Find research datasets worth reusing

opencc-by-4.0Oct 2019View details →

Written and spoken digits database for multimodal learning

Database description: The written and spoken digits database is not a new database but a constructed database from existing ones, in order to provide a ready-to-use database for multimodal fusion [1]. The written digits database is the original MNIST handwritten digits database [2] with no additional processing. It consists of 70000 images (60000 for training and 10000 for test) of 28 x 28 = 784 dimensions. The spoken digits database was extracted from Google Speech Commands [3], an audio dataset of spoken words that was proposed to train and evaluate keyword spotting systems. It consists of 105829 utterances of 35 words, amongst which 38908 utterances of the ten digits (34801 for training and 4107 for test). A pre-processing was done via the extraction of the Mel Frequency Cepstral Coefficients (MFCC) with a framing window size of 50 ms and frame shift size of 25 ms. Since the speech samples are approximately 1 s long, we end up with 39 time slots. For each one, we extract 12 MFCC coefficients with an additional energy coefficient. Thus, we have a final vector of 39 x 13 = 507 dimensions. Standardization and normalization were applied on the MFCC features. To construct the multimodal digits dataset, we associated written and spoken digits of the same class respecting the initial partitioning in [2] and [3] for the training and test subsets. Since we have less samples for the spoken digits, we duplicated some random samples to match the number of written digits and have