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45,411 results for “collection”
Community Established Best Practice Recommendations for Tephra Studies-from Collection through Analysis
<p>Tephra is a unique volcanic product with an unparalleled role in understanding past eruptions, long-term behavior of volcanoes, and the effects of volcanism on climate and the environment. Tephra deposits also provide spatially widespread, extremely high-resolution time-stratigraphic markers across a range of sedimentary settings and are used in a range of disciplines (e.g., volcanology, climate science, archaeology, ecology, and impact assessment). Nonetheless, the study of tephra deposits is challenged by a lack of standardization that often inhibits data integration across geographic regions and across disciplines.</p> <p>Here we present comprehensive recommendations for tephra data gathering and reporting that were developed by the tephra science community to serve as guidelines for future investigators and to ensure that sufficient data are gathered for transparency and interoperability. Recommendations include standardized field and laboratory data collection along with reporting and correlation guidance. These are organized as tabulated lists of key metadata with their definition and purpose. They are system independent and usable for template, tool, and database development. This new standardized framework promotes consistent tephra documentation and archiving, fosters interdisciplinary communication, and improves effectiveness of data sharing among diverse communities of researchers. Wider adoption will help to expand the applicability and usability of tephra data and facilitate scientific collaboration and data reuse.</p> <p>For additional details, see the accompanying manuscript:</p> <p>Wallace, K.*, Bursik, M. Kuehn, S., Kurbatov, A., Abbott, P., Bonadonna, C., Cashman, K., Davies, S., Jensen, B., Lane, C., Plunkett, G., Smith, V. Tomlinson, E., Thordarsson, T., and Walker, D. Community established best practice recommendations for tephra studies—from collection through analysis. <em>Sci Data</em> <strong>9, </strong>447 (2022). <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a></p> <p>*corresponding author: Kristi Wallace, <a href="mailto:kwallace@usgs.gov">kwallace@usgs.gov</a></p> <p>Open access article is available online here <a href="https://doi.org/10.1038/s41597-022-01515-y">https://doi.org/10.1038/s41597-022-01515-y</a> or as a PDF here <a href="https://gcc02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nature.com%2Farticles%2Fs41597-022-01515-y.pdf&data=05%7C01%7Ckwallace%40usgs.gov%7C673f9f39fd3e4122dd9b08da6f3b9667%7C0693b5ba4b184d7b9341f32f400a5494%7C0%7C0%7C637944598967375940%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=%2BKVfwK2FbUKAoJf2gMerCmBMEQE1rvMDkS6xIk3DGKY%3D&reserved=0">https://www.nature.com/articles/s41597-022-01515-y.pdf</a>.</p>
Systematic assessment of pathway databases, based on a diverse collection of user-submitted experiments
<p><strong>Supplemental data for the manuscript </strong></p> <p><strong>"Systematic assessment of pathway databases, based on a diverse collection of user-submitted experiments".</strong></p> <p>Content</p> <ul> <li>functional_annotations.tar.gz <ul> <li> functional annotations for 10 different functional annotation systems, for 5090 species</li> </ul> </li> <li> genome_info_and_statistics.tar.gz <ul> <li>basic genome info, annotation system statistics, user query statistics</li> </ul> </li> <li>example_user_queries.tar.gz <ul> <li>three example files for user query inputs used in the analysis </li> </ul> </li> <li>README.txt <ul> <li>details about the files and file formats</li> </ul> </li> </ul>
Resource status collected during AWOPS tests
<p>The dataset is about resource status collected during the validation of the Automated Work Planning Services (AWOPS). The dataset includes:</p> <ul> <li>5 csv files regarding crews composition involved at JEA renovation works from March 7<sup>th</sup> to April 11<sup>th</sup>;</li> <li>9 json files regarding crews efforts in the same period.</li> </ul>
Building status collected during AWOPS tests
