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410 results for “Data Repositories”
Unofficial Kawasaki City Open Data Repository
<div> <div> <div># Unofficial Kawasaki City Open Data Repository</div> <div> </div> <div>## 0. 概要</div> <div> </div> <div>[本リポジトリ](https://doi.org/10.5281/zenodo.14252205)では、神奈川県川崎市の[オープンデータカタログページ](https://www.city.kawasaki.jp/main/opendata/opendata_list.html)で公開されているオープンデータと、それを加工したデータをまとめて公開しています。元のオープンデータは、2024 年 12 月 07 日にダウンロードしました。今後は折を見て更新予定です。</div> <div> </div> <div>### 更新履歴</div> <div> </div> <div>- Version v3 (2024-12-08):</div> <div> - 元データを更新</div> <div> - 元データダウンロード日: 2024 年 12 月 07 日</div> <div> - `list.tsv` のフォーマットを大幅変更</div> <div> - `list.tsv` を更新</div> <div> - `README.md` を更新</div> <div>- Version v2 (2024-12-01):</div> <div> - `README.md` を更新</div> <div>- Version v1 (2024-12-01):</div> <div> - リポジトリを公開</div> <div> - 元データダウンロード日: 2024 年 11 月 27 日から 28 日にかけての深夜</div> <div> </div> <div>## 1. 提供物</div> <div> </div> <div>提供物は `20241207.zip` にまとめられています。以下のようなディレクトリ構成になっています。</div> <div> </div> <div>- `20241207/`</div> <div> - `Converted/`</div> <div> - `001_Corrected_Extensions/`</div> <div> - ...</div> <div> - `Original/`</div> <div> - ...</div> <div> - `README.md`</div> <div> - `list.tsv`</div> <div> </div> <div>各ディレクトリ及びファイルの内容は次の通りです。</div> <div> </div> <div>### `Original/`</div> <div> </div> <div>このディレクトリには、神奈川県川崎市の[オープンデータカタログページ](https://www.city.kawasaki.jp/main/opendata/opendata_list.html)からコピーしたオープンデータのファイル群が含まれています。ファイルは、`https://www.city.kawasaki.jp/` 配下のディレクトリ構造に従い、`Original/www.city.kawasaki.jp/` 配下に配置されています。</div> <div> </div> <div>### `Converted/`</div> <div> </div> <div>このディレクトリには、`Original/` 配下のファイルをいくつかのステップ (2024 年 12 月 07 日現在、拡張子修正のステップのみ) で加工した結果が含まれています。</div> <div> </div> <div>#### `Converted/001_Corrected_Extensions/`</div> <div> </div> <div>`Original/` 配下のファイルのうち、拡張子に誤りがあったものを修正したファイルです。ファイルの内容に変更はありません。修正されたファイルは、`Original/` 配下のディレクトリ構造に従い、`Converted/001_Corrected_Extensions/` 配下に配置されています。</div> <div> </div> <div>### `list.tsv`</div> <div> </div> <div>このファイルは、`Original/` 配下の全てのファイルのうち元サイトに存在する (「2. 注意」参照) ファイルに関する情報の一覧です。9 列から成る TSV 形式ファイルで、各列の内容は次の通りです。</div> <div>- `Original`</div> <div> - リポジトリ内の `Original/` 配下のファイルのパス。</div> <div>- `Converted/001_Corrected_Extensions`</div> <div> - リポジトリ内の `Converted/001_Corrected_Extensions/` 配下の、対応するファイルとパス。対応するファイルがない場合は空欄。</div> <div>- `Data_URL`</div> <div> - ファイルの元サイトでの URL。</div> <div>- `HTML_URL`</div> <div> - ファイルが掲載されているウェブページの URL。</div> <div>- `Anchor`</div> <div> - 掲載ウェブページ上での当該ファイルのアンカーテキスト。</div> <div>- `Dataset_Title`</div> <div> - 掲載ウェブページ上で、当該ファイルを含む 1 個以上のファイルの囲みに書かれたタイトル。</div> <div>- `Subtitle`</div> <div> - 掲載ウェブページのサブタイトル (`<h2>` タグ)。ない場合は空欄。</div> <div>- `Title`</div> <div> - 掲載ウェブページのタイトル (`<h1>` タグ)。</div> <div>- `Breadcrumbs`</div> <div> - セミコロンで区切った、掲載ウェブページのパンくずリスト。</div> <div> </div> <div>### `README.md`</div> <div> </div> <div>このファイルです。</div> <div> </div> <div>## 2. 注意</div> <div> </div> <div>- `http://kawasaki.geocloud.jp/` 配下のファイルは、ライセンスの確認が取れていないため、含めていません。</div> <div>- [バリアフリーマップ](https://www.city.kawasaki.jp/kurashi/category/26-4-10-0-0-0-0-0-0-0.html)に掲載されている多くのファイルがリンク切れのため、このページにある全てのファイルを含めていません。</div> <div>- [令和4年就業構造基本調査結果](https://www.city.kawasaki.jp/170/page/0000157324.html)のアンカーテキスト「表13 男女、就業希望意識別無業者数(平成29年、令和4年)(XLS形式, 28.50KB)」に含まれるタブ文字は、`list.tsv` 作成の際に削除しました。