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228 results for “burials”
Comparing vertical accretion, organic carbon (C) sequestration, and nitrogen burial between a natural, never diked tidal salt marsh and a hydrologically restored tidal salt marsh on Sapelo Island, Georgia.
Restoration of tidal marshes throughout the 20th century have attempted to bring back important functions of natural tidal systems. In this study, vertical accretion, organic carbon (C) sequestration, and nitrogen burial were compared between a natural, never diked tidal salt marsh and a hydrologically restored tidal salt marsh on Sapelo Island, Georgia to examine the impacts of restoration years later. On Sapelo Island there are two marshes near the University of Georgia Marine Institute, one of which is a natural marsh, and one of which is a restored marsh. The restored marsh had been diked in 1948, and the dike was breached, allowing for the marsh to be restored, in 1956. Soil cores were collected from both marshes, and the sediments were analysed for Nitrogen and Carbon concentrations and bulk density. This analysis was used to determine accretion rates for the two marshes as well as changes in the restored marsh since the dike was breached. Nitrogen burial, carbon sequestration, and soil accretion in the restored marsh as compared to the natural marsh were the focus of this study.
Niedertiefenbach: neolithic collective burial
<p>Spatialite database (SQLite) with data of the Neolithic collective grave Niedertiefenbach in Hesse (Germany). Data collected from the published images and copies of the corresponding lithographs in the archive (Wurm et al., Fundberichte aus Hessen Bd. 3, 1963, 56-78). Data collection from CRC 1266: "Scales of Transformation - Human-Environmental Interaction in Prehistoric and Archaic Societies". Project: "Regional and Local Patterns of 3rd Millennium Transformations of Social and Economic Practices in the Central German Mountain Range (D2)". Funded by the DFG. DFG project number: 2901391021</p>
Sri Ksetra, Bago, Myanmar. Burial urn as excavated in 1912 at the Pyutaik terrace adjacent to the Payama stūpa.
<p>Sri Ksetra, Bago, Myanmar. Burial urn as excavated in 1912 at the Pyutaik terrace adjacent to the Payama stūpa. </p>
Supplementary material: Burial Analysis on the Middle Bronze Age in the Carpathian Basin (dataset and scripts)
<p>This is the supplementary material of the paper "Wealth Consumption, Sociopolitical Organization, and Change: A Perspective from Burial Analysis on the Middle Bronze Age in the Carpathian Basin" (accessible over doi: https://doi.org/10.1515/opar-2022-0281). Please consult the publication for in depth description of the data, its context and for the method applied on the data, as well as references to primary sources. The data tables comprise the burial data of the Hungarian Middle Bronze Age cemeteries of Dunaújváros-Duna-dűlő, Dömsöd, Adony, Lovasberény, Csanytelek-Palé, Kelebia, Hernádkak, Gelej, Pusztaszikszó and Streda nad Bodrogom. The script "supplementary_material_2_wealth_index_calculation.py" provides the calculation of a wealth index, based on grave goods, for the provided data. The script "supplementary_material_3_population_estimation.py" models the living population of Dunaújváros-Duna-dűlő. Both can be run by double-click. Requirements to be installed to run the scripts: Python 3 (https://www.python.org/) with the packages numpy (https://numpy.org/), pandas (https://pandas.pydata.org/), matplotlib (https://matplotlib.org/), seaborn (https://seaborn.pydata.org/) and scipy (https://scipy.org/); all included in Ancaonda (Python-Distribution, https://www.anaconda.com/).</p>
Altendorf: neolithic collective burial
<p>Spatialite database (SQL) with data of the Neolithic collective grave Altendorf in Hesse (Germany).<br> Data collected from the original drawings and sketches of the excavation and the immediately following final drawings for the first publication by W. Jordan (Kurhessische Bodenaltertümer Bd. 3, 1954, 5-26). The data originally digitised as shp files by Clara Drummer were reorganised for the spatialite database.<br> Data collection from CRC 1266: "Scales of Transformation - Human-Environmental Interaction in Prehistoric and Archaic Societies". Project: "Regional and Local Patterns of 3rd Millennium Transformations of Social and Economic Practices in the Central German Mountain Range (D2)". Funded by the DFG. DFG project number: 2901391021</p>
Sediment, C, N, and P Concentrations and Burial Rates in Three Southwestern Ohio Retention Ponds: 2006-2019
These datasets correspond to Rogers et al (2022) “Temporal patterns in sediment, carbon, and nutrient burial in ponds associated with changing agricultural tillage” published in Biogeochemistry (DOI: 10.1007/s10533-022-00916-w). We sampled three retention ponds in southwest Ohio in 2019 to compare sediment, carbon, nitrogen, and phosphorous burial rates to those calculated in 2006 to see the effect a watershed-wide shift to conservation tillage and to estimate the value of the ecosystem services these ponds provide via sequestration. Two methods were used to calculate burial rates: simple mean and spatially explicit. All datasets use simple mean except for the data set named “Spatially Explicit Sediment C N P Burial in SW OH Retention Ponds 2019”, which uses the spatially explicit method. For more information, please refer to our paper.