<p>The dataset is about building status collected during the validation of the Automated Work Planning Services (AWOPS). The dataset includes:</p> <ul> <li>1 csv file regarding renovation works' activities carried out from March 7<sup>th</sup> to April 11<sup>th</sup>;</li> <li>9 json files regarding progress data collected during the following days: <ul> <li>March 14<sup>th</sup> 2022 (day 2);</li> <li>March 17<sup>th</sup> 2022 (day 5);</li> <li>March 21<sup>st</sup> 2022 (day 9);</li> <li>March 24<sup>th</sup> 2022 (day 12);</li> <li>March 28<sup>th</sup> 2022 (day 16);</li> <li>March 31<sup>st</sup> 2022 (day 19);</li> <li>April 4<sup>th</sup> 2022 (day 23);</li> <li>April 7<sup>th</sup> 2022 (day 26);</li> <li>April 11<sup>th</sup> 2022(day 30).</li> </ul> </li> </ul>
Video: Introducing the Open Book Collective (OBC)
<p><em>This video is a Deliverable (D2.11) of the COPIM project.</em></p> <p>Open Book Collective is a non-profit that connects academics, librarians, publishers, and service providers to collectively sustain the infrastructures, relationships, and organizations vital for the success of open access book publishing.</p> <p>Through the Open Book Collective platform, publishers and publishing service providers can offer research institutions the option to financially support their work through library membership programs. Librarians can access the platform to explore and assess different initiatives, support Open Access collections, and manage their subscriptions.</p> <p>OBC’s legal and governance structure ensures it can’t be co-opted for profit, and that stakeholders have a meaningful say in its future. We provide financial support to new open access initiatives and connect book publishers to sustainable revenue streams.</p> <p>Open Book Collective is helping build a world where open access books are produced and distributed collaboratively and anti-competitively, without technical or economic barriers.</p>
MIDAS2 protocol example custom genome collection dataset v1
<p>Example input database of custom genome collection for MIDAS2 protocols.</p> <p>Two genomes from two species (<em>Staphylococcus epidermidis </em>and <em>Streptococcus mutans </em>)</p>
Mataws annotated Web service collection
<p><strong>Description. </strong>The Mataws annotated Web service collection is a set of WS descriptions under the WSDL and OWL-S formats. It contains 816 descriptions, which were originally only syntactically described, and were annotated using our tool Mataws. Consequently, each description appears twice (once in a syntactical version, and once in a semantic version). The descriptions are also classified thematically.</p> <p>Our collection is based primarily on the FullDataset collection of the Assam project (<a href="http://www.andreas-hess.info/projects/annotator/">http://www.andreas-hess.info/projects/annotator/</a>), which we extended using WS descriptions found on the web. These individual files were classified thematically with the rest of the WSDL files, and used to assess the quality of annotation of Mataws.</p> <p><strong>Source code. </strong>The source code of our tool Mataws is available online: <a href="https://github.com/CompNet/mataws">https://github.com/CompNet/mataws</a></p> <p><strong>License. </strong>The annotated descriptions are shared under a Creative Commons 0 license. The original descriptions belong to their authors.</p> <p><strong>Citation. </strong>If you use our dataset, please cite the following article:</p> <ul> <li>Aksoy, C., Labatut, V., Cherifi, C. & Santucci, J.-F (2011). MATAWS: A Multimodal Approach for Automatic WS Semantic Annotation. In International Conference on Networked Digital Technologies. Macau, CN : Springer. ⟨<a href="https://hal.archives-ouvertes.fr/hal-00620566">hal-00620566</a>⟩ - DOI: <a href="https://doi.org/10.1007/978-3-642-22185-9_27">10.1007/978-3-642-22185-9_27</a></li> </ul> <p><br><code>@InProceedings{Aksoy2011,</code><br><code> author = {Aksoy, Cihan and Labatut, Vincent and Cherifi, Chantal and Santucci, Jean-François},</code><br><code> title = {{MATAWS}: A Multimodal Approach for Automatic WS Semantic Annotation},</code><br><code> booktitle = {3\textsuperscript{rd} International Conference on Networked Digital Technologies},</code><br><code> year = {2011},</code><br><code> volume = {136},</code><br><code> series = {Communications in Computer and Information Science},</code><br><code> pages = {319-333},</code><br><code> address = {Macau, CN},</code><br><code> publisher = {Springer},</code><br><code> doi = {10.1007/978-3-642-22185-9_27},</code><br><code>}</code></p>