</div> <div>- `Original/` 配下には存在するものの `list.tsv` に載っていないファイルがいくつかあります。これらは元サイトで、過去のダウンロードの際存在したが、現在は削除されたファイルです (恐らく更新のため)。こうしたファイルの取り扱いについては、今後見直しを予定しています。</div> <div>- 掲載ウェブページからの情報抽出に不備がある可能性があります(特に `Subtitle`)。今後、精査を予定しています。</div> <div> </div> <div>## 3. ライセンス</div> <div> </div> <div>元データ (`Original/` 配下の全てのファイル) のライセンスは川崎市が所有しています。加工データや本 `README.md` 等その他のファイルのライセンスは「Unofficial Kawasaki City Open Data Repository」が所有し、[Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/) に従います。</div> <div> </div> <div>- `Original/` ディレクトリ配下の全てのファイルは川崎市が提供するオープンデータのコピーであり、クレジット情報は次の通りです。</div> <div> </div> <div> > 川崎市オープンデータ、川崎市、クリエイティブ・コモンズ・ライセンス 表示 2.1 (http://creativecommons.org/licenses/by/2.1/jp/)</div> <div> </div> <div> これらのデータを利用・再配布する際には、[川崎市オープンデータ利用規約 (pdf)](https://www.city.kawasaki.jp/170/cmsfiles/contents/0000057/57493/kawasakiod_rules.pdf) に従ってクレジットを記載して下さい。</div> <div> </div> <div>- `Converted/` ディレクトリ配下の全てのファイルは、川崎市が提供するオープンデータを加工したデータです。この全ファイルは以下の著作物を改変して利用しています。</div> <div> </div> <div> > 川崎市オープンデータ、川崎市、クリエイティブ・コモンズ・ライセンス 表示 2.1 (http://creativecommons.org/licenses/by/2.1/jp/)</div> <div> </div> <div> これらのデータを利用・再配布する際には、[川崎市オープンデータ利用規約 (pdf)](https://www.city.kawasaki.jp/170/cmsfiles/contents/0000057/57493/kawasakiod_rules.pdf) に従ってクレジットを記載し、「Unofficial Kawasaki City Open Data Repository」のデータを利用している旨も任意の方法で記載して下さい。</div> <div> </div> <div>- その他のファイルを利用・再配布する際には、「Unofficial Kawasaki City Open Data Repository」のファイルを利用している旨を任意の方法で記載して下さい。</div> <div> </div> <div>## 4. 免責事項</div> <div> </div> <div>本リポジトリは、「現状のまま」提供されており、著作権者はその正確性、完全性、適用性、またはデータの利用によって生じた損害について、いかなる責任も負いません。利用者は、自己の責任で本リポジトリを利用するものとし、利用に際しては必要な確認や注意を行ってください。</div> <div> </div> <div>## 5. 連絡先</div> <div> </div> <div>- X (旧 Twitter): @lod_y15</div> <div>- GitHub: ytklod</div> <div> </div> </div> </div>
Data Repository: Fast Single-Particle Tracking of Membrane Proteins Combined with Super-Resolution Imaging of Actin Nanodomains
<p>This repository contains a collection of correlated 2D super-resolution images obtained through single molecule localization microscopy and 3D time series of single particle tracking data of membrane proteins. By utilizing high-speed fluorescent microscopy, we tracked a transmembrane protein – the high-affinity IgE receptor – and an outer-leaflet protein – GPI-anchored protein – at the frame rate of 490 Hz. Subsequently, actin structures of the same cells were captured using a super-resolution microscopy (dSTORM technique). Additionally, this dataset includes Technical Validation to support the transition from live-cell imaging to fixed-cell imaging when adding fixation buffers. </p> <p>The data was classified as “Class I” and “Class II” describing two categories of RBL-2H3 cells. In "Class I", the cells were untransfected. In “Class II”, the cells were transfected to express GFP-GPI-anchored fusion protein. The zip folder names that include “IgE Untreated” include image time series of fluorescently labeled IgE receptors in untreated RBL-2H3 cells and image series of corresponding super-resolution imaging of fluorescently labeled actin filaments of the same cell in “SRImage” folder.</p> <p>The data with folder names including with “IgE Treated” are image time series of fluorescently labeled IgE receptors in either phalloidin- or PMA-treated RBL-2H3 cells and corresponding image series of super-resolution imaging of fluorescently labeled actin filaments in the same cell.