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35 results for “geoscience”
Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors: V4.NA.02.MAPLE
<p>We estimate ground-level fine particulate matter (PM<sub>2.5</sub>) total and compositional mass concentrations over North America by combining Aerosol Optical Depth (AOD) retrievals from the NASA MODIS, MISR, and SeaWIFS instruments with the GEOS-Chem chemical transport model, and subsequently calibrated to regional ground-based observations of both total and compositional mass using Geographically Weighted Regression (GWR) as detailed in the provided reference for V4.NA.02. V4.NA.02.MAPLE further modified the V4.NA.02 GWR method with additional developments as part of the MAPLE (Mortality–Air Pollution Associations in Low-Exposure Environments) project. This adjustment was of particular value over low concentrations. The GWR method of individual components remains unchanged from V4.NA.02, but are provided are percentages to ensure mass closure and recommended to be applied to the V4.NA.02.MAPLE total PM<sub>2.5</sub>.</p> <p>Annual datasets are provided in NetCDF [.nc]. Gridded files use the WGS84 projection. Compositional estimates are provided for sulfate (SO4), nitrate (NO3), ammonium (NH4), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS). Percentages are denoted with a ‘p’ after component identifiers within filenames. A slight change in file name has been included for 2017, corresponding to minor internal changes compared to earlier years. Overall, however, the dataset is consistent throughout its entire time period and can be appropriately used for trend analysis.</p> <p><strong>Reference:</strong><br> van Donkelaar, A., R. V. Martin, et al. (2019). <strong>Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors.</strong> Environmental Science & Technology, 2019, doi:10.1021/acs.est.8b06392.</p>
Catalog of synthetic seismic records from mineral physics and travel-time tables from Waszek et al., 2021, Nature Geoscience
<p>This release is associated with the accepted publication in Nature Geoscience:</p> <p>Waszek L., Tauzin B., Schmerr N., Ballmer M. and Afonso J.C. A poorly mixed mantle transition zone and its thermal state inferred from seismic waves. Nature Geoscience, 2021.</p> <p>This dataset must be used in conjunction with the NoLimit software package (https://zenodo.org/record/5512805).</p> <p>Both the software and dataset allow the prediction of synthetic seismic waveforms for SS and PP-precursors from mineral physics models, as well as their processing for reconstructing the surface of seismic boundaries associated with major mineralogical phase transitions in the Earth’s mantle (namely, the 410-km and 660-km depth discontinuities).</p> <p>For technical reasons (storage and quick access), the catalog is downsampled with respect to the one in Waszek et al. (2021), and it is provided with the HDF5 format. For more advanced applications such as changing mantle composition, or generating waveforms for deeper earthquakes, please contact Benoit Tauzin (benoit.tauzin@univ-lyon1.fr) and Lauren Waszek (lauren.waszek@jcu.edu.au).</p> <p>The dataset includes:</p> <p>* A fixed mantle composition, which is a mechanical mixture of basalt and harzburgite with a fraction of basalt f=0.2.<br> * A downsampled catalog of synthetic waveforms for event depths between 0 and 80 km by step of 10 km (enough for reproducing the processing of observed SS and PP precursors waveforms).<br> * Adiabatic temperature gradients with potential temperature Tpot between 1200 and 2100 K by step of 100 K.</p> <p>This catalog and associated travel-time tables will allow any user to generate synthetic waveforms for any moment tensor, and events within the pre-defined depth interval.<br> </p> <p><strong>How to cite this material?</strong></p> <p>Any use of the datasets or software must refer to:</p> <p>The reference paper: Waszek L., Tauzin B., Schmerr N., Ballmer M., Afonso J.C. A poorly mixed mantle transition zone and its thermal state inferred from seismic waves. Nature Geoscience. 2021.<br> <br> Software: Tauzin, Benoit, & Waszek, Lauren. (2021). NoLiMit MATLAB package v1.0. Non-Linear Bayesian partition Modeling of the Earth's Mantle Transition zone (Version 1). Zenodo. https://doi.org/10.5281/zenodo.5512805<br> <br> Datasets: Tauzin, Benoit, Waszek, Lauren, & Afonso, Juan Carlos. (2021). Catalog of synthetic seismic records from mineral physics and travel-time tables from Waszek et al., 2021, Nature Geoscience (Version 1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5512035</p>
Svalbard Rock Vault - liberating vintage geoscience data from Svalbard
