cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p9a7ac65
title: Return Beam Vidicon (RBV)

description: The Return Beam Vidicon (RBV) operated on Landsat satellites 1 and 2, and acquired approximately 1,600 sub-scenes at 80 meter resolution. The initial RBV sensor configuration used three independent cameras, each sensing a different spectral wavelength such as (0.48 to 0.83, 0.48 to 0.57, 0.58 to 0.68, and 0.70 to 0.83 micrometer). Landsat 1 and 2 RBV data were recorded to 70 millimeter (mm) black and white film rolls at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center and delivered to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center for archiving and user distribution. The RBV sensor utilized vidicon tube instruments containing an electron gun that read images from a photoconductive faceplate similar to television cameras The data stream received from the satellite was analog-to-digital preprocessed to correct for radiometric and geometric errors. The RBV system was redesigned for Landsat 3 to use a two-camera configuration mounted side by side that acquired four sub-scenes within the field of view of a Multispectral Scanner (MSS) scene. The Landsat 3 RBV spatial resolution is 40 meters with a spectral wavelength of 0.505 to 0.75 micrometer. Landsat 3 data were also recorded to 70 mm film until the EROS Digital Imagery Processing System (EDIPS) became operational in 1979. EROS Laser Beam Recorders (LBRs) recorded MSS and RBV data at 28 microns to 9-inch film rolls and the imagery was chipped up for archival storage and remains a viable archive backup to the digital MSS archive. However, all of the RBV digital archive data were purged for lack of computer compatible reasons. The last known collection of RBV tapes were disposed of in 2003. Today, the RBV 70 mm and 9-inch film sources are maintained in the USGS EROS archive and are accessible through EarthExplorer as an on-demand film scanning product. RBV images that are scanned and the black and white images faithfully represent the Landsat RBV film archive as it exists today.
DOI: 10.18739/a20p0wq64
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015H, Beaufort Sea, Arctic Ocean, 2015
DOI: 10.18739/a27659f39
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2010H, Central Arctic, 2010
DOI: 10.18739/a2862bb22
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2011M, Central Arctic, 2011
DOI: 10.18739/a2bz6176n
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2010F, Beaufort Sea, Arctic Ocean, 2010
DOI: 10.18739/a2gq6r201
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015G, Central Arctic, 2015
DOI: 10.18739/a2ng4gr5g
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2006B, Central Arctic, 2006
DOI: 10.18739/a2r785n9c
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015B, Beaufort Sea, Arctic Ocean, 2015
DOI: 10.18739/a2s756j84
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013G, Beaufort Sea, Arctic Ocean, 2013
DOI: 10.18739/a2v11vk32
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013C, Central Arctic, 2013
DOI: 10.18739/a2w08wg28
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2011A, Beaufort Sea, Arctic Ocean, 2011
DOI: 10.18739/a2ww7700r
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2010G, Canadian Arctic Archipelago, 2010
DOI: 10.18739/a20k26b17
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2003D, Beaufort Sea, Arctic Ocean, 2003
DOI: 10.18739/a21j9773w
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013E, Central Arctic, 2013
DOI: 10.18739/a22j6842n
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012J, Laptev Sea, Arctic Ocean, 2012
DOI: 10.18739/a23b5w75r
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013F, Beaufort Sea, Arctic Ocean, 2013
DOI: 10.18739/a23f4kn0n
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013H, Central Arctic, 2013
DOI: 10.18739/a24b2x46g
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2007B, Beaufort Sea, Arctic Ocean, 2007
DOI: 10.18739/a24f1mh9s
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012D, Central Arctic, 2012
DOI: 10.18739/a2599z165
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012G, Central Arctic, 2012
DOI: 10.18739/a2696zx5h
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2014C, Beaufort Sea, Arctic Ocean, 2014
DOI: 10.18739/a2736m200
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015I, Central Arctic, 2015
DOI: 10.18739/a2833mz0t
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015K, Chukchi Sea, Arctic Ocean, 2015
DOI: 10.18739/a2930nt9z
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013I, Beaufort Sea, Arctic Ocean, 2013
DOI: 10.18739/a29z90b7w
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2016A, Beaufort Sea, Arctic Ocean, 2016
DOI: 10.18739/a2bv79v4d
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2009D, Central Arctic, 2009
DOI: 10.18739/a2cv4br35
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012L, Beaufort Sea, Arctic Ocean, 2012
DOI: 10.18739/a2cz3246w
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2014B, Beaufort Sea, Arctic Ocean, 2014
DOI: 10.18739/a2dr2p81k
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2011K, Beaufort Sea, Arctic Ocean, 2011
DOI: 10.18739/a2fn10r8v
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2010B, Beaufort Sea, Arctic Ocean, 2010
DOI: 10.18739/a2fq9q50s
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013B, Central Arctic, 2013
DOI: 10.18739/a2gm81n72
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012H, Beaufort Sea, Arctic Ocean, 2012
DOI: 10.18739/a2hh6c55g
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2007F, Beaufort Sea, Arctic Ocean, 2007
DOI: 10.18739/a2hq3rz1b
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2014I, Beaufort Sea, Arctic Ocean, 2014
DOI: 10.18739/a2jh3d247
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2006D, Laptev Sea, Arctic Ocean, 2006
DOI: 10.18739/a2kd1qk1r
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012B, Central Arctic, 2012
DOI: 10.18739/a2kh0dz42
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012F, Canadian Islands, 2012
DOI: 10.18739/a2m90229x
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2005F, Central Arctic, 2005
DOI: 10.18739/a2mg7fv57
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012C, Central Arctic, 2012
DOI: 10.18739/a2p843v8z
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2011B, Beaufort Sea, Arctic Ocean, 2011
DOI: 10.18739/a2q23r032
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2004C, Central Arctic, 2004
DOI: 10.18739/a2q814r9p
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015D, Central Arctic, 2015
DOI: 10.18739/a2r20rw2d
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2013D, Beaufort Sea, Arctic Ocean, 2013
DOI: 10.18739/a2s17ss23
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012E, Canadian Arctic Archipelago, 2012
DOI: 10.18739/a2t14tp3t
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015F, Central Arctic, 2015
DOI: 10.18739/a2tt4fs60
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2007H, Central Arctic, 2007
DOI: 10.18739/a2vt1gp67
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2012M, East Greenland Sea, 2012
DOI: 10.18739/a2ws8hk7d
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2004D, Central Arctic, 2004
DOI: 10.18739/a2xs5jg84
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2015C, Beaufort Sea, Arctic Ocean, 2015
DOI: 10.18739/a2zk55m0r
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2014F, Beaufort Sea, Arctic Ocean, 2014
DOI: 10.18739/a2zs2kc6d
title: Autonomous Ice Mass Balance Buoy Observations, Buoy 2011L, Central Arctic, 2011
DOI: 10.5063/f1cn7254
title: North Pacific salmon abundance, 1925-2015