</p> <p>Similarly, the data with folder names starting with “GPI Untreated” are image time series of fluorescently labeled GPI-anchored proteins in untreated RBL-2H3 cells and corresponding image series of super-resolution imaging of fluorescently labeled actin filaments in the same cell.</p> <p>The data with folder names starting with “GPI Treated” are image time series of fluorescently labeled GPI-anchored proteins in phalloidin treated RBL-2H3 cells and corresponding image series of super-resolution imaging of fluorescently labeled actin filaments in the same cell.</p> <p>The number within each folder name represents an individual experiment and the corresponding data collected under the same conditions.</p> <p>For all experiments an IR movie was added to monitor the cell morphology during live-cell image and adding initial fixation buffer and it was saved in the tracking file. </p> <p>The HDF5 files of all data are available in the second version of this repository. For each sample, there are two files: "Tracking.h5" and "SuperResolution_actin.h5". The "Tracking" files include two groups: single-particle tracking data and IR images during tracking. The "SuperResolution_actin" files contain two groups: super-resolution images of actin filaments and IR reference images for image registeration and drift correction during data collection. </p> <p> </p> <p> </p> <p> </p>
FactDrill: A Data Repository of Fact-checked Social Media Content to Study Fake News Incidents in India
<p>A dataset containing 22,435 fact-checked social media content to study fake news incidents in India. The dataset comprises news stories from 2013 to the year 2020, covering 13 different languages spoken in the country. There are 14 different attributes present in the dataset.</p>
Data & code repository for "A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation"
<p>This repository includes the data and code that can be used to reproduce the figures for the paper entitled <em>A re-appraisal of the ENSO response to volcanism with paleoclimate data assimilation</em> (<a href="https://doi.org/10.1038/s41467-022-28210-1">DOI: 10.1038/s41467-022-28210-1</a>).</p> <p>The code is tested with Python v3.8, and the package <a href="https://github.com/fzhu2e/LMRt">LMRt</a> (Zhu et. al., 2021) is required to perform essential analysis (e.g. Superposed Epoch Analysis) and the corresponding visualization.</p> <p><strong>Repository Structure</strong></p> <ul> <li> <p><code>recons</code>: the folder that includes our reconstructions of (i) the NINO3.4 series with 0.05, 0.25, 0.5, 0.75, 0.95 quantiles and (ii) the ensemble median surface temperature field</p> <ul> <li><code>recon_Ocn2kCorals_Li13b6.nc</code>: the reconstruction that assimilates all the available Ocean2k corals (Tierney et al., 2015; PAGES2k Consortium, 2017) and the six best ENSO predictors in Li et al. (2013).</li> <li><code>recon_Corals_Li13b6.nc</code>: the reconstruction that assimilates the corals reaching back before 1750 CE and the six best ENSO predictors in Li et al. (2013).</li> <li><code>recon_Corals.nc</code>: the reconstruction that assimilates the corals reaching back before 1750 CE.</li> <li><code>recon_Li13b6.nc</code>: the reconstruction that assimilates the six best ENSO predictors in Li et al. (2013).