cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10078932
title: Data Product for "Toward a Cenozoic history of atmospheric CO2"

description: These data were vetted and revised from published paleo-CO2 data (original estimates archived at https://zenodo.org/uploads/8052599) by an international group of proxy experts supported through an NSF-funded Research Coordination Network. It brings together paleo-CO2 reconstruction data from terrestrial and marine archives, and the compilation includes estimates derived from multiple proxies including Phytoplankton, Boron, Stomatal Frequencies, Leaf Gas Exchange, Liverworts, Land Plant d13C, Paleosols, and Nahcolite. Data are visualized in an interactive product plot made available on the Paleo-CO2 project web page at (https://www.paleo-co2.org) and are also archived in the NCDC database (https://www.ncei.noaa.gov/pub/data/paleo/climate_forcing/trace_gases/Paleo-pCO2/product_files/). 
description: The geological record encodes the relationship between climate and atmospheric carbon dioxide (CO2) over long and short timescales, as well as potential drivers of evolutionary transitions. However, reconstructing CO2 beyond direct measurements requires the use of paleo-proxies and herein lies the challenge, as proxies differ in their assumptions, degree of understanding, and even reconstructed values. Here we critically evaluate, categorize, and integrate available proxies to create a high-fidelity and transparently constructed atmospheric CO2 record spanning the past 66 million years. This provides clearer evidence for higher Earth System Sensitivity in the past and for the role of CO2 thresholds in biological and cryosphere evolution.
DOI: 10.5281/zenodo.10402783
title: Data Product for "Toward a Cenozoic history of atmospheric CO2"

description: These data were vetted and revised from published paleo-CO2 data (original estimates archived at https://zenodo.org/uploads/8052599) by an international group of proxy experts supported through an NSF-funded Research Coordination Network. It brings together paleo-CO2 reconstruction data from terrestrial and marine archives, and the compilation includes estimates derived from multiple proxies including Phytoplankton, Boron, Stomatal Frequencies, Leaf Gas Exchange, Liverworts, Land Plant d13C, Paleosols, and Nahcolite. Data are visualized in an interactive product plot made available on the Paleo-CO2 project web page at (https://www.paleo-co2.org) and are also archived in the NCDC database (https://www.ncei.noaa.gov/pub/data/paleo/climate_forcing/trace_gases/Paleo-pCO2/product_files/). 
description: The geological record encodes the relationship between climate and atmospheric carbon dioxide (CO2) over long and short timescales, as well as potential drivers of evolutionary transitions. However, reconstructing CO2 beyond direct measurements requires the use of paleo-proxies and herein lies the challenge, as proxies differ in their assumptions, degree of understanding, and even reconstructed values. Here we critically evaluate, categorize, and integrate available proxies to create a high-fidelity and transparently constructed atmospheric CO2 record spanning the past 66 million years. This provides clearer evidence for higher Earth System Sensitivity in the past and for the role of CO2 thresholds in biological and cryosphere evolution.
DOI: 10.5281/zenodo.14537923
title: Data Product for "Toward a Cenozoic history of atmospheric CO2"

description: These data were vetted and revised from published paleo-CO2 data (original estimates archived at https://zenodo.org/uploads/8052599) by an international group of proxy experts supported through an NSF-funded Research Coordination Network. It brings together paleo-CO2 reconstruction data from terrestrial and marine archives, and the compilation includes estimates derived from multiple proxies including Phytoplankton, Boron, Stomatal Frequencies, Leaf Gas Exchange, Liverworts, Land Plant d13C, Paleosols, and Nahcolite. Data are visualized in an interactive product plot made available on the Paleo-CO2 project web page at (https://www.paleo-co2.org) and are also archived in the NCDC database (https://www.ncei.noaa.gov/pub/data/paleo/climate_forcing/trace_gases/Paleo-pCO2/product_files/). 
description: The geological record encodes the relationship between climate and atmospheric carbon dioxide (CO2) over long and short timescales, as well as potential drivers of evolutionary transitions. However, reconstructing CO2 beyond direct measurements requires the use of paleo-proxies and herein lies the challenge, as proxies differ in their assumptions, degree of understanding, and even reconstructed values. Here we critically evaluate, categorize, and integrate available proxies to create a high-fidelity and transparently constructed atmospheric CO2 record spanning the past 66 million years. This provides clearer evidence for higher Earth System Sensitivity in the past and for the role of CO2 thresholds in biological and cryosphere evolution.
DOI: 10.5281/zenodo.14537863
title: Travel times by car from La Calera to Bogotá (Colombia)

description: Data set with a sample of travel times by car (morning commute) from the coordinate (latitude,longitude)=(4.754425222968817, -73.95268680747647) located in La Calera (Cundinamarca, Colombia) to the coordinate (latitude,longitude)=(4.603220503060856, -74.06511047660112) located in Bogotá (Colombia). The data set is a CSV file with ";" as the separator of the columns (variables). The data set contains three columns labeled in the first row of the data set: 



