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71 results for “json”
huARdb Database V2 JSON Files TCR Partition 5 [N-P]
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huARdb Database V2 JSON Files TCR Partition 2
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huARdb Database V2 JSON Files TCR Partition 1
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huARdb Database V2 JSON Files TCR Partition 4 [E-F]
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huARdb Database V2 JSON Files TCR Partition 7 [P]
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huARdb Database V2 JSON Files TCR Partition 5 [F-L]
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huARdb Database V2 JSON Files TCR Partition 9 [U]
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huARdb Database V2 JSON Files TCR Partition 5 [G]
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huARdb Database V2 JSON Files TCR Partition 10
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Zenodo metadata JSON records as of 2019-09-16
<p>This preliminary dataset contains the <code>application/vnd.zenodo.v1+json</code> JSON records of <a href="http://zenodo.org/">Zenodo</a> deposits as retrieved on 2019-09-16.</p> <p><strong>Files</strong></p> <ul> <li><code>zenodo-records-json-2019-09-16.tar.xz</code> <em>Zenodo JSON records</em><br> XZ-compressed tar archive of individual JSON records as retrieved from Zenodo. Filenames reflects record, e.g. <code>1310621.json</code> was retrieved from <a href="https://zenodo.org/api/records/1310621">https://zenodo.org/api/records/1310621</a> using content-negotiation for <code>application/vnd.zenodo.v1+json</code></li> <li><code>zenodo-records-json-2019-09-16-filtered.jsonseq.xz</code> <em>Concatinated Zenodo JSON records</em><br> XZ-compressed <a href="https://tools.ietf.org/html/rfc7464">RFC7464</a> JSON Sequence stream, readable by <a href="https://stedolan.github.io/jq/manual/v1.5/">jq</a>. Concatination of Zenodo JSON records. Order not significant.</li> <li><code>zenodo-records.sh</code> <em>Retrieve Zenodo JSON records</em><br> A retrospectively created Bash shell script that shows the commands used to retrieve JSON files and concationate to jsonseq.</li> <li><code>ro-crate-metadata.jsonld</code> <em><a href="https://w3id.org/ro/crate/0.2">RO-Crate 0.2</a> structured metadata</em></li> <li><code>ro-crate-preview.html</code> <em>Browser rendering of RO-Crate structured metadata</em></li> <li><code>README.md</code> <em>This dataset description</em></li> </ul> <p><strong>License</strong></p> <p>This dataset is provided under the license <a href="https://www.apache.org/licenses/LICENSE-2.0">Apache License, version 2.0</a>:</p> <p>Copyright 2019 The University of Manchester</p> <p>Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at</p> <pre><code>http://www.apache.org/licenses/LICENSE-2.0 </code></pre> <p>Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.</p> <p><strong>CC0 for Zenodo metadata</strong></p> <p>The <a href="https://about.zenodo.org/terms/">Zenodo metadata</a> in <code>zenodo-records-json-2019-09-16.tar.xz</code> is reused under the terms of <a href="https://creativecommons.org/publicdomain/zero/1.0/">https://creativecommons.org/publicdomain/zero/1.0/</a></p> <p><strong>Reproducibility</strong></p> <p>To retrieve the Zenodo JSON it was deemed necessary to use the <a href="https://github.com/zenodo/zenodo/issues/1426#issuecomment-369171411">undocumented</a> parts of <a href="https://developers.zenodo.org/">Zenodo API</a>.</p> <p>From the <a href="https://github.com/zenodo/zenodo/blob/deploy-qa-2019-09-19-0735/zenodo/config.py#L814">Zenodo source code</a> it was identified that the REST template <code>https://zenodo.org/api/records/{pid_value}</code> could be used with <code>pid_value</code> as the numeric part from the OAI-PMH identifier, e.g. for <code>oai:zenodo.org:1310621</code> the Zenodo JSON can be retrieved at <a href="https://zenodo.org/api/records/1310621">https://zenodo.org/api/records/1310621</a>.