Burial mounds dataset associated with the paper Geomorphometric methods for tumuli recognition and extraction from high resolution LiDAR DEMs
<p>This dataset consist of the burial (tumuli) mounds delineation and the associated data produced for the article Geomorphometric methods for tumuli recognition and extraction from high resolution LiDAR DEMs, submitted to Sensors. The dataset work in conjunction with the script (http://doi.org/10.5281/zenodo.3628805) to make the work reproductible. The DEM is available only by request to mihai.niculita@uaic.ro.</p>
FIG. 5. — Undated female red deer upper left canine from Abri des Autours. A in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 5. — Undated female red deer upper left canine from Abri des Autours. A, general view; B, detail of perforation; C, detail of the crown with remaining traces of enamel (arrow). Scale bars: A, 10 mm; B, C, 1 mm.
FIG. 7 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 7. — Needle made of a suid left fibula, from the Neolithic collective burial at Abri des Autours: A, general view; B, detail of the tip showing a smooth polish associated with fine and short striations; C, detail of the posterior edge near the point, showing fine parallel striations; D, detail of the posterior edge at the midpoint of the tool, showing smooth polish. Scale bars: A, 10 mm; B, C, D, 150 μm.
FIG. 2 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 2. — Plan of Abri des Autours: A, circular depression; B, rubble of old (unpublished) excavations; C, crack in the rock; D, pit under low wall (from Polet & Cauwe 2007).
FIG. 6 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 6. — Pointed rib of a large bovid, from the Neolithic collective burial at Abri des Autours: A, general view (from left to right: internal, centre and external views); B, detail of the tip (internal view) showing some polish; C, detail of the tip (internal view) showing fine perpendicular striations; D, detail of a lateral edge of the rib devoid of striations. Scale bars: A, 10 mm; B, 500 μm; C, D, 100 μm.
FIG. 3 in The worked bone industry and intrusive fauna associated with the prehistoric cave burials of Abri des Autours (Belgium)
FIG. 3. — Stratigraphy of Abri des Autours, east–west profile (modified from Cauwe 1994): 1a, b, clay, without pebbles; 2, as layer 6, but with more clay; 3a, brown, argillaceous deposit with small, densely dispersed pebbles; 3b, as layer 3a, but less humic. Contains the Neolithic multiple burial; 3c, as layer 3a, but strongly compacted by calcite precipitations; 4, clay with fine pebbles; 5a, b, cryoclastic deposit without humic or clayish fraction; layer 5b corresponds to very fine gravels, while layer 5a includes larger elements. The Mesolithic single burial extends through both of these layers; 6, brown-grey clayey deposit, strongly inclined. Contains the Mesolithic collective burial; 7, cryoclastic layer, included in clayey orange-brown sediment; 8, thin pebble deposit mixed with greyish sediment; 9, low wall constructed of unworked stone blocks.
Mahurjhari महुरझरी (Nagpur, Maharashtra). Gond burial, with stone circle behind.
<p>Mahurjari महुरझरी (Nagpur, Maharashtra). Gond burial, with stone circle of the Iron Age behind.</p>
Verified Burial Mounds in Yambol Province, SE Bulgaria
<p>This release contains field observations collected at mound locations shown in 1:50,000-scale Soviet military topographic maps from 1980s, visited in years 2009-2022 by the Tundzha Regional Archaeologial Project within the Province of Yambol in SE Bulgaria. The observations are divided into datasets "YambolMounds.7zip" and photos associated with the records "YambolMounds images 2009-2022". They are provided separately as the photos are heavy (8Gb) and users can select or deselect them. </p> <p>Inside the YambolMounds.zip, there are two main datasets:</p> <ul> <li>features ( ~1260) which include all kinds of surface phenomena teams encountered when visiting mound locations, such as settlement mounds, surface scatters, etc. Observations at 18 locations have been repeated, producing spatial duplicates with different attributes. A unique version can be generated by filter on one of the two columns Upto2010 and Post2010. </li> <li>mounds (~ 1095) which include only those rows in features dataset classified as extant or extinct burial mounds. Observations at 18 locations have been repeated, producing spatial duplicates with different attributes. A unique version can be generated by filter on one of the two columns Upto2010 and Post2010. </li> </ul> <p>These two datasets have been streamlined and clipped to the borders of the Yambol region. While spatial duplicates are identified in each dataset, for purpose of analysis the user can choose among the duplicates by selecting either 2010 or post-2010 version, by filtering on one or another column. Datasets are provided in output_data/ folder in .CSV, .RDS (native R format) and .GeoJSON (spatial format for Python).