Obs(n):  observation number;   

Date(dd-mm-yyyy): collection date of the data point in the format dd-mm-yyyy; and

Time(min): commute time in minutes.
DOI: 10.5281/zenodo.14537864
title: Travel times by car from La Calera to Bogotá (Colombia)

description: Data set with a sample of travel times by car (morning commute) from the coordinate (latitude,longitude)=(4.754425222968817, -73.95268680747647) located in La Calera (Cundinamarca, Colombia) to the coordinate (latitude,longitude)=(4.603220503060856, -74.06511047660112) located in Bogotá (Colombia). The data set is a CSV file with ";" as the separator of the columns (variables). The data set contains three columns labeled in the first row of the data set: 



Obs(n):  observation number;   

Date(dd-mm-yyyy): collection date of the data point in the format dd-mm-yyyy; and

Time(min): commute time in minutes.
DOI: 10.5281/zenodo.14537890
title: MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification

description: These are the two datasets -- EMBER Class and AZ Class to reproduce the results of the paper ``MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification", accepted to be published at the The 39th Annual AAAI Conference on Artificial Intelligence (AAAI) 2025.



EMBER 2018 datasetWe use the 2018 EMBER dataset, known for its challenging classification tasks, focusing on a subset of 337,035 malicious Windows PE files labeled by the top 100 malware families, each with over 400 samples. Features include file size, PE and COFF header details, DLL characteristics, imported and exported functions, and properties like size and entropy, all computed using the feature hashing trick.

AZ-ClassThe AZ-Class dataset contains 285,582 samples from 100 Android malware families, each with at least 200 samples. We extracted Drebin features (Arp et al.2014) from the apps, covering eight categories like hardware access, permissions, API calls, and network addresses.
DOI: 10.5281/zenodo.14537891
title: MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification

description: These are the two datasets -- EMBER Class and AZ Class to reproduce the results of the paper ``MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification", accepted to be published at the The 39th Annual AAAI Conference on Artificial Intelligence (AAAI) 2025.



EMBER 2018 datasetWe use the 2018 EMBER dataset, known for its challenging classification tasks, focusing on a subset of 337,035 malicious Windows PE files labeled by the top 100 malware families, each with over 400 samples. Features include file size, PE and COFF header details, DLL characteristics, imported and exported functions, and properties like size and entropy, all computed using the feature hashing trick.

AZ-ClassThe AZ-Class dataset contains 285,582 samples from 100 Android malware families, each with at least 200 samples. We extracted Drebin features (Arp et al.2014) from the apps, covering eight categories like hardware access, permissions, API calls, and network addresses.
DOI: 10.34740/kaggle/dsv/10257742
title: Balochi Language to English Translation Dataset
DOI: 10.15468/dl.sywqqc
title: Occurrence Download

description: A dataset containing 29 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Brachyplatystoma rousseauxii (Castelnau, 1855))",
 "BasisOfRecord is one of (Human Observation, Observation, Machine Observation, Living Specimen, Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than or equal to 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 },
 "OccurrenceStatus is one of (Present)"
 ]
}

 The dataset includes 29 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044624-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e191743
title: Data and code for: The Ends of 27 Big Depressions

description: How did countries recover from the Great Depression? In this paper, we explore the argument that leaving the gold standard helped by boosting inflationary expectations, lowering real interest rates, and stimulating interest-sensitive expenditures. We do so for a sample of 27 countries, using modern nowcasting methods and a new dataset containing more than 230,000 monthly and quarterly observations for over 1,500 variables. In those cases where the departure from gold happened on well-defined dates, inflationary expectations clearly rose in the wake of departure. IV, diff-in-diff, and synthetic matching techniques suggest that the relationship is causal.
DOI: 10.3886/e191743v1-162101
title: Data and code for: The Ends of 27 Big Depressions

description: How did countries recover from the Great Depression? In this paper, we explore the argument that leaving the gold standard helped by boosting inflationary expectations, lowering real interest rates, and stimulating interest-sensitive expenditures. We do so for a sample of 27 countries, using modern nowcasting methods and a new dataset containing more than 230,000 monthly and quarterly observations for over 1,500 variables. In those cases where the departure from gold happened on well-defined dates, inflationary expectations clearly rose in the wake of departure. IV, diff-in-diff, and synthetic matching techniques suggest that the relationship is causal.
DOI: 10.5281/zenodo.14291348
title: Sediment elemental X-ray fluorescence record at IODP Site U1475 during the early Pliocene