Sea ice core temperature and salinity data collected during the 2019 SCALE Winter Cruise
<p>Temperature and salinity profiles of sea ice cores extracted from in situ sea ice floes and lifted pancakes were measured in the Atlantic sector of the Antarctic Marginal Ice Zone during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019 (<a href="http://www.scale.org.za">www.scale.org.za</a>) aboard the SA Agulhas II.</p>
Sea ice core temperature and salinity data collected during the 2019 SCALE Spring Cruise
<p>Temperature and salinity profiles of sea ice cores extracted from in situ sea ice floes and lifted pancakes were measured in the Atlantic sector of the Antarctic Marginal Ice Zone during the Southern oCean seAsonal Experiment (SCALE) spring cruise in 2019 (<a href="http://www.scale.org.za">www.scale.org.za</a>) aboard the SA Agulhas II.</p>
Custom Dataset Collected for Energy Manager
<ul> <li>Change directory to inside the dataset</li> <li>Create virtual python environment and install the contents in requirements.txt</li> <li>Run the commands in sample_commands.txt file to get an idea on how the sample_pvm_to_csv.py script works</li> </ul> <p><strong>Data description:</strong><br> Light sensor (APDS9960) - Solar irradiance; Power sensor (INA226) - solar panel open circuit voltage (OCV), solar panel closed circuit current (CCC), solar panel closed circuit shunt voltage (CCSV); DHT22 - temperature and humidity data are collected using a custom setup (check the custom_setup.pdf file), placed indoors, next to a curtain less glass window (the plane of the sensing surfaces were almost 45 degree to the window glass. The spectral distortions made by the glass on the solar irradiance observed is unknown - sorry! The sensors used are INA226, Solar panel (1.5W, 137x81x2.5 mm, 16% efficiency, V & I at peak power :5.5V & 270ma), APDS9960 and DHT22.</p> <p>The custom setup transmits collected data to the server. The server creates a new log file everyday with '.txt' file extension. When the server restarts and begins logging, the first file created has the time information of when the log file was created, suffixed with number '0' before the file extension. This suffix is incremented day by day, until the next interruption to the server, where it create a new log file with the current time and suffix '0', and the whole cycle continues. The log files provided here are raw and unfiltered.<br> <br> A header with 'UTC' time was transmitted by the custom setup to the server whenever it restarts. It contains column information. The sampling period is 0.2s and only the time stamp for the first data is found in the header. The timestamp for the rest is calculated using the index / serial number and the sample period. The index and the data from each sensor are separated by '#'. If a sensor provides multiple data, then those data are separated by ','.</p>
A collection of fully-annotated soundscape recordings from the Western United States
<p>This collection contains 33 hour-long soundscape recordings, which have been annotated with 20,147 bounding box labels for 56 different bird species from the Western United States. The data were recorded in 2018 in the Sierra Nevada, California, USA. This collection has partially been featured as test data in the 2021 BirdCLEF competition and can primarily be used for training and evaluation of machine learning algorithms.</p> <p><strong>Data collection</strong></p> <p>Measuring the effects of forest management activities in the Sierra Nevada, California, USA can reveal a potential correlation with avian population density and diversity. For this dataset, passive acoustic surveys were conducted in the Lassen and Plumas National Forests in May-August 2018. Survey grid cells (4 km<sup>2</sup>) were randomly selected from a 6,000-km<sup>2</sup> area, and SWIFT recording units were deployed at locations conducive to sound propagation (e.g., ridges rather than gullies) within those cells. The sensitivity of the used microphones was -44 (+/-3) dB re 1 V/Pa. The microphone's frequency response was not measured, but is assumed to be flat (+/- 2 dB) in the frequency range 100 Hz to 7.5 kHz. The analog signal was amplified by 38 dB and digitized (16-bit resolution) using an analog-to-digital converter (ADC) with a clipping level of -/+ 0.9 V. Recording units recorded continuously 17:00 - 23:59, 0:00 - 10:00, one-hour files were stored as uncompressed WAVE sampled at 32 kHz and later converted to FLAC. Parts of this dataset have previously been used in the 2021 BirdCLEF competition.