<p>The Svalbard Rock Vault project (www.svalbox.no/srv) has the main objective to recover vintage geoscientific data from Svalbard's geoscientific exploration, in particular the overlooked petroleum exploration onshore Svalbard. Eighteen boreholes were drilled from 1961 to 1994 but data are only available as fragments. These data are systematically collected, digitized and made available for research purposes by the Svalbox team at the University Centre in Svalbard. </p> <p>This initial data set publication includes three overview spreadsheets:</p> <p>1) An overview of the archive material of Norsk Polar Navigasjon (NPN), a private company that was involved in many of the exploration boreholes. The physical archive is available at UNIS and scans are available upon request. </p> <p>2) An overview of the archive material related to the Tromsøbreen II exploration borehole, drilled in 1988. The physical archive is in Lund, Sweden, and most of it has been digitized by UNIS and scans are available upon request. </p> <p>3) An overview of the data available from the eighteen exploration boreholes, including wireline log data, reports and analyses. The data are also integrated in a Petrel project available at UNIS. </p> <p>More data will be added as they are (re-)discovered. </p>
Geoscience undergraduate major course requirements
<p>This data compilation contains course requirements for undergraduate geoscience majors in Earth Science departments at 50 R1 universities in the United States. The authors of this compilation (Ken Ferrier, Eva Golos, and Marianne Haseloff at the University of Wisconsin-Madison) collected these data in March-April 2024 (n = 966 courses in total) from each department’s publicly accessible webpage. These data are organized in four tables, which contain data on the geoscience courses and credits required inside the home department and the cognate courses and credits required outside the home department (e.g., Math, Physics, Chemistry).</p>
Rainbow colour maps remain widely used in the geosciences
<p>This dataset is the result of a systematic survey of scientific publication to investigate the extent to which rainbow colour maps are used in geoscience publications. Papers were surveyed from five journals - Earth System Dynamics (ESD), Geophysical Research Letters (GRL), Ocean Science (OS), Solid Earth (SE) and The Cryosphere (TC) - for the years 2005, 2010, 2015 and 2020.</p> <p>The final data set includes the pre-existing Stoelzle and Stein (2021) survey data for HESS, which is independently available at https://doi.org/10.5281/zenodo.5145746 (Stoelzle, 2021).</p> <p>All papers (n=2638) were classified according to the type of colour encoding used.</p> <p>year = year of publication (YYYY)<br> title = full paper title<br> authors = list of authors seperated by semi-colon<br> n_authors = number of authors<br> col_code = color-issue classification (see below)<br> volume = Journal volume<br> start_page = first page of paper (where available)<br> end_page = last page of paper (where available)<br> base_url = url to access the paper on the journal website <br> filename = file name of the PDF version of the paper</p> <p>Color classification is stored in the col_code variable with:</p> <p>0 = Colour visualisations with no colour issues<br> 1 = At least one visualisation with red-green issues<br> 2 = At least one visualisation with a rainbow colour map<br> bw = Black and white paper</p>
Computational Implementation of "Uncoupling electrokinetic flow solutions", published in Mathematical Geosciences
<p>This dataset includes Python and Mathematica scripts used to generate figures, and images used in the Mathematical Geosciences (MG) manuscript "Uncoupling Electrokinetic Flow Solutions" by Kuhlman and Malama (2020).</p> <p>Python scripts implementing eigenvalue uncoupling approach for differential equations governing 1D cylindrically symmetric electrokinetic flow problem (i.e., flow to a pumping well).</p> <ol> <li>mpmath python script (recombine-expint.py) implementing Theis "type curve" solution for an infinite domain (Figures 1-3 in MG manuscript)</li> <li>fipy python script (compare-via-fipy.py) and plotting script (plot_fipy_results.py) showing a finite-volume fully coupled solution for a similar finite domain for comparison against eigenvalue uncoupling approach (Figure 4 in MG manuscript). Also includes two shell scripts for driving python scripts for a variety of inputs.</li> </ol> <p>mathematica script (periodic-1D-steady-state-type-1.nb) for solving the algebra associated with the governing equations and plotting figures for analytical solution of periodically driven 1D solution (i.e., laboratory sinusoidal streaming potential and electroosmosis; Figures 4-9 in MG manuscript).</p> <p> </p>
geoscience-semantics: First release--stripped down version
<p>Stripped down version of geoscience semantic models "review"</p>
Figure 1 in History and development of ABCDEFG: a data standard for geosciences
Figure 1. Simplified overview of the schema extension EFG. Given are the relationships among EFG components and between EFG components and the ABCD schema. EFG elements are given in yellow and elements originating from ABCD in green.