description: This dataset documents the early Pliocene elemental composition of Aluminum (Al), Potassium (K), Calcium (Ca), and Iron (Fe) in sediments from IODP Site U1475, drilled on the southwestern flank of the Agulhas Plateau in the southwestern Indian Ocean during IODP Expedition 361: South African Climate (30 January to 31 March 2016). The data were obtained via X-ray fluorescence (XRF) analysis using a third-generation Avaatech Core Scanner equipped with a Canberra X-PIPS SDD, Model SXD 15C-150-500 X-ray detector at the IODP JRSO XRF Core Scanning Facility at the Texas A&M University (USA). Core sections were prepared by scraping and covering with 4 µm-thick Ultralene film to ensure clean measurement surfaces. XRF measurements were taken every 3 cm in three separate runs with generator settings of 10 kV (Al to Fe detection), 30 kV (Rb, Sr, and Zr detection), and 50 kV (for Ba). This dataset focuses on reporting Al, Ca, Sr, and K ratios.
DOI: 10.15468/dl.jrgx77
title: Occurrence Download

description: A dataset containing 31595 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Setophaga dominica (Linnaeus, 1766)"
 ]
}

 The dataset includes 31595 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044625-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48577/jpl.opr9ab
title: Collection of files utilized and recorded as part of the pre-flight calibration of PIXL for X-ray fluorescence elemental quantification

description: This dataset includes all the files utilized or produced as part of the pre-flight elemental calibration performed on the X-ray system of NASA’s Planetary Instrument for X-ray Lithochemistry (PIXL) (Allwood et al., 2020). PIXL is a focused-beam X-ray fluorescence spectrometer (XRS) installed on the arm of the Mars 2020 Perseverance rover. NASA has long relied upon XRS’s to deliver quantified chemical compositional information of typical inorganic rock-forming elements (atomic number: Z ≥ 11). New to this generation of spectrometer, PIXL is capable of raster scanning its focused beam to produce high-spatial resolution elemental map images of rock textures. To ensure that PIXL would be capable of quantifying elemental concentrations, a calibration procedure was conducted pre-flight (Heirwegh et al., 2024) on the flight hardware. Spectrum files acquired from PIXL measurements performed on 30 calibration target materials were utilized in this procedure along with the open sourced PIXL Quantitative XRF software (PIQUANT) (Heirwegh et al., 2022, Elam et al., 2022). Details of this calibration are recorded elsewhere (Heirwegh et al., 2024). A ReadMe file that accompanies this dataset describes the basic structure of the file set and gives and abridged version of the flight calibration procedure and how the files in this dataset were involved in the calibration. The dataset includes raw recorded and summed spectrum files, and all files used as input to, and generated as output by, the PIQUANT software. The sharing of this dataset on the JPL Open Repository serves the purpose of providing a primary means to a make these data permanently available to the public. A. C. Allwood, L. A. Wade, M. C. Foote, et al., PIXL: Planetary Instrument for X-ray Lithochemistry Space Sci. Rev. 216 (2020) 134. doi:10.1007/s11214-020-00767-7 C. M. Heirwegh, W. T. Elam, L. P. O’Neil, K. P. Sinclair, A. Das, The Focused Beam X-ray Fluorescence Elemental Quantification Software Package PIQUANT, Spectrochim. Acta B, 196 (2022) 106520. doi:10.1016/j.sab.2022.106520. W. T. Elam, C. M. Heirwegh, PIQUANT (Version 3.2.11) [Open source computer software] Zenodo. (2022) doi:10.5281/zenodo.6959225 C. M. Heirwegh, W. T. Elam, Y. Liu, C. Hummel, A. Das, A. C. Allwood, L. G. Armstrong, N. Bacop, K. P. Sinclair, L. P. O’Neil, L. A. Wade, M. C. Foote, M. E. Sondheim, R. W. Denise, P. R. Lawson, J. H. Kawamura, M. H. Au, A. Kitiyakara, R. A. Romero, J. A. Hurowitz, B. C. Clark III, G. R. Rossman, M. S. Anderson, Pre-Flight Calibration of PIXL for X-ray Fluorescence Elemental Quantification (2024) arXiv:2402.01544 [physics.app-ph].
DOI: 10.5066/p1z44umm
title: Deep learning classification of landforms from lidar-derived elevation models in the glaciated portion of the northern Delaware River Basin of New Jersey, New York, and Pennsylvania

