Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
13
datasets available to search
ShareScore release 0.7.1
Dataset results
13 results for “geodatabase”
The soil province geodatabase of Italy, storing information of soil typological units and broad soil regions at the 1:1,000,000 and 1:10,000,000 scales
<p>The Soil Map of Italy at 1:1,000,000 scale, was the result of the work of Edoardo AC Costantini, Giovanni L'Abate, Roberto Barbetti, Maria Fantappié, Romina Lorenzetti, and Simona Magini affiliated to Research Centre for agrobiology and soil science (CREA-ABP), in collaboration with several regional institutions, universities and other research centers of the CREA - Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria. The map, was printed by S.EL.CA. of Florence. The map is an informative and educational work of general scientific interest, which updates the previous one edited by prof. Fiorenzo Mancini and collaborators in 1966 both in terms of knowledge and of the adopted methods. It was produced processing of all data within a geographical and soil geodatabase, collected by the CREA-ABP and other institutions collaborating in over ten years of work and using the latest international methods. The soil map shows the distribution of major soils in the country and constitutes a milestone in the process launched in 1999 as part of the project the Soil Map of Italy at a scale of 1: 250,000, funded by MIPAAF and implemented in collaboration with the regional institutions. Both broad soil regions and soil provinces (reference scale 1:10,000,000 and 1:1,000,000) are reported.</p> <p>Most small-scale soil maps report dominant typological units and allow only a partial appraisal of pedodiversity since territories with similar dominant soils can actually possess different pedodiversity. This is particularly true at the national scale, where a great wealth of soil information collected at more detailed scales is generalized.</p> <p>A methodology was set up, which aimed at preserving pedodiversity in upscaling soil maps by using geomatic techniques and the World Reference Base for soil resources (WRB). The main source of information was the soil system geodatabase of Italy, storing information of soil typological units and soilscapes at the 1:500,000 reference scale. Qualitative aggregation of soil taxa followed upscaling rules aimed at (i) maintaining the information about pedogenetic processes and (ii) grouping soilscapes showing recurrent patterns of soil forming processes. The upscaling methodology can be summarized in seven steps as follows: (1) soil forming processes selection, retrieved from soil typological units stored in the national database; (2) upscaling soil systems and creation of broad soil regions at 1:10,000,000 reference scale; (3) semantic upscaling of typological units to form taxa showing different soil forming processes; (4) ranking and associating soil forming processes; (5) geography upscaling of soil systems geometry to form polygons at 1:1,000,000 reference scale, called subregions; (6) ranking subregions according to their extension; (7) naming subregions by ranking the taxa according to the number of soil typological units.</p> <p>The soil subregion map reported 47 map unit and 148 taxa, belonging to 22 reference soil group of WRB and showing from one to four qualifiers. Each map unit had from 2 to 18 taxa, for a total of 317 occurrences. Thirty taxa had 3 or more occurrences, while the remaining took place in one or two subregions only.</p>
SBC LTER: Land: Catchment characteristics along the southern coast of Santa Barbara County in Geodatabase
This data package include GIS layers stored in Geodatabase. The layers describe the characteristics of the catchments along the southern coast of Santa Barbara County used in the article Aguilera, R., & Melack, J. M. (2018). Relationships among nutrient and sediment fluxes, hydrological variability, fire, and land cover in coastal California catchments. Journal of Geophysical Research: Biogeosciences, 123, 2568– 2589. https://doi.org/10.1029/2017JG004119. Catchment characteristics include: Land cover and land use based on hyperspectral imagery obtained by the Airborne Visible/Infrared Imaging Spectrometer; number of inhabitants based on population counts by block from the 2010 census spatial database; relief and slopes estimated from a 30 m digital elevation model; geological substrata obtained from geologic maps of California; soil textural types based on the Soil Survey Geographic data, and fire perimeters for the Gaviota, Gap, Tea and Jesusita fires.