</p> <p>The JSON API supports content negotiation, the content-types supported as of 2019-09-20 include:</p> <ul> <li><code>application/vnd.zenodo.v1+json</code> giving the Zenodo record in Zenodo's <a href="https://github.com/zenodo/zenodo/blob/deploy-qa-2019-09-19-0735/zenodo/modules/records/serializers/schemas/json.py#L267">internal JSON schema</a> (v1)</li> <li><code>application/ld+json</code> giving <a href="https://www.w3.org/TR/2014/REC-json-ld-20140116/">JSON-LD</a> Linked Data using the <a href="http://schema.org/">http://schema.org/</a> vocabulary</li> <li><code>application/x-datacite-v41+xml</code> giving <a href="https://doi.org/10.5438/0012">DataCite v4 XML</a></li> <li><code>application/marcxml+xml</code> giving <a href="http://www.loc.gov/standards/marcxml/">MARC</a> 21 XML</li> </ul> <p>Using these (currently) undocumented parts of the Zenodo API thus avoids the need for HTML scraping while also giving individual complete records that are suitable to redistribute as records in a filtered dataset.</p> <p>This preliminary exploration will be adapted into the reproducible CWL workflow, for now included as a Bash script <code>zenodo-records.sh</code></p> <p>Execution time was about 3 days from a server at the University of Manchester network on a single 1 GBps network link. The script does:</p> <ul> <li>Retrieve each of the first 3.5 million Zenodo records<br> as Zenodo JSON by iterating over possible numeric IDs (the maximum ID <code>3450000</code> was estimated from <a href="https://zenodo.org/">"Recent uploads"</a>)</li> <li>Filter list to exclude records that are not found, moved or deleted. The presence of the key <code>conceptrecid</code> is used as marker.</li> <li>Use <a href="https://stedolan.github.io/jq/manual/v1.5/">jq</a> to ensure the JSON is on a single line</li> <li>Join the JSON files using the ASCII Record Separator (RS, <code>0x1e</code>) to make a <code>application/json-seq</code> <a href="https://doi.org/10.17487/RFC7464">JSON text sequence</a> stream</li> <li>Save the JSON stream as a single compressed file using <code>xz</code></li> </ul>
Soil science JSON files
<p>JSON files that will be harvested in the process in ORKG.</p>
Google Map JSON data file
<p>A data file used by several JSON engine.</p>
BestBuy JSON dataset
<p>Dataset used in several JsonPath engines.</p>
WFO Plant List JSON Datasets 2018 to 2022
<p>Every six months the <a href="http://www.worldfloraonline.org/">World Flora Online</a> publishes a new checklist of plant names. The checklist is available at <a href="https://doi.org/10.5281/zenodo.7467360">doi:10.5281/zenodo.7467360</a></p> <p>In December 2022 the publication mechanism began to include the data in JSON format for direct import into a <a href="https://solr.apache.org/">SOLR</a> index. As part of this change JSON format files were created for the previous data releases so that they can be imported into the same SOLR index as those from December 2022 onwards. This archive contains those JSON files.</p> <p>It is be possible to create the full history of the WFO Plant List in a SOLR index by loading these files followed by the JSON files provided in each data release from December 2022 onward.</p> <p> </p>
Schema.org Characteristic Sets computed from the JSON-LD subset of Web Data Commons dataset (October 2021 release)
<p>This dataset reports the computation of Characteristic Sets from the JSON-LD subset of Web Data Commons dataset (October 2021 release). Each row consists in a combination of Schema.org properties and its cardinality. </p>
Collection of Object-Centric Event Logs (OCEL 1.0 format; JSON-OCEL specification)
<p>We provide some realistic examples of logs in the OCEL standard. The logs have originally been published at https://www.ocel-standard.org/ </p>
Primary metric measurements of USA tree rings in one dataset in JSON format.