description: The Delaware River Basin (DRB) covers portions of five states (Delaware, Maryland, New Jersey, New York, and Pennsylvania) and several geologic provinces, encompassing much of the complex geology of the Mid-Atlantic region. This data release focuses on the recently glaciated northern DRB, which includes portions of New Jersey, New York, and Pennsylvania. Groundwater storage is conceptualized to be greatest in the glacial surficial aquifers in the upper part of the basin, thus characterization of this critical zone is of primary importance for USGS Next Generation Water Observing System (NGWOS) modeling of baseflow to the upper Delaware River. In support of this effort, we trained four deep learning models to classify surficial materials in unique physiographic areas of the northern DRB, using previously published surficial geologic maps as training data. First, we compiled existing digital surficial geologic map data at various scales (1:100,000 to 1:24,000), with high-resolution data taking precedent where available. Next, we generalized the compiled map data to the following categories: alluvium, anthropogenic, bedrock, colluvium, drumlins, glaciofluvial, glaciolacustrine (coarse), ice-contact stratified, marsh, moraine, pre-Illinoian glacial, till, and water bodies. We then compiled lidar data for the entire northern DRB and generated a derivative RGB composite raster to facilitate the training and running of convolutional neural networks (Odom and Doctor, 2023; Maxwell et al., 2023). The resultant geologic data and imagery were then clipped to four distinct physiographic areas: "Eastern Valley and Ridge", "Northern Glaciated Plateau", "Terminal Moraine Plateau", & "Western Valley and Ridge". We then trained a DeepLabV3+ pixel classification model for each region, reserving 10% of geologic training polygons for validation during the training process. The resultant models, which had training times ranging from 21-41 hours, featured F1 values ranging from 0.85-0.91 at the final epoch of training. External validation using geologic maps likewise demonstrated satisfactory performance. The trained models were then run on their respective physiographic areas, and the results joined in a mosaic classification of the northern DRB.

References
Maxwell, A.M., Odom, W.E., Shobe, C.M., Doctor, D.H., Bester, M.S., Ore, T.M, 2023. Exploring the Influence of Input Feature Space on CNN-Based Geomorphic Feature Extraction From Digital Terrain Data. Earth and Space Science, 10. https://doi.org/10.1029/2023EA002845
Odom, W.E., Doctor, D.H., 2023. Rapid estimation of minimum depth-to-bedrock from lidar leveraging deep-learning-derived surficial material maps. Applied Computing and Geosciences, 18. https://doi.org/10.1016/j.acags.2023.100116
DOI: 10.15468/dl.dj4kg6
title: Occurrence Download

description: A dataset containing 18898 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Setophaga pitiayumi (Vieillot, 1817)"
 ]
}

 The dataset includes 18898 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0044627-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25983/2263365
title: Expanded genetic variation (SNP) and phenomics (image based) dataset for Populus trichocarpa

description: The image dataset consists of 11,791 images representing 1,219 genotypes of Populus trichocarpa undergoing in planta regeneration. Genotypes were imaged with a median of four weekly timepoints and a median of two replicates each. A representative and diverse subset of 249 images was annotated using the IDEAS annotation interface (ideas.eecs.oregonstate.edu) and these annotated images were used to train a deep semantic segmentation model (PSPNet), which was deployed for inference over the entire dataset. Annotated classes include specific stages of regeneration (callus and shoot) in addition to unregenerated plant material and background. Statistics of relative tissue area were extracted and used for downstream genetic association mapping in a genome-wide association study. The SNP dataset consists of over 40 million single-nucleotide polymorphisms across 1,323 wild accessions of Populus trichocarpa
DOI: 10.15468/dl.maa79t
title: Occurrence Download

description: A dataset containing 764 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Sphenisciformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-60 -30,-30 -30,-30 0,-60 0,-60 -30))"
 ]
}

 The dataset includes 764 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061623-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48420/30296533
title: Supporting File 7 - Rb-Sr Dating of Enstatite Chondrites - Standards Summary

description: Results from standards used during in situ Rb-Sr dating of enstatite chondrites by LA-ICP-MS .
DOI: 10.48420/30296533.v1
title: Supporting File 7 - Rb-Sr Dating of Enstatite Chondrites - Standards Summary

description: Results from standards used during in situ Rb-Sr dating of enstatite chondrites by LA-ICP-MS .
DOI: 10.15468/dl.4zj7xm
title: Occurrence Download

description: A dataset containing 832 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ranunculus pygmaeus Wahlenb.",
 "Year 1981-2010"
 ]
}

 The dataset includes 832 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002079-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nvp9y4
title: Occurrence Download

description: A dataset containing 832 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ranunculus pygmaeus Wahlenb.",
 "Year 1981-2010"
 ]
}

 The dataset includes 832 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002076-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ffjfne
title: Occurrence Download

description: A dataset containing 832 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "CoordinateUncertaintyInMeters 0.0-1000.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ranunculus pygmaeus Wahlenb.",
 "Year 1981-2010"
 ]
}

 The dataset includes 832 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002080-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yy7pgx
title: Occurrence Download

description: A dataset containing 36515 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Taxon occurrence data for the FungalRoot database"
 ]
}

 The dataset includes 36515 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002077-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.