MAR2PROTECT - Geodatabase for vulnerability and risk maps
<p>This Dataset includes each of the GIS layers needed for the risk maps as well as the calculations and the final results for each Demo Site in which maps have been produced: Demo Site 3 - Frielas, Demo Site 4 - Emilia-Romagna, Demo Site 5 - Cape Flats and Demo Site 6 - Marbella. </p> <p>The objective was to develop risk vulnerability maps replicable at European scale to assess the vulnerability, hazard, exposure and risk of the different sites so it can be replicable at other sites. It is linked to one of the modules of the REACH Tool: GIS-REACH and the maps and methodology are presented in deliverable 4.3 - Report on the REACH Tool for GC and CC impactos on GW chemical status.</p>
Geodatabase Dataset of the Distribution of Inland Water fish fauna of Freshwater Systems in Northern Greece
<p>Abstract</p> <p>The dataset is a geodatabase focusing on the distribution of freshwater fish species in Northern Greece. The study area encompasses various lakes and rivers within the regions of Thrace, Eastern, Central, and Western Macedonia, and Epirus. It classifies fish species into three categories based on their conservation status according to the IUCN Red List: Critically Endangered, Endangered, and Vulnerable. The data analysis reveals that the study area is characterized by high fish diversity, particularly in certain ecosystems such as the Evros River, Strymonas River, Aliakmonas River, Axios River, Volvi Lake, Nestos River, and Prespa Lake. These ecosystems serve as important habitats for various fish species. Mapping of the dataset shows the geographic distribution of threatened fish species, indicating that Northern Greece is a hotspot for species facing extinction risks. Overall, the dataset provides valuable insights for researchers, policymakers, and conservationists in understanding the status of fish fauna in Northern Greece and developing strategies for the protection and preservation of these important ecosystems.</p> <p>Methods</p> <p>Data Collection: The dataset was collected through a combination of field surveys, literature reviews, and the compilation of existing data from various reliable sources. Here's an overview of how the dataset was collected and processed:</p> <ul> <li>Freshwater Fishes and Lampreys of Greece: An Annotated Checklist </li> <li>The Red Book of Endangered Animals of Greece</li> <li>The "Red List of Threatened Species"</li> <li>The study "Monitoring and Evaluation of the Conservation Status of Fish Fauna Species of Community Interest in Greece"</li> <li>The international online fish database FishBase</li> </ul> <p>Data Digitization and Georeferencing: To create a comprehensive database, we digitized and georeferenced the collected data from various sources. This involved converting information from papers, reports, and surveys into digital formats and associating them with specific geographic coordinates. Georeferencing allowed us to map the distribution of fish species within the study area accurately.</p> <p>Data Integration: The digitized and georeferenced data were then integrated into a unified geodatabase. The geodatabase is a central repository that contains both spatial and descriptive data, facilitating further analysis and interpretation of the dataset.</p> <p>Data Analysis: We analyzed the collected data to assess the distribution of fish species in Northern Greece, evaluate their conservation status according to the IUCN Red List categories, and identify the threats they face in their respective ecosystems. The analysis involved spatial mapping to visualize the distribution patterns of threatened fish species.</p> <p>Data Validation: To ensure the accuracy and reliability of the dataset, we cross-referenced the information from different sources and validated it against known facts about the species and their habitats. This process helped to eliminate any discrepancies or errors in the dataset.</p> <p>Interpretation and Findings: Finally, we interpreted the analyzed data and derived key findings about the diversity and conservation status of freshwater fish species in Northern Greece. The results were presented in the research paper, along with maps and visualizations to communicate the spatial patterns effectively.</p> <p>Overall, the dataset represents a comprehensive and well-processed collection of information about fish fauna in the study area. It combines both spatial and descriptive data, providing valuable insights for understanding the distribution and conservation needs of freshwater fish populations in Northern Greece.</p> <p> </p> <p>Usage notes</p> <p>The data included with the submission is stored in a geodatabase format, specifically an ESRI Geodatabase (.gdb). A geodatabase is a container that can hold various types of geospatial data, including feature classes, attribute tables, and raster datasets. It provides a structured and organized way to store and manage geographic information.</p> <p>To open and work with the geodatabase, you will need GIS software that supports ESRI Geodatabase formats. The primary software for accessing and manipulating ESRI Geodatabases is ESRI ArcGIS, which is a proprietary GIS software suite. However, there are open-source alternatives available that can also work with Geodatabase files.</p> <p>Open-source software such as QGIS has support for reading and interacting with Geodatabase files. By using QGIS, you can access the data stored in the geodatabase and perform various geospatial analyses and visualizations. QGIS is a powerful and widely used open-source Geographic Information System that provides similar functionality to ESRI ArcGIS.</p> <p>For tabular data within the geodatabase, you can export the tables as CSV files and open them with software like Microsoft Excel or the open-source alternative, LibreOffice Calc, for further analysis and manipulation.</p> <p>Overall, the data provided in the submission is in a geodatabase format, and you can use ESRI ArcGIS or open-source alternatives like QGIS to access and work with the geospatial data it contains.</p>