description: Abundance estimates of wild and hatchery Pacific salmon Oncorhynchus spp. are important for evaluation of stock status and density-dependent interactions at sea. This data package includes total abundances of pink, chum, and sockeye salmon, reconstructed from catch and spawning abundance data for both Asia and North America. These data are in two main categories of salmon abundance estimates: (1) return (catch plus escapement) estimates of natural-origin and enhanced-origin salmon (numerical and biomass) by species and region, and (2) Total biomass estimates of mature and younger salmon by species and region (natural-origin and hatchery-origin combined). Most of the tables cover the period from 1952-2015. Longterm tables begin at 1925. The .csv files are plain text versions of the tables found in the original excel file. The excel file also contains additional information on how the datasets can be used. These data are described further in: Ruggerone, G.T., Peterman, R.M., Dorner, B., Myers, K.W. (2010). Magnitude and trends in abundance of hatchery and wild pink salmon, chum salmon, and sockeye salmon in the North Pacific Ocean. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science 2:306–328 (available at http://www.bioone.org/doi/full/10.1577/C09-054.1). They are also included as Supporting Information in Ruggerone, G.T. & Irvine, J.R. (2018). Numbers and Biomass of Natural- and Hatchery-Origin Pink Salmon, Chum Salmon, and Sockeye Salmon in the North Pacific Ocean, 1925–2015. Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science 10:152–168 (available at https://onlinelibrary.wiley.com/doi/full/10.1002/mcf2.10023). The dataset here is the same version as in the SI of Ruggerone & Irvine 2018, in the form of extracted .csv's.
DOI: 10.5066/p9hrzvq5
title: Concentrations of Pesticides, Pharmaceuticals, Organic Waste Indicators, and Volatile Organic Chemical Contaminants and Their Predicted Effects Potential in Wadeable Southeastern USA Streams