</p> <p><strong>Sampling and annotation protocol</strong></p> <p>We subsampled data for this collection by selecting locations that spanned the full elevational and latitudinal gradients of our study area (~840 – 1700 m asl and 39.41 – 40.71°N), and thus represent a broad range of plant communities. A single annotator boxed every bird call he could recognize, ignoring those that are too faint or unidentifiable. Raven Pro software was used to annotate the data. Provided labels contain full bird calls that are boxed in time and frequency. The annotator was allowed to combine multiple consecutive calls of one species into one bounding box label if pauses between calls were shorter than five seconds. We use eBird species codes as labels, following the 2021 eBird taxonomy (Clements list).</p> <p><strong>Files in this collection</strong></p> <p>Audio recordings can be accessed by downloading and extracting the “soundscape_data.zip” file. Soundscape recording filenames contain a sequential file ID, recording date and timestamp in PDT. As an example, the file “SNE_001_20180509_050002.flac” has sequential ID 001 and was recorded on May 9th 2018 at 05:00:02 PDT. Ground truth annotations are listed in “annotations.csv” where each line specifies the corresponding filename, start and end time in seconds, low and high frequency in Hertz and an eBird species code. These species codes can be assigned to scientific and common name of a species with the “species.csv” file. The approximate recording location with longitude and latitude can be found in the “recording_location.txt” file.</p> <p><strong>Acknowledgements </strong></p> <p>The collection and annotation of this dataset was funded by the U.S. Forest Service Region 5 and the California Department of Fish and Wildlife.</p>
The Natural History Museum's collection of Dalbergia, Pterocarpus and the Phaseolinae subtribe
<p>In 2018 the Natural History Museum (NHMUK, herbarium code: BM) undertook a pilot digitisation project together with the Royal Botanic Gardens Kew (project Lead) and the Royal Botanic Garden Edinburgh to collectively digitise non-type herbarium material of the subtribe <em>Phaseolinae</em> and the genera <em>Dalbergia </em>L.f. and <em>Pterocarpus</em> Jacq. (rosewoods and padauk), all from the economically important family of legumes (<em>Leguminosae</em> or <em>Fabaceae</em>). </p> <p>These taxonomic groups were chosen for two case studies using the herbarium collections to support the aims of the UK’s Department for Environment Food & Rural Affairs (DEFRA)-allocated, Official Development Assistance (ODA) funding: study 1 - to support the development of dry beans as a sustainable and resilient crop; study 2 - to aid conservation and sustainable use of rosewoods and padauk.</p> <p>We present the images and metadata for 11,222 NHMUK specimens. This includes label transcription and georeferencing, along with summary data on geographic, taxonomic, collector and temporal coverage. We also provide timings and the methodology for our transcription and georeferencing protocols. Approximately 35% of specimens digitised were collected in ODA-listed countries, in tropical Africa, but also in south east Asia and South America.</p>
A collection of fully-annotated soundscape recordings from the Island of Hawai'i
<p>This collection contains 635 soundscape recordings with a total duration of almost 51 hours, which have been annotated by expert ornithologists who provided 59,583 bounding box labels for 27 different bird species from the Hawaiian Islands, including 6 threatened or endangered native birds. The data were recorded between 2016 and 2022 at four sites across Hawai‘i Island. This collection has partially been featured as test data in the 2022 BirdCLEF competition and can primarily be used for training and evaluation of machine learning algorithms.