<p>The International Tree Rings Data Bank (ITRDB) is the most comprehensive tree growth database (https://www1.ncdc.noaa.gov/pub/data/paleo/treering).</p> <p>Shoudong Zhao, et al. (2019, 2018) analyzes the representativity of dendrochronological data (ITRDB) and proposes a corrected database with error indications. One of the bottlenecks of data use (ITRDB) is that the data is loaded as a collection of separate files in the Tucson positional format.</p> <p>The purpose of our data presentation is to change the Tucson data format to JSON format and combine the separate files into one.</p> <p>We convert the initial data for the USA of 2298 rwl-files into Json format of data on tree growth in one file. The data was converted using the R programming language and the dplR program library Bunn, A. (2008)</p> <p>The experience of developing the structure of dendroclimatic data in JSON format is described in the works of Kachaev A. (2016, 2017, 2020).</p> <p>Description of the structure of JSON data format is attached in the file ReadMe.pdf</p> <p> </p> <p><em>References</em></p> <p><em>Bunn, A. G. (2008). A dendrochronology program library in R (dplR). Dendrochronologia, 26, 115-124. https://doi.org/10.1016/j.dendro.2008.01.002</em></p> <p><em>Kachaev, Alexander (2020), "Compact dataset of dendrochronological data of pri-mary metric characteristics of tree rings of Asia.", Mendeley Data, V1, doi: 10.17632 / p9zhpmzgtk.1</em></p> <p><em>Kachaev A. V. (2017) Model for describing the structure of dendroclimatic data In the collection: Regional problems of remote sensing of the Earth Materials of the IV international scientific conference. Siberian Federal University, Institute of Space and Information Technologies. p. 120-122. (Russia)</em></p> <p><em>Kachaev A. V. (2016) NOSQL Approach for Development of Dendroclimatic Data Bank. In the collection: Regional problems of remote sensing of the Earth. Materials of the III International Scientific Conference. p. 89-91. (Russia)</em></p> <p><em>Shoudong Zhao, et al. (2019). The International Tree-Ring Data Bank (ITRDB) revisited: Data availability and global ecological representativity. Journal of Biogeography, 46 (2), 355-368. doi: 10.1111 / jbi.13488</em></p> <p><em>Zhao, Shoudong et al. (2018), Data from: The International Tree-Ring Data Bank (ITRDB) revisited: data availability and global ecological representativity, Dryad, Dataset, https://doi.org/10.5061/dryad.kh0qh06</em></p>
MSnLib Mass spectral libraries (.mgf and .json)
<p>The data for <a href="https://doi.org/10.26434/chemrxiv-2024-l1tqh-v2">MSnLib</a> are divided into several Zenodo records due to size constraints. </p> <p>raw positive: <a href="https://doi.org/10.5281/zenodo.10966404">10966404</a><br>raw negative: <a href="https://doi.org/10.5281/zenodo.10967081">10967081</a><br>mzml positive and negative: <a href="https://doi.org/10.5281/zenodo.10966280">10966280</a><br>spectral libraries: <a href="https://doi.org/10.5281/zenodo.11163380">11163380</a></p> <p>This record includes the automatically generated spectral libraries (MSnLib) within mzmine, acquired using a flow injection method on an Orbitrap ID-X instrument, for all compound libraries. There are multiple files for each compound library containing MS2 only or MSn in two data formats (.mgf or .json) for both polarities. </p> <p>MS2 contains next to all MS2 spectra all pseudo MS2 spectra (a full MSn tree merged into one spectrum per compound ion). MSn contains all individual MSn stages additionally. The first number for each file highlights the library building date.</p> <p>9 Compound Libraries:</p> <ul> <li>Short Name: Full name, Provider (Catalog number), total compounds (not all detected during library building)</li> <li>MCEBIO: Bioactive Compound Library, MedChemExpress (HY-L001), 10,315 compounds</li> <li>MCESAF: 5k Scaffold Library, MedChemExpress, (HY-L902), 4998 compounds</li> <li>NIHNP: NIH NPAC ACONN collection of NP, NIH/NCATS, 3988 compounds</li> <li>OTAVAPEP: Alpha-helix Peptiomimetic Library, OTAVAchemicals (a-helix-Peptido), 1298 compounds</li> <li>ENAMDISC: Discovery Diversity Set -10, Enamine (DDS-10), 10,240 compounds</li> <li>ENAMMOL: Carboxylic Acid Fragment Library + Random, Enamine and Molport, 4378 compounds</li> <li>MCEDRUG: FDA-Approved Drug Library, MedChemExpress (HY-L022), 2610 compounds</li> <li>MCEDIV_50k_Sub: Subset of 50K Diversity Library, MedChemExpress (HY-L901), 20000 compounds</li> <li>TargetMolHTSNP: Subset of Natural Product Library for HTS, TargetMol (L6000), 2175 compounds</li> </ul> <p>Information regarding the SPECTYPE</p> <ul> <li>no SPECTYPE or SINGLE_BEST_SCAN: Best spectrum for each precursor and energy (highest TIC)</li> <li>'SAME_ENERGY' = Additionally, if a spectrum was acquired multiple times for a precursor with the same energy, they are merged into one spectrum only with the same energy (max. signal height used for each fragment signal).</li> <li>'ALL_ENERGIES' = merged spectrum of all used energies (in our case 3 for each precursor, using the merged (same energy) if available).</li> <li>'ALL_MSN_TO_PSEUDO_MS2' = mzmine merges all MSn into one pseudo MS2.</li> </ul> <p> </p> <p>MCEDIV and TargetmolNPHTS </p>
Semantics Conflicts for Edge (JSON)
<p>Semantics Conflicts for Edge (JSON)</p>
Test Article with ODRL Metadata_json_test1
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.