description: This dataset presents the results of 475 unique organic compounds collected from 54 wadeable streams within the Southeastern, USA, collected within 10 weeks during 2014. Maximum and median exposure conditions were evaluated in relation to watershed characteristics and for potential biological effects. This dataset contains the summary statistics (maximum and median concentrations)of detected compounds, as well as a summary of quality-assurance (blanks and replicates) samples. Also included are the statistical summaries as related to analyte specific contaminant detection/concentration data and site-specific land-use matrices, spearman-rank correlations, and ToxCast evaluations.
DOI: 10.5066/p9teiu3h
title: Landsat Image Mosaic Of Antarctica (LIMA)

description: In support of the International Polar Year (IPY 2007-2008), LIMA brings the coldest continent on Earth alive in greater detail than ever before through this virtually cloudless, seamless, and high resolution satellite view of Antarctica. The U.S. Geological Survey (USGS), the British Antarctic Survey (BAS), and the National Aeronautics and Space Administration (NASA), with funding from the National Science Foundation (NSF), created LIMA from more than 1,000 Landsat ETM+ scenes. As the first major scientific outcome of the IPY, LIMA truly fulfills the IPY goals. LIMA is an international effort, supports current scientific polar research, encourages new projects, and helps the general public visualize Antarctica and changes happening to this southernmost environment. Researchers and the general public can download LIMA and all of the component Landsat scenes at no charge. Pan to view the continent and zoom in to see the stunning details of this NaturalColor, Pan-Sharpened LIMA (bands 3, 2, 1). LIMA covers the entire continent except from the South Pole at 90 degrees south to 82.5 degrees south latitude, where Landsat has no coverage because of its nearpolar orbit. To provide a continental view, the image above has LIMA 3, 2, 1 overlaying the MODIS Mosaic of Antarctica (MOA). The opening view includes McMurdo Station, the largest research base in Antarctica. Located at the tip of Hut Point Peninsula on Ross Island, McMurdo has been continually operated by the United States of America since 1956. Ross Island is roughly 72 km (45 mi) across. The flat, white areas are the Ross Ice Shelf and other sea ice off the coast of Antarctica. Also visible are the Erebus Glacier Toungde, Koettlitz and Ferrar Glaciers, and the Royal Society Range.
DOI: 10.14469/hpc/4798
title: peracid epoxidation of propene, Def2-TZVPPD/DCM/M062X Reactant ionic starting point collapsing to non-ionic form during optimisation

description: Gaussian Calculation
DOI: 10.5281/zenodo.3940568
title: "The evolutionary history of Neandertal and Denisovan Y chromosomes" - Y chromosome capture designs

description: Coordinates of target capture regions and sequences of capture probes used in the paper "The evolutionary history of Neandertal and Denisovan Y chromosomes" by Petr et al. See the project's GitHub repository for more information: https://www.github.com/bodkan/archaic-ychr.
DOI: 10.5281/zenodo.3940567
title: "The evolutionary history of Neandertal and Denisovan Y chromosomes" - Y chromosome capture designs

description: Coordinates of target capture regions and sequences of capture probes used in the paper "The evolutionary history of Neandertal and Denisovan Y chromosomes" by Petr et al. See the project's GitHub repository for more information: https://www.github.com/bodkan/archaic-ychr.
DOI: 10.5281/zenodo.1489895
title: Örebro University basement SLAM dataset - Radar, Velodyne