</p> <p><strong>Data collection</strong></p> <p>Soundscapes for this collection were recorded for various research projects by the Listening Observatory for Hawaiian Ecosystems (LOHE) at the University of Hawai‘i at Hilo. The recordings were collected using Wildlife Acoustics Inc. Song Meters (models 2, 4, or Mini), as 16-bit wav files at a sampling rate of 44.1 kHz, using the default gain settings of each model. Further specifics for each recording, such as recording location and habitat type, can be found in the metadata provided. Soundscapes in this collection vary in length, ranging from just under a minute to 9 minutes in duration. All audio was unified, converted to FLAC, and resampled to 32 kHz for this collection. Parts of this dataset have previously been used in the 2022 BirdCLEF competition.</p> <p><strong>Sampling and annotation protocol</strong></p> <p>This collection is a subset of the files recorded over the course of the LOHE lab’s respective studies. The data were subsampled for annotation by aurally scanning the recordings and visually scanning spectrograms generated using Raven Pro software for target species of interest to the individual research project for which each recording was collected. Recordings that did not contain vocalizations of the species of interest were excluded from full annotation and thus this collection. </p> <p>Using Raven Pro, annotators were asked to create a selection box around every bird call they could recognize, ignoring those that were too faint or unidentifiable at a spectrogram window size of 700 points. Provided labels contain full bird calls that are boxed in time and frequency. Annotators were allowed to combine multiple consecutive calls of the same species into one bounding box label if pauses between calls were shorter than 0.5 seconds. We converted labels to eBird species codes, following the 2021 eBird taxonomy (Clements list).</p> <p><strong>Files in this collection</strong></p> <p>Audio recordings can be accessed by downloading and extracting the “soundscape_data.zip” file. Soundscape recording filenames contain a sequential file ID, site ID, recording date, and timestamp in HST. As an example, the file “UHH_001_S01_20161121_150000.flac” has sequential ID 001 and was recorded at site S01 on Nov 21st, 2016 at 15:00:00 HST. Ground truth annotations are listed in “annotations.csv” where each line specifies the corresponding filename, start and end time in seconds, low and high frequency in Hertz, and an eBird species code. These species codes can be assigned to the scientific and common name of a species with the “species.csv” file. The approximate recording location with Universal Transverse Mercator (UTM) coordinates and other metadata can be found in the “recording_location.csv” file.</p> <p><strong>Acknowledgements </strong></p> <p>Compiling this extensive dataset was a major undertaking, and we are very thankful to the domain experts who helped to collect and manually annotate the data for this collection. Specifically, we want to thank Charlotte Forbes-Perry with the Pacific Cooperative Studies Unit, University of Hawai'i at Hawai‘i Volcanoes National Park as well as the following current and past members of the LOHE lab (in alphabetical order): Keith Burnett, Saxony Charlot, Noah Hunt, Caleb Kow, Elizabeth Lough, and Bret Mossman.</p> <p>Access and permits to record soundscapes were provided by (in alphabetical order): Hakalau Forest National Wildlife Refuge, the State of Hawai‘i Department of Land and Natural Resources Division of Forestry and Wildlife, and the U.S. Fish and Wildlife Service.</p> <p>We would also like to acknowledge our funding sources (in alphabetical order): The National Park Service Inventory and Monitoring Division, the National Science Foundation, and the U.S. Army Engineer Research and Development Center.</p>
A collection of fully-annotated soundscape recordings from the Northeastern United States
<p>This collection contains 285 hour-long soundscape recordings, which have been annotated by expert ornithologists who provided 50,760 bounding box labels for 81 different bird species from the Northeastern USA. The data were recorded in 2017 in the Sapsucker Woods bird sanctuary in Ithaca, NY, USA. This collection has (partially) been featured as test data in the 2019, 2020 and 2021 BirdCLEF competition and can primarily be used for training and evaluation of machine learning algorithms.