Making predictions for geoscience and climate policy workshop results
<p>This provides the data files and basic plotting and interpretation for results for predictions made in a series of workshops run in 2024, with predictions made for 2024, 2050, 2100 and 5o years after net zero. The workshop results are found in the files "EGU_Prediction-making workshop questions cleaned.csv" and "RGS_...", the code expects these to be in a folder denoted "data". More details can be found in the README.txt. Updates to this codebase can be found in <a href="https://github.com/Rlamboll/ClimatePredictionsWorkshop">https://github.com/Rlamboll/ClimatePredictionsWorkshop.</a></p> <p> </p>
Reproducibility package for: Badges for Geoscience Containers
<p>This repository contains demo data and software for research in using badges to improve discovery for scholarly publications in the geosciences. The web service "badger" provides an HTTP API for retrieving several types of badges based on a publications digital object identifier (DOI). The "extender" client integrates with the web browser and enhances existing platforms for discovery of publications with badges independent of the platforms code.</p> <p>Included in the archive are the source code of the required web services and client as well as ready to use Docker containers (including database and required web service with test data) to reproduce the results with minimal system requirements.</p> <p>Background on the project is provided in a peer-reviewed short paper from the AGILE conference 2019, <a href="https://doi.org/10.31223/osf.io/xtsqh">https://doi.org/10.31223/osf.io/xtsqh</a> , and in the blog post <a href="https://o2r.info/2017/09/12/reproducible-research-badges/">https://o2r.info/2017/09/12/reproducible-research-badges/</a>.</p> <p>For reproduction, follow the instructions in README.md and Makefile.and means to download the required software to enhance research websites with badges for reproducible research papers.</p>
Survey data on the perceptions and impacts of gender inequality in the geosciences
<p>The data stem from an anonymous, online survey conducted from March 25 to April 11, 2018 using Google Surveys. The link to the survey was distributed by the authors via emails and social media (Twitter and Facebook). Among the 1415 participants, we analyzed the responses of those who identified as either female or male (leaving out seven non-binary respondents due to the small sample size), and currently work in academia (i.e., universities or research institutes, including emeritus and adjunct professors, research support staff, and research assistants). We thereby retained 1220 respondents with a gender distribution of 67.0% female to 33.0% male survey participants.</p> <p>Based on this survey, we published to following freely accessible article: Popp, A. L.; Lutz, S. R.; Khatami, S.; van Emmerik, T. H. M.; Knoben, W. J. M. (2019) A global survey on the perceptions and impacts of gender inequality in the earth and space sciences, <em>Earth and Space Science</em>, 6(8), 1460-1468, <a href="http://doi.org/10.1029/2019EA000706">doi:10.1029/2019EA000706</a>.</p>
Dataset for Nature Geoscience: Acceleration of a large deep-seated tropical landslide due to urbanisation feedbacks
<p>This archive file contains datafiles used in the manuscript: 'Acceleration of a large deep-seated tropical landslide due to urbanisation feedbacks' [https://doi.org/10.1038/s41561-022-01073-3]. It contains historical aerial orthomosaics, UAS DSM and orthomosaics, shapefiles, deformation maps, etc. for Funu landslide.</p>
Case study on an integrated interoperable metadata model for geoscience information resources
<p>An integrated metadata schema was created to promote interoperability and to characterize historically collected geoscience data. The metadata standard describes the steps taken to develop a switching‐across methodology that allows geoscience metadata standards (ISO 19115, CSDGM, ANZLIC and INSPIRE) to communicate with one another. We also demonstrated a real example of one of the switching‐across that was created. A representative metadata schema was created using items from harmonization standards that might be optimally mapped. Semantic interoperability allows users to access equivalent classes across several metadata standards in a uniform and consistent rule. It also tries to provide fundamental aspects that might characterize acquisition information to enhance data reuse and current metadata standards for data preservation and distribution.</p> <p>This dataset contains 5 data and contains the content standard of each of the four metadata schema and the metadata information of integrated metadata schema.</p> <ul> <li>data_ISO19115.xlsx: Core level of metadata elements for geographic resources of ISO 19115</li> <li>data_CSDGM.xlsx: Content Standard for Digital Geospatial Metadata of CSDGM</li> <li>data_INSPIRE.xlsx: Content Standard of INSPIRE metadata modeldata_ANZLIC.xlsx: Content Standard of ANZLIC Metadata Profile</li> <li>data_integrated model.xlsx: metadata class and their elements in the integrated interoperable metadata model</li> </ul>