description: Dataset recorded using the Taurob Tracker in Örebro University. The data includes a novel radar sensor and velodyne data.
DOI: 10.5281/zenodo.1489896
title: Örebro University basement SLAM dataset - Radar, Velodyne

description: Dataset recorded using the Taurob Tracker in Örebro University. The data includes a novel radar sensor and velodyne data.
DOI: 10.5063/f17w69fd
title: Taipei botanical garden avian diet survey,Taipei botanical garden,Taipei,Taiwan, August 2017 - August 2018.

description: 為了解台北植物園園區內鳥類可利用的食物資源分布狀況以及鳥類實際利用情形，於2017年至2018年每週一次於台北植物園全區進行穿越線調查，記錄路線上觀察到的各種鳥種以及其所取食的食物資源種類。
DOI: 10.5066/p9hdrzm0
title: Acute toxicity of sodium chloride and potassium chloride to a unionid mussel (Lampsilis siliquoidea) in water exposures-Data

description: Attributes regarding the acute toxicity of sodium chloride (NaCl) and potassium chloride (KCl) to larvae (glochidia) or juveniles of a unionid mussel (fatmucket, Lampsilis siliquoidea) at various water hardness and in the presence of other major ions.
DOI: 10.5063/f1348hm2
title: Salmon brood tables, Westward Region, Alaska

description: Brood tables, also called run reconstructions, utilize annual estimates of the total run (commercial catch plus escapement), and samples of ages, to estimate the number of recruits per age class. These data are useful for salmon biologists to understand salmon productivity and salmon life histories. These data can come in a number of different formats, but generally follow the pattern of: rows for each brood year, and columns for the estimated number of fish in each age class. This dataset consists of reformated brood tables from the Westward Region of Alaska. These datasets were gathered as part of the State of Alaskan Salmon and People project (https://alaskasalmonandpeople.org/). Age classes are given in European Notation, where the first number is the number of winters spent in freshwater before going to sea (1 winter in freshwater = age-1.X), and the second number is the number of winters spent at sea (3 winters at sea = age-X.3). For chinook salmon, only total age (age X) is given.
DOI: 10.5063/f1445jq0
title: Native place names and language boundaries, Alaska

description: The native place names and language boundaries are a revised version of those established in the "Native Peoples and Languages of Alaska" map created by Michael E. Krauss (1974, revised 1982). The revised version was digitized and stored in GIS by Krauss et al. (2011). This data package includes the GIS data as a zipped ESRI file geodatabase (ipla.gdb.zip), which includes language boundaries and place names. This package also includes a script (NativePlaceNames_Regions.Rmd) detailing how to assign SASAP region names to the native places as well as the output .csv file (NativePlaceNames.csv). Citations: Krauss, Michael. 1974 Native Peoples and Languages of Alaska. (Revised 1982). Fairbanks: Alaska Native Language Center. Krauss, Michael, Gary Holton, Jim Kerr, and Colin T. West. 2011. Indigenous Peoples and Languages of Alaska. Fairbanks and Anchorage: Alaska Native Language Center and UAA Institute of Social and Economic Research.
DOI: 10.5063/f16w9891
title: Salmon hatchery return data, 1975-2016