</p> <p><strong>Data collection</strong></p> <p>As part of the Sapsucker Woods Acoustic Monitoring Project (SWAMP), the K. Lisa Yang Center for Conservation Bioacoustics at the Cornell Lab of Ornithology deployed 30 first-generation SWIFT recorders in the surrounding bird sanctuary area in Ithaca, NY, USA. The sensitivity of the used microphones was -44 (+/-3) dB re 1 V/Pa. The microphone's frequency response was not measured, but is assumed to be flat (+/- 2 dB) in the frequency range 100 Hz to 7.5 kHz. The analog signal was amplified by 33 dB and digitized (16-bit resolution) using an analog-to-digital converter (ADC) with a clipping level of -/+ 0.9 V. This ongoing study aims to investigate the vocal activity patterns and seasonally changing diversity of local bird species. The data are also used to assess the impact of noise pollution on the behavior of birds. Recordings were recorded 24 h/day in 1-hour uncompressed WAVE files at 48 kHz, converted to FLAC and resampled to 32 kHz for this collection. Parts of this dataset have previously been used in the 2019, 2020 and 2021 BirdCLEF competition.</p> <p><strong>Sampling and annotation protocol</strong></p> <p>We subsampled data for this collection by randomly selecting one 1-hour file from one of the 30 different recording units for each hour of one day per week between Feb and Aug 2017. For this collection, we excluded recordings that were shorter than one hour or did not contain a bird vocalization. Annotators were asked to box every bird call they could recognize, ignoring those that are too faint. Raven Pro software was used to annotate the data. Provided labels contain full bird calls that are boxed in time and frequency. Annotators were allowed to combine multiple consecutive calls of one species into one bounding box label if pauses between calls were shorter than five seconds. We use eBird species codes as labels, following the 2021 eBird taxonomy (Clements list).</p> <p><strong>Files in this collection</strong></p> <p>Audio recordings can be accessed by downloading and extracting the “soundscape_data.zip” file. Soundscape recording filenames contain a sequential file ID, recording date, and timestamp in UTC. As an example, the file “SSW_001_20170225_010000Z.flac” has sequential ID 001 and was recorded on Feb 25th, 2017 at 01:00:00 UTC. Ground truth annotations are listed in “annotations.csv” where each line specifies the corresponding filename, start and end time in seconds, low and high frequency in Hertz, and an eBird species code. These species codes can be assigned to scientific and common name of a species with the “species.csv” file. Unidentifiable calls have been marked with “????” and are included in the ground truth annotations. The approximate recording location with longitude and latitude can be found in the “recording_location.txt” file.</p> <p><strong>Acknowledgements </strong></p> <p>Compiling this extensive dataset was a major undertaking, and we are very thankful to the domain experts who helped to collect and manually annotate the data for this collection (individual contributors in alphabetic order): Jessie Barry, Sarah Dzielski, Cullen Hanks, W. Alexander Hopping, Robert Koch, Jim Lowe, Jay McGowan, Ashik Rahaman, Yu Shiu, Laurel Symes, and Matt Young. </p> <p><strong>Version history</strong></p> <p>Version 2: Unidentifiable calls have been marked with “????” and added as bounding box labels to the ground truth annotations.<br> Version 1: Initial release.</p>
Collecting_09/29/22
Documentation material from the Mastic pilot of the Mingei project
Collection of Tools used in the Mastic collection process. (uploaded on 09/29/22)
<p>Documentation material from the Mastic pilot of the Mingei project</p>
Collection of Silk Parament Patterns
<p>Documentation material from the Mingei project</p>
Archaeological Survey of India Collections: Burma Circle, 1903-07. Photo 1004/1 : 1903-1907 (.jpg format)
<p>This is a digitized collections of photos held by the British Library (catalog record photo 1004/1). These photos were taken by the Archeological Survey of India (Burma Circle) between 1903-1907. The digitization was conducted by the photography lab of the British Library as part of the Pyu epigraphy sub-project (PI, Nathan W. Hill of SOAS University of London) of the ERC synergy grant "Beyond Boundaries: Religion, Region, Language and the State" (Identifier: ASIA 609823). The original photographs are under crown copyright, which means that sufficient time has past for them to be distributed to the public. Here is the record from the BL--</p> <p> </p> <ul> <li><strong>Title:</strong> <p>Archaeological Survey of India Collections: Burma Circle, 1903-07. Photographer(s): Archaeological Survey of India</p> </li> <li><strong>Collection Area: </strong> Visual Arts</li> <li><strong>Reference: </strong> Photo 1004/1</li> <li><strong>Creation Date: </strong> 1903-1907</li> <li><strong>Extent and Access: </strong><br> <strong>Extent: </strong>418 items<br> <strong>Conditions of Use: </strong>Appointment Required to view these records. Please consult Asian and African Studies Print Room staff.