</p> <p>A number of accompanying datasets were generated for this release and placed in the interim/ folder, including a paired list of all spatial duplicates, an .rds/.geojson file with all verified map features from within and without Yambol Province (the largest dataset of ~ 1466 features) , as well as faims4326.rds fully digitally collected dataset between 2017-2022, containing over 40 attributes as opposed to the shared~27 from the whole span of work 2009-2022.</p> <p>Both the interim and the final datasets can be found in the output_data/ . Attributes in the final datasets are described in the Metadata.csv in the root folder. Broader description of the cleaning process and remaining uncertainties in the datasets can be found in the Readme.md file in the root folder. The scripts used for the processing and streamlining of the data sit in the scripts/ folder.</p> <h2>Acknowledgements</h2> <p>Collecting a large-scale landscape dataset would not be possible without the dedicated help of local and international colleagues. We owe massive thanks to Barbora Weissova for long-term collaboration on mound monitoring and subsequent assistance with data streamlining. We also thank Petra Heřmánková and Věra Doležálková for leading field teams and managing data collection. Last but not least, the data would not exist were it not for the students, colleagues, and volunteers from the Yambol History Museum, UNSW Australia, Macquarie University, New Bulgarian University, Charles University, Aarhus University and many other institutions. In rough chronological order of appearance these include Iliya Iliev, Georgi Iliev, Yavor Rusev, Stefan Bakardzhiev, Simon Connor, Shawn Ross, Petra Tušlová, Tereza Dobrovodská, Sona Holičková, Scott Jackson, Stanislav Marchovski, Jana Ryšavková, Radko Sedláček, Jarmila Švédová, Dragomir Garbov, Emma Jacobson, Royce Lawrence, Briana Barton, Stephanie Black, Lachlan Hanley, Samuel Riley, Isaac Roberts, Tiana Anderson, Amy Tanswell, Mikaila Walker, Bronwyn Schlamowitz, Elissa Sinclair, Angel Bogdanov Grigorov, Matilde Jensen, Sara Vejrup, Dorthe Pedersen, Julie Lund, Joel Sercombe, Mathias Kaas, and Mathias Johansen.</p> <h2>Funding Information</h2> <p>This work was supported by the Australian Research Council Linkage Projects Funding scheme LP0989901, University of Michigan International Grant, America for Bulgaria Foundation, Endeavour Short-Term Mobility Programme from the Australian Department of Education, grant 19686; National eResearch Collaboration Tools and Resources (NeCTAR) under eResearch Tools grant RT043; the Australian Research Council under Linkage, Infrastructure, Equipment and Facilities (LIEF) grant LE140100151; Macquarie University and UNSW Australia under internal infrastructure grant schemes; and Aarhus University Forskningsfond Starting grant no. AUFF-2018-7-22 awarded to the ‘Social Complexity in the Ancient Mediterranean’ (SDAM) project.</p>
Influences of the 1855 AD Huanghe (Yellow River) Relocation on Sedimentary Organic Carbon Burial in the Southern Yellow Sea
<p>This is the original data used in the manuscript titled "Influences of the 1855 AD Huanghe (Yellow River) Relocation on Sedimentary Organic Carbon Burial in the Southern Yellow Sea" which has been accepted by Frontiers in Marine Science. The data is from a box-core HH12 recovered from the southern Yellow Sea (123.50°E, 35.00°N; core length: 48 cm; water depth: 77 m; time span: ~300 yr). This excel includes depth, year, TOC, TN, biomarkers and other proxy record.</p> <p>Full Article at: <a href="https://www.frontiersin.org/articles/10.3389/fmars.2022.824617/full">https://www.frontiersin.org/articles/10.3389/fmars.2022.824617/full</a></p>
Detailed analytical results for archaeological textiles from the Uden–Slabroekse Heide elite burial (Early Iron Age, Netherlands)
<p>The dataset contains 3D volume of the mineralised textile, showing four superimposed layers. The textile layer was segmented on the basis of the fibre orientation used for the 3D rendering of the vanished colour pattern.</p>
FIG. 12 in Animal Management, preparation and sacrifice: reconstructing burial 6 at the Moon Pyramid, Teotihuacan, México
FIG. 12. — Model of the life histories of the animals interred in Burial 6 divided into four stages; acquisition, management, preparation and sacrifice and/or deposition. Arrows and letters in grey indicate the zooarchaeological and archaeological indicators of these processes.
FIG. 11 in Animal Management, preparation and sacrifice: reconstructing burial 6 at the Moon Pyramid, Teotihuacan, México
FIG. 11. — Photograph of basket excavated as a block from Burial 6. Arrow indicates the concentration of serpentine remains.
FIG. 10 in Animal Management, preparation and sacrifice: reconstructing burial 6 at the Moon Pyramid, Teotihuacan, México
FIG. 10. — Canid and felid skull preparation methods: A, Element 2194 female wolf 1-2 years old; B, Element 1960 jaguar infant.
FIG. 9. — Element 1818 in Animal Management, preparation and sacrifice: reconstructing burial 6 at the Moon Pyramid, Teotihuacan, México
FIG. 9. — Element 1818: A, in situ in Burial 6; B, deformed right femoral shaft; C, head injury along the nuchal crest; D, right innonimate with deformed acetabulum.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.