description: This dataset contains salmon return data by release site to Alaska fisheries enhancement projects, as reported by operators. More details on this dataset can be found in the Alaska Fisheries Enhancement Annual Report, 2016 (http://www.adfg.alaska.gov/FedAidPDFs/RIR.5J.2017.04.pdf). This harvest data is simply how many fish were harvested by a hatchery operator in their harvest area, and is not necessarily the number of hatchery-origin fish in that harvest. The original data is contained in ADFG_Obtained_AKReturns.xlsx. The included RMarkdown script (Hatchery_returns_reformatting.Rmd) reformats these data, and assigns region information based on the release site used by the hatchery. The reformatted file is "hatchery_returns.csv". The "Project" column generally denotes the release site. "CatchType" indicates what kind of harvest project the harvested fish were a part of. This distinguishes both by sector (commercial, subsistence, sport fish), gear (for commercial sector fish), and fish caught for brood stock or cost-recovery. In some early years, the harvest was not broken out by gear, and only an estimate for generalized commercial catch was derived - these are assigned the CatchType of "commerical other." A CatchType of "other" indicates that the type of catch did not fit easily into the other categories. Negative numbers in the catch values for this dataset are real. Sometimes when a sample of fish is taken at the hatchery or the escapement to a system where a hatchery is located, not all the fish may originate from that hatchery. The fish may be wild fish from the system or hatchery fish from another hatchery. The negative numbers are there to reduce the total of hatchery fish that were counted in the brood stock or escapement by those non-hatchery fish, where non-hatchery fish are known to exist in the harvest.
DOI: 10.5063/f1m61hhd
title: Summary of Pacific Salmon Escapement Goals in Alaska with a Review of Escapements from 2007 to 2015

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 2007 to 2017." 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."
DOI: 10.5063/f1vq30w7
title: Daily salmon escapement counts from the OceanAK database, Alaska, 1921-2017

description: The number of mature salmon migrating from the marine environment to freshwater streams is defined as escapement. 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. Escapement data are collected in a variety of ways. Stationary projects utilize observers stationed along freshwater corridors who count salmon as they pass upriver through weirs or past elevated towers. Sonar equipment placed in the river can also give a stationary escapement count. These counts usually represent a sample, and are expanded to represent a 24h period. Escapement data can also be collected using aerial surveys, where observers in an aircraft provide an index to estimate escapement. In general, escapement counts do not represent total abundance, but instead an index of abundance. Surveys are usually timed to coincide with peak spawning activity, generally in the summer, but in the case of Coho salmon in the fall as well. This dataset contains salmon escapement data extracted from the Alaska Department of Fish and Game's OceanAK database, and contains data from multiple regions in Alaska.
DOI: 10.5063/f10c4t14
title: Daily escapement counts, Bristol Bay, Alaska, 1955-2017

description: The number of mature salmon migrating from the marine environment to freshwater streams is defined as escapement. Escapement data are the enumeration of these migrating fish as they pass upstream, and represent the total abundance of spawning salmon. These data are important for fisheries management, since most salmon harvest occurs in freshwater rivers during this migration. This dataset contains escapement data for sockeye salmon from the Bristol Bay region of Alaska in the years 1955-2017.
DOI: 10.5063/f1bp0119
title: Alaska Sport Fishing Licenses, 1993-2016

description: This dataset contains information about sport fishing licenses issued by the Alaska Department of Fish and Game from 1993-2016. A sport fishing license is mandatory for any resident over the age of 18 or nonresident over the age of 16 participating in sport or personal fishing activities in fresh or marine waters. Licenses are valid from the date of purchase through December 31st of the year of purchase. Data is collected via the application process and includes: license year, type code, license number, city, state, zip code, country, sex, citizenship, vendor number, class code, and issue date. This package includes the combined, reformatted data file (SportFishingLicense_Data.csv); the original data as csv files (1993.csv-2016.csv); and the reformatting script (SportFishingLicenses_DataReformat_Script.R).
DOI: 10.5063/f1gf0rr7
title: Alaska commercial salmon fishery ex-vessel prices, 1984-2015

description: Ex-vessel prices are post-season adjusted price per pound for the first purchase of a commercial harvest. Ex-vessel values are weighted average estimates based on best available data for administrative area, and applied to the administrative area as a whole. Here, ex-vessel prices for all five species of salmon (pink, sockeye, chinook, chum, and coho) are included, spanning from 1984 to 2015. Data are included from all of Alaska and are presented annually by region, including the following regions: Alaska Peninsula, Bristol Bay, Chignik, Cook Inlet, Kodiak, Kotzebue, Kuskokwim, Norton Sound, Prince William Sound, Southeast, and Yukon. The Prince William Sound administrative area includes Copper River.