</li> </ul> </li> <li> <p><code>notebooks</code>: the folder that includes Jupyter notebooks</p> <ul> <li><code>Fig-1.ipynb</code>: the notebook that performs analysis and generates Fig. 1 in the main text</li> <li><code>Fig-2.ipynb</code>: the notebook that performs analysis and generates Fig. 2 in the main text</li> <li><code>Fig-3.ipynb</code>: the notebook that performs analysis and generates Fig. 3 in the main text</li> <li><code>Fig-4.ipynb</code>: the notebook that performs analysis and generates Fig. 4 in the main text</li> </ul> </li> <li> <p><code>data</code>: the folder that includes auxiliary data for the analysis and visualization</p> <ul> <li><code>proxy_locs.pkl</code>: the pickle file that includes the location information of the assimilated proxies</li> <li><code>eVolv2k_v3_ds_1.nc</code>: the eVolv2k v3 volcanic forcing data (Toohey & Sigl, 2017), which is publicly available and can be downloaded <a href="https://doi.org/10.26050/WDCC/eVolv2k_v3">here</a></li> <li><code>palmyra2013.txt</code>: the Palmyra coral d18O data (Emile-Geay et al., 2013), which is publicly available and can be downloaded <a href="https://www.ncdc.noaa.gov/cdo/f?p=519:1:::::P1_STUDY_ID:1875">here</a></li> <li><code>Li13b6.txt</code>: the six best ENSO predictors in Li et al. (2013), including the first two principle components (PCs) of the North American Drought Atlas (NADA; Cook et al., 2004) and Monsoon Asia Drought Atlas (MADA; Cook et al., 2010) networks, the Kauri tree-ring composite (Fowler et al., 2012), and the South America Altiplano (SA Altiplano) tree-ring composite (Morales et al., 2012)</li> <li><code>enso-li2013.txt</code>: the Li et al. (2013) NINO3.4 reconstruction, which is publicly available and can be downloaded with the link: <code>ftp://ftp.ncdc.noaa.gov/pub/data/paleo/treering/reconstructions/enso-li2013.txt</code></li> <li><code>ERSSTv5_sst_DJF.nc</code>: the ERSSTv5 boreal winter (December-February) SST field data (Huang et al., 2017)</li> </ul> </li> <li> <p><code>figs</code>: the folder that includes figures</p> <ul> <li><code>Fig-1.pdf</code>: Fig. 1 in the main text</li> <li><code>Fig-2.pdf</code>: Fig. 2 in the main text</li> <li><code>Fig-3.pdf</code>: Fig. 3 in the main text</li> <li><code>Fig-4.pdf</code>: Fig. 4 in the main text</li> </ul> </li> </ul> <p><strong>References</strong></p> <ul> <li>Cook, E. R., Woodhouse, C. A., Eakin, C. M., Meko, D. M., & Stahle, D. W. (2004). Long-Term Aridity Changes in the Western United States. Science, 306(5698), 1015–1018. <a href="https://doi.org/10.1126/science.1102586">https://doi.org/10.1126/science.1102586</a></li> <li>Cook, E. R., Anchukaitis, K. J., Buckley, B. M., D’Arrigo, R. D., Jacoby, G. C., & Wright, W. E. (2010). Asian Monsoon Failure and Megadrought During the Last Millennium. Science, 328(5977), 486–489. <a href="https://doi.org/10.1126/science.1185188">https://doi.org/10.1126/science.1185188</a></li> <li>Emile-Geay, J., Cobb, K. M., Mann, M. E., & Wittenberg, A. T. (2013). Estimating Central Equatorial Pacific SST Variability over the Past Millennium. Part II: Reconstructions and Implications. Journal of Climate, 26(7), 2329–2352. <a href="https://doi.org/10.1175/JCLI-D-11-00511.1">https://doi.org/10.1175/JCLI-D-11-00511.1</a></li> <li>Fowler, A. M., Boswijk, G., Lorrey, A. M., Gergis, J., Pirie, M., McCloskey, S. P. J., et al. (2012). Multi-centennial tree-ring record of ENSO-related activity in New Zealand. Nature Climate Change, 2(3), 172–176. <a href="https://doi.org/10.1038/nclimate1374">https://doi.org/10.1038/nclimate1374</a></li> <li>Huang, B., Thorne, P. W., Banzon, V. F., Boyer, T., Chepurin, G., Lawrimore, J. H., et al. (2017). Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons. Journal of Climate, 30(20), 8179–8205. <a href="https://doi.org/10.1175/JCLI-D-16-0836.1">https://doi.org/10.1175/JCLI-D-16-0836.1</a></li> <li>Li, J., Xie, S.-P., Cook, E. R., Morales, M. S., Christie, D. A., Johnson, N. C., et al. (2013). El Niño modulations over the past seven centuries. Nature Climate Change, 3(9), 822–826. <a href="https://doi.org/10.1038/nclimate1936">https://doi.org/10.1038/nclimate1936</a></li> <li>Morales, M. S., Christie, D. A., Villalba, R., Argollo, J., Pacajes, J., Silva, J. S., et al. (2012). Precipitation changes in the South American Altiplano since 1300 AD reconstructed by tree-rings. Climate of the Past, 8(2), 653–666. <a href="https://doi.org/10.5194/cp-8-653-2012">https://doi.org/10.5194/cp-8-653-2012</a></li> <li>PAGES2k Consortium (2017). A global multiproxy database for temperature reconstructions of the Common Era. Scientific Data, 4, 170088. <a href="https://doi.org/10.1038/sdata.2017.88">https://doi.org/10.1038/sdata.2017.88</a></li> <li>Tierney, J. E., Abram, N. J., Anchukaitis, K. J., Evans, M. N., Giry, C., Kilbourne, K. H., et al. (2015). Tropical sea surface temperatures for the past four centuries reconstructed from coral archives. Paleoceanography, 30(3), 2014PA002717. <a href="https://doi.org/10.1002/2014PA002717">https://doi.org/10.1002/2014PA002717</a></li> <li>Toohey, M., & Sigl, M. (2017). Volcanic stratospheric sulfur injections and aerosol optical depth from 500 BCE to 1900 CE. Earth System Science Data, 9(2), 809–831. <a href="https://doi.org/10.5194/essd-9-809-2017">https://doi.org/10.5194/essd-9-809-2017</a></li> <li>Zhu, F., Emile-Geay, J. Hakim, G. J., Tardif, R., and Perkins., A., (2021). LMR Turbo (LMRt): a lightweight implementation of the LMR framework (0.8.0). Zenodo. <a href="http://doi.org/10.5281/zenodo.5205223">http://doi.org/10.5281/zenodo.5205223</a></li> </ul> <p><strong>How to cite this repo</strong></p> <p>This repo can be cited with <a href="https://doi.org/10.5281/zenodo.5716165">DOI: 10.5281/zenodo.5716165</a>.</p>
EIAH data model: semantic interoperability between distributed digital repositories
<p>The authors described their information architecture project aimed at improving access to the Encyclopaedia of Iranian architectural history (EIAH) by signalling relationships between concepts and between concepts and documents. The outcome will be presented in a semantic portal or might be used for complex search queries by end users.</p>
Claude_et_al_NAR_GaB_Data_repository
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FIGURE 59 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 59. Ptyas luzonensis (Sorsogon Prov., Luzon Id.) (KU uncat.; field no. RMB 23519). Photo © JBF/RMB.
FIGURE 7 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 7. Ramphotyphlops cumingii (head) (Augsan del Norte Prov., Mindanao Id.) (KU 334468). Photo © RMB.
MAPS 21A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 21A–D. Geographic range maps for Philippine records of (A) Lycodon alcalai; (B) Lycodon bibonius; (C) Lycodon capucinus; (D) Lycodon chrysoprateros.
