "2005 North American Land Cover at 250 m spatial resolution. Produced by Natural Resources Canada/Canadian Center for Remote Sensing (NRCan/CCRS), United States Geological Survey (USGS); Insituto Nacional de Estadística y Geografía (INEGI), Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO) and Comisión Nacional Forestal (CONAFOR).”) was combined with the "sasap_regions.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2c1c26fc-bfb9-4b6a-8d4a-0be8e61c4deb) to create the shapefile, "regions_slope_shp.zip" and with the "sasap_watersheds_gapfix.zip" shapefile (located here: https://knb.ecoinformatics.org/#view/urn:uuid:2b5ab57e-38ec-4bc9-8290-f080ec0befb4) to create the shapefile "watersheds_slope_shp.zip". CSV versions of the resulting shapefiles are also archived. The included python script, which was used to merge the data, outlines the process in more detail.
DOI: 10.5066/p9lkxzkp
title: 2017 seismic imaging of the West Napa Fault Zone, St. Helena, California

description: In April 2017, the U.S. Geological Survey acquired high resolution P- and S-wave seismic data across the suspected trace of the West Napa Fault zone in St. Helena, California. We acquired seismic reflection, refraction, and guided-wave data along a 215-m-long profile across the expected trend of the West Napa Fault zone. To acquire the reflection and refraction data, we co-located shots and geophones, spaced every 2 m along the profile. We used 109 SercelTM L40A P-wave (40-Hz vertical-component) geophones with a sensitivity of 22.34 volts/meter/second to record 108 P-wave shots, and 109 SercelTM L28-LBH S-wave (4.5-Hz horizontal-component) geophones with a sensitivity of 31.3 volts/meter/second to record 108 S-wave shots. We generated P-wave data using one of two active sources depending on site accessibility: a 226-kg accelerated weight drop (AWD) and a 3.5-kg sledgehammer and steel plate combination. S-wave sources were generated by horizontally striking an aluminum block with a 3.5-kg sledgehammer. We acquired fault zone guided wave data by generating P- (AWD) and S-wave (angle AWD) energy approximately 225 m north of the P- and S-wave recording arrays. All data were recorded using two 60-channel Geometrics Stratavisor NX-60TM seismographs with a 24-bit analog-to-digital converter with a roll-along descaling factor (Subcommittee of the SEG Engineering and Groundwater Geophysics Committee, 1990); the seismographs were connected to the P- and S-wave geophones via refraction cables. Each shot was recorded for two seconds, with data recording starting 100 ms before the actual time of the shot. Data were recorded at a sampling rate of 0.5 ms, or 2000 samples per second. This report provides the metadata needed to utilize the seismic data. Reference: Subcommittee of the SEG Engineering and Groundwater Geophysics Committee, Pullan, S. E., Chairman, 1990, Recommended standard for seismic (/radar) data files in the personal computer environment: Geophysics, vol. 55, no. 9, p. 1260-1271.
DOI: 10.5066/f72r3pxb
title: Ratings and estimated provisional streamflow for streamgages in Virginia, water years 1991 through 2013

description: The U.S. Geological Survey, in cooperation with the Virginia Department of Environmental Quality, has quantified several measures of rating stability and the frequency and magnitude of changes to ratings through time for 174 real-time continuous streamgages active in Virginia as of September 30, 2013. Alternative flow (AltFlow) tables were developed as a method of estimating provisional flow data. They were constructed for periods with complete records of shifts and ratings between October 1, 1990 and September 30, 2013. Alternate flows consist of Qsame, the flow value from the shifted rating table used to compute the daily flow value at the time of the most recent flow measurement that corresponds to the gage height of each day's daily flow value, and Qprev, the flow value from the shifted rating table in effect at the time of the previous flow measurement that corresponds to the gage height of each day's daily flow value. These AltFlow tables were limited in several important ways that are discussed in the report; most important among them are that they were not developed from the ratings that were in place at the time provisional data were initially published to the web. This data release is comprised of the AltFlow tables and the expanded, shifted ratings used to develop them. Data are grouped by major river basin. Expanded shifted ratings and AltFlows are provided in five Microsoft Excel files. These files include the formulas used to compute the AltFlow tables. These files may be used to extend the AltFlow record for Virginia past the end of the study period, or develop an AltFlow record for another state, using procedures described in Appendix 2 of the companion report (Messinger and Burgholzer, 2018). The AltFlows are also provided in comma-separated variable (csv) files, one file for each major river basin, without formulas and without the fields used only for processing and computation.
DOI: 10.5066/p98z8oj2
title: Incorporating teleseismic tomography data into models of upper mantle slab geometry

description: Earthquake-based models of slab geometry are limited by the distribution of earthquakes within a subducting slab, which is often heterogeneous. The fast seismic velocity signature of slabs in tomography studies is independent of the distribution of earthquakes within the slab, providing a critical constraint on slab geometry when earthquakes are absent. In order to utilize this constraint, researchers typically hand-contour images of subducting slabs in tomography models, leading to a subjective final slab model. With this paper, we present an automated procedure for extracting slab geometry from teleseismic tomography volumes that limits this subjectivity and provides constraints on the structure of aseismic segments of slabs. This procedure is designed as a complement to earthquake-based slab models rather than as a replacement, which can help to broaden the extent of existing subduction zone geometry databases.
DOI: 10.25606/surf.578c6039-1bbd8864
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (1024-011)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 011 of the 1024³ resolution collection.
DOI: 10.7910/dvn/hj2y8u/8xaksy
title: 05.PASTOSAR.tab

description: Data about grasses are planting and its areas
DOI: 10.7910/dvn/hj2y8u/9jv6u7
title: 03.LOTESAR.tab

description: Data about lots and utilization
DOI: 10.7910/dvn/hj2y8u/hnajjp
title: 02.FINCASAR.tab

description: Survey data of Study of early adoption-acceptability by farmers of A. pintoi in Colombia
DOI: 10.7910/dvn/hj2y8u/ialgn0
title: 01.METADATA.tab

description: Description of columns used
DOI: 10.7910/dvn/hj2y8u/wgna34
title: 04.LEGUMAR.tab

description: Data about legumes are planting and its areas
DOI: 10.5063/f15m63wc
title: Summary of Pacific Salmon Escapement Goals in Alaska with a Review of Escapements from 2001 to 2009

description: This dataset is compiled from Tables 1-4 from the report "Summary of Pacific salmon escapement goals in Alaska with a review of escapements from 2001 to 2009.” Escapement is defined as the number of mature salmon migrating from the marine environment to freshwater streams. Escapement data are the enumeration of these migrating fish as they pass upstream, and are a widely used index of spawning salmon abundance. These data are important for fisheries management, since most salmon harvest occurs in freshwater rivers during this migration. As a part of management of these salmon stocks, some Alaskan river systems are assigned escapement goals, which generally represent the number of salmon that need to be given the opportunity to spawn to ensure survival of the stock. Generally there are three common types of escapement goals. Biological Escapement Goals (BEGs) are defined in Alaska fishery regulations 5 AAC 39.222(f) as "the escapement that provides the greatest potential for maximum sustained yield." Sustainable Escapement Goals (SEGs) are defined in the same section as "a level of escapement, indicated by an index or an escapement estimate, that is known to provide for sustained yield over a 5 to 10 year period, used in situations where a BEG cannot be estimated or managed for." Optimal Escapement Goals (OEGs) are defined as "a specific management objective for salmon escapement that considers biological and allocative factors and may differ from the SEG or BEG."