Berends_etal_2019_Geosciences_Supplement
<p>Supplement to the Berends et al. (2019) article in Geosciences.<br> Results from three separate simulations of the last 3.6 Myr with an ice-sheet model: global mean sea-level and pCO2.<br> Full citation: Berends, C.J., de Boer, B. and van de Wal, R. S. W.: Reconstructing the<br> evolution of ice sheets, sea-level and atmospheric CO2 during the past 3.6 million years,<br> Geosciences, special issue “Developments in Modelling Palaeo-Ice Sheets”, 2019 (under review)</p>
Highlighting altruism in geoscience careers aligns with diverse US student ideals better than emphasizing working outdoors
<p>We surveyed students enrolled in College Algebra at a large, urban, Hispanic-serving, R-1 public university in the southwestern United States. The data span five semesters, from Fall 2018 through Spring 2020. The survey was composed of demographic questions as well as questions using the Likert scale, in which students rated how much they agreed or disagreed with a particular statement regarding descriptions of their “ideal career.” Students were also asked to rate statements about careers in different science fields and engineering. Demographic questions were included at the end of the survey in order to mitigate stereotype threat.</p> <p>Our study tests (i) whether altruistic factors, personal achievement, or work environment are most important to college students (early in their undergraduate program) for their future careers, (ii) whether the ratings of these ideals differ between male/female, URM/non-URM, and first-generation/non-first-generation college students, and (iii) how student perceptions of the geosciences are in regard to those ideals compared to other STEM fields. </p>
Geoscience OER Environmental Scan and Data
<p><strong>Title: </strong>Geoscience OER Environmental Scan and Data, from <em>A Review of Open Educational Resources in the Geosciences: Guidelines and Criteria</em></p> <p><strong>Authors: </strong></p> <p><strong>Samantha Teplitzky</strong>*, Open Science Librarian, Earth Sciences & Map Library, University of California, Berkeley, 50 McCone Hall, Berkeley, CA 94720, steplitz@berkeley.edu, ORCID: 0000-0001-7071-332X</p> <p><strong>Shaun Hardy</strong>, Librarian, Earth & Planets Laboratory, Carnegie Institution for Science, Washington, DC 20015, shardy@carnegiescience.edu, ORCID: 0000-0002-7259-3330</p> <p><strong>Kay Johnson</strong>, Head of Collection and Technical Services, Radford University, 801 E. Main St., Radford, VA 24142-6881, kjohnson497@radford.edu, ORCID: 0000-0001-6472-345X</p> <p><strong>Robert Tolliver</strong>, Sciences Librarian, North Dakota State University, Fargo, ND 58108-6050, robert.tolliver@ndsu.edu, ORCID: 0000-0003-1584-433X</p> <p><strong>Lori Tschirhart</strong>, Assistant Director, STEM, University of Michigan Library, Ann Arbor, MI 48109-1190, ltz@umich.edu, ORCID: 0000-0001-9322-3171</p> <p><strong>Ifigenia Vardakosta</strong>, Phd. Head Librarian, Harokopio University, Library & Information Centre, Athens, Greece, ifigenia@hua.gr, ORCID: 0000-0001-9465-8476</p> <p><strong>Keywords:</strong><br> Open Educational Resources, OER, Geoscience Education</p> <p>This repository documents the background information to the following report:</p> <p>Teplitzky, S., Hardy, S., Johnson, K., Tolliver, R., Tschirhart, L., & Vardakosta, I. (2021). <em>A Review of Open Educational Resources in the Geosciences: Guidelines and Criteria. </em><a href="https://doi.org/10.31223/X5J90G">https://doi.org/10.31223/X5J90G</a></p> <p><strong>Report</strong></p> <p>This study examines the creation and adoption of OER in the Geosciences with a goal of providing guidance for institutions, libraries and librarians who support and fund OER initiatives. An environmental scan, employed to identify and characterize available college-level OER in this discipline, provided a baseline for the study. Analysis of the scan along with a review of OER, textbook and field guide standards informs a new set of proposed guidelines for Geoscience OER. This work will describe these guidelines and offer a call for community feedback.</p> <p><strong>Data</strong></p> <p>Appendix 1: Geoscience OER Environmental Scan and Data, 10.5281/zenodo.5542323</p> <p><strong>Research Products</strong></p> <p>Guidelines Table, 10.5281/zenodo.5542306</p> <p><em>This work is a collaboration of members of the GeoScience Information Society (GSIS) which emerged from the Professional Issues Roundtable at the 2020 Annual Meeting (virtually on October 30, 2020).</em></p>
Strategies for and Barriers to Collaboratively Developing Anti-racist Policies and Resources as Described by Geoscientists of Color Participating in the Unlearning Racism in Geoscience (URGE) Program
<p>The Unlearning Racism in Geosciences (URGE) program guides groups of geoscientists as they draft, implement, and assess anti-racist policies and resources for their workplace. Some participating Geoscientists of Color (GoC) shared concerns about microaggression, tokenism, and power struggles within their groups. These reports led us to collect and analyze data that describe the experiences of GoC in URGE. The data are from five discussion groups and two surveys. Our analyses revealed that participating GoC want to continue working with White colleagues on anti-racist work. GoC want White colleagues not to shy away from doing anti-racist work. Instead, GoC want White colleagues (1) to create and adhere to robust behavioral codes of conduct, (2) to focus discussions on anti-racism, (3) to act on anti-racism initiatives, (4) not to prompt GoC to educate them or reveal trauma, and (5) to refrain from microaggressions and tokenism. These desired outcomes were achieved in some groups with varying degrees of success. Correcting a history of mistrust relating to racism and anti-racism action is key to implementing and assessing effective anti-racist policies and resources. This requires leadership support, following through on anti-racism action, and deepening relationships between GoC and White colleagues. Future anti-racist programs should spend a substantial amount of time on and demonstrate the importance of training participants how to discuss racism effectively and how to create and adhere to robust behavioral codes of conduct. Future programs should also explore developing a robust program-wide code of conduct that includes a policy for reporting offenses.</p>
Data Processing for a Small-Scale Long-Term Coastal Ocean Observing System Near Mobile Bay, Alabama: A Geoscience Papers of the Future (GPF) Data Set
<p>The Dauphin Island Sea Lab (DISL) has been operating a permanent moored oceanographic station at 30 05.410'N, 88 12.694'W, 25 km southwest of the entrance to Mobile Bay, Alabama, since 2004. It collects hydrographic and current velocity data.</p> <p>This set of data files was collected between 27 Jan and 18 May 2011. It includes the raw data at initial download from the instruments, several intermediate processing steps, and final processed files ready for initial scientific analysis.</p> <p>The files have been prepared as supplementary material for a Geoscience Paper of the Future (GPF) in prep for publication at Earth and Space Science, as part of the OntoSoft GPF Initiative.</p> <p> </p>
Data Processing for a Small-Scale Long-Term Coastal Ocean Observing System Near Mobile Bay, Alabama: A Geoscience Papers of the Future (GPF) Workflow Diagram
<p>The Dauphin Island Sea Lab (DISL) has been operating a permanent moored oceanographic station at 30 05.410'N, 88 12.694'W, 25 km southwest of the entrance to Mobile Bay, Alabama, since 2004. It collects hydrographic and current velocity data.</p> <p>This diagram shows the processing steps for data from the instruments at this mooring, from initial download to initial scientific analysis. The accompanying text explains how to apply the workflow to the example dataset (10.5281/zenodo.18943) using the provided software (10.5281/zenodo.32741). </p> <p>The files have been prepared as supplementary material for a Geoscience Paper of the Future (GPF) in prep for publication at Earth and Space Science, as part of the OntoSoft GPF Initiative.</p>
Investigation of metadata standard use by geoscience data repositories
This dataset supports a paper being written about metadata standard use by geoscience data repositories. The study is being done to better understand which metadata standards and keyword vocabularies are prominent within the geoscience data repository landscape. The findings should be useful for NCAR's evaluation of metadata standards within our own systems, as well as by external data repository staff. The guiding questions of the study are as follows: 1. What metadata standards are geoscience data repositories using? 2. What keyword / subject term vocabularies are they using? 3. What interoperability challenges are present in the use of metadata and keyword vocabulary standards within the geoscience repository community?
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.