MAPS 28A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 28A–D. Geographic range maps for Philippine records of (A) Oligodon modestus; (B) Oligodon notospilus; (C) Oligodon perkinsi; (D) Ophiophagus hannah.
data repositorie publi mannitol
<p>Data for Rapid Polymorphic Screening using Sessile Microdroplets: Competitive Nucleation of Mannitol Polymorphs<br>Ruel Cedeno, Romain Grossier, Nadine Candoni, Stéphane Veesler<br>CNRS, Aix-Marseille Université, CINaM (Centre Interdisciplinaire de Nanosciences de Marseille), Campus de Luminy, Case 913, F-13288 Marseille Cedex 09, France</p> <p>2 files: <br>file 1: data Raman for figure 2a<br>contains ascii raman data and photo of analyzed samples for the different droplet volume <br>file 2: data sigma for fig1d<br>contains greylevel standard deviation for the 40 droplets of figure 1a (time scale 2s)<br>refer to publications [1 and 2] and details in section S1 in the ESI for data treatment.<br>[1] R. Grossier, V. Tishkova, R. Morin, S. Veesler,<br>A parameter to probe microdroplet dynamics and crystal nucleation, <br>AIP Advances, 8 (2018) 075324.<br>[2] R. Cedeno, R. Grossier, V. Tishkova, N. Candoni, A.E. Flood, S. Veesler,<br>Evaporation Dynamics of Sessile Saline Microdroplets in Oil Langmuir,<br>38 (2022) 9686-9696.</p>
CircaKB Data Repository
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Child maltreatment and use of psychoactive substances in adolescence and adulthood: a systematic review and metanalysis (data repository)
<p>Data used for study titled "Child maltreatment and use of psychoactive substances in adolescence and adulthood: a systematic review and metanalysis".</p>
Data repository for the article: Fluorescence lifetime imaging unravels the pathway of glioma cell death upon hypericin-induced photodynamic therapy.
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Data repository for Uniaxial compression of 3D printed samples with voids: laboratory measurements compared with Effective Medium Theory
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Raw Image Data Repository: Repurposing Large-Format Microarrays for Scalable Spatial Transcriptomics
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Raw data repository for the article: Influence of Contacts and Applied Voltage on a Structure of a Single GaN Nanowire
<p>The archive NWrawdata.zip contains information about the raw data collected at P10 beamline at PETRA III during this experiment, which is shown in Figs. 4, 5, and 6 of the main text.</p>
Using shear-wave elastography in skeletal muscle: data repository of a reliability study
<p>This repository contains raw data from experiments investigating the reliability of shear-wave<br> elastography (SWE) to assess muscle stiffness. The first dataset contains meat specimen experiments (using<br> porcine meat specimens). The second and third datasets contain the measurements of human<br> subjects, performed on the first and second visit to the laboratory, respectively. All values are in<br> kilopascals (kPa). This experiment showed that SWE is a reliable tool for assessing muscle stiffness,<br> when the probe pressure is kept constant and the muscle is examined in relaxed condition.</p>
Supporting data for "onlineFDR: an R package to control the false discovery rate for growing data repositories"
<p>Supporting data for the manuscript "onlineFDR: an R package to control the false discovery rate for growing data repositories"</p>
Data Repository for: Machine-learning the spectral function of a hole in a quantum antiferromagnet
<p>The machine-learning dataset of 51^3 ~1.3 × 10^5 density of states (DOS) of a mobile hole in the t-t'-t''-J model theoretically generated by using the self-consistent Born approximation in the three-dimensional parameter space of t′ ∈ [−0.5, 0.5], t′′ ∈ [−0.5, 0.5] and J ∈ [0.2, 1.0], with each parameter sampled on a 51-point uniform grid. The dataset is randomly partitioned into an 80/10/10 training (T), validation (V), and testing T split. Note that each DOS A(ω) was calculated on a 1201-point uniform grid of ω ∈ [−6t, 6t], then it was resampled on a 301-point uniform grid for the forward problem and on a 354-point uniform grid for the inverse problem. The dataset used in the inverse problem is limited to the parameter space of t′ ∈ [−0.5, 0], t′′ ∈ [0, 0.5] and J ∈ [0.2, 1.0]. To open the enclosed .npz files, use numpy.load() in python3.</p>
ScienceDex guides
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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.