A global-scale geodatabase of mine areas
<p>Globally, the mine area include open cut pits, milling infrastructure, waste rock dumps, and tailings storage facilities of global. Totaled 24605 polygons were studied.</p> <p> </p>
Knepp WildVeg Geodatabase
<p><em><strong>An article describing the production of this data set has been prepared for peer-review. A link will be provided here following publication. Please contact project lead Alex Henshaw (a.henshaw@qmul.ac.uk) for further information in the interim. </strong></em></p> <p>We are releasing our 'Knepp WildVeg’ geodatabase to support future research on rewilding and landscape change. The geodatabase was co-produced by geographers at Queen Mary University of London and ecologists and conservationists at the Knepp Estate, UK. The data set quantifies vegetation regeneration (vegetation cover, height, density and type) at 20 years since the start of rewilding at Knepp Wildland, West Sussex, UK. The Knepp Estate was previously a 3,500 acre intensive arable and dairy farm, but has been devoted to landscape rewilding since 2001. The unique nature of Knepp provides vast opportunities for environmental research but the scale of the project generates research design challenges. Future research on the environmental and ecological effects of rewilding requires baseline data on vegetation structure and dynamics to inform sampling design. Furthermore, the rewilding agenda has, to date, been largely driven by biodiversity goals (with dramatic results achieved) but the fundamental principles that underpin the approach offer potential for much wider-ranging ecosystem services benefits including natural flood management, nutrient cycling, and climate and soil quality regulation. These outcomes are less well understood and this data set is intended to support their investigation.</p> <p>We analysed Environment Agency airborne LiDAR surveys<sup>1</sup> from 2001 and 2019 to produce spatial data on vegetation extent, height and density for both pre-existing vegetation (hedgerows, woodland) and new vegetation that has regenerated in former arable fields following rewilding. We used this information in combination with spectral reflectance data from high resolution satellite imagery<sup>2</sup> to classify the new vegetation into three distinct types (thorny scrub, bramble scrub, sallows).</p> <p>Further information on our project is available here <a href="https://arcg.is/C5mDP">arcg.is/C5mDP</a>. The project was funded by Queen Mary University of London via an HSS Collaboration Fund grant.</p> <p><sup>1</sup><strong> </strong>LiDAR data supplied by Environment Agency under <a href="https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/">Open Government License v3.0</a>. </p> <p><sup>2</sup> Multispectral satellite image data used in new vegetation classification supplied by Planet Team (2017) under Education and Research Program license. Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA. <a href="https://api.planet.com/">https://api.planet.com</a>.</p>
Geodatabase of ultramafic soils of the Americas
<p>This is a compiled geospatial dataset in ESRI polygon shapefile format of ultramafic soils of the Americas showing the location of ultramafic soils in Canada, the United States of America, Mexico, Guatemala, Cuba, Dominican Republic, Puerto Rico, Costa Rica, Colombia, Argentina, Chile, Venezuela, Ecuador, Brazil, Suriname, French Guiana, and Bolivia. The R code used to compile the dataset as well as an image of the compiled dataset are also included. </p>
Geodatabase of ultramafic soils of the Americas
Open the record for dataset details and reuse information.
Geodatabase for the Baltimore Ecosystem Study Spatial Data
The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, acces
PUDL Raw Census DP1 Tract GeoDatabase
<p>US Census Demographic Profile 1 County and Tract GeoDatabase archived from <a href="https://www2.census.gov/geo/tiger/TIGER2010DP1/Profile-County_Tract.zip">https://www2.census.gov/geo/tiger/TIGER2010DP1/Profile-County_Tract.zip</a></p> <p>This archive contains raw input data for the Public Utility Data Liberation (PUDL) software developed by <a href="https://catalyst.coop">Catalyst Cooperative</a>. It is organized into <a href="https://specs.frictionlessdata.io/data-package/">Frictionless Data Packages</a>. For additional information about this data and PUDL, see the following resources:</p> <ul> <li><a href="https://github.com/catalyst-cooperative/pudl">The PUDL Repository on GitHub</a></li> <li><a href="https://readthedocs.org/projects/catalystcoop-pudl/">PUDL Documentation</a></li> <li><a href="https://zenodo.org/communities/catalyst-cooperative/">Other Catalyst Cooperative data archives</a></li> </ul> <p> </p>
SMAPVEX16 Manitoba Soils Geodatabase V001
This data set contains detailed soil survey data used for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign. Data are provided in a relational geodatabase.
SMAPVEX16 Manitoba Soils Geodatabase V001
This data set contains detailed soil survey data used for the Soil Moisture Active Passive Validation Experiment 2016 Manitoba (SMAPVEX16 Manitoba) campaign. Data are provided in a relational geodatabase.
geodatabase for open space points
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
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.