</li> <li><strong>Language: </strong> Not applicable</li> <li><strong>Contents and Scope: </strong><br> <strong>Contents: </strong> <p>Blue half-leather album, 385x322mm, containing prints mounted on pages interleaved with tissue. The photographs were taken by the Archaeological Survey, Burma, between 1903-07, and listed in the annual Report of the Superintendent... Copies of each year's report precede the photographs for that year, as follows:</p> <p>Year Photo no</p> <p>1903-04 1-123</p> <p>1904-05 124-304</p> <p>1905-06 305-407</p> <p>1906-07 408-509</p> <p>The photographs, including views of Burmese architecture, sculpture and relics, were taken under the direction of the Superintendent, Archaeological Survey, Burma (previously known as the Government Archaeologist), a post held at the time by Taw Sein Ko.</p> <p>Process = Collodio-chloride prints</p> <p>Photographers = Archaeological Survey of India., ;</p> </li> <li><strong>History: </strong><br> <strong>Immediate Source of Acquisition: </strong> <p>Official Deposit</p> </li> <li><strong>Related persons, etc: </strong> Archaeological Survey of India, Unspecified</li> <li><strong>Related places: </strong> Mandalay, Myanmar, Asia, Unspecified</li> <li><strong>Related subjects: </strong> Archaeological Survey Of India Collections<br> Archaeological Survey Of India: Burma Series</li> </ul>
Wikipedia. Events and collective memory detection dataset
<p>This is the data accompanying the code (https://github.com/mizvol/WikiBrain), required to reproduce results of "Wikipedia graph mining: dynamic structure of collective memory" paper (https://arxiv.org/abs/1710.00398).</p>
Polidoc.net CODEBOOK: National and Regional Manifestos and other Political Documents Collected for the Research Projects "Representation in Europe: Congruence between Preferences of Elites and Voters" (REPCONG) and "The Impact of EU Cohesion Policy on European Identification" (COHESIFY)
<p>The Political Documents Archive http://www.polidoc.net/ contains election manifestos, coalition agreements, government declarations and various other documents of political actors from developed democracies. Currently, the archive builds on a stock of more than 3000 political documents from 20 European countries. The aim of the repository is to provide political texts in order to facilitate scholarly research in different areas of comparative politics such as party competition, coalition politics, legislative decision-making or electoral behavior.</p> <p>National electoral manifestos have been collected in the course of the REPCONG project ("Representation in Europe: Policy Congruence between Citizens and Elites"), and the archive includes party manifestos for regional elections in several European democracies. Because the process of European integration resulted in a strengthening of regions in EU member states and in countries that want to join the European Union, the relevance of the regional level for political decision-making has increased during the last decades. Therefore, also the policy profiles of regional parties are required to get a full picture of democratic responsiveness in European states across all levels of the political system. The collection of regional manifestos was supported by the COHESIFY project (www.cohesify.eu), funded under the Horizon 2020 Framework Programme for Research and Innovation. The aim of COHESIFY is to study whether the European Structural and Investment Funds affect people’s support for and identification with the European project.</p> <p>The archive is freely accessible (after a simple registration) and meant to foster rigorous research in these areas by enabling scholars to produce valid and reliable findings from empirical studies of textual data rather than unnecessarily struggling to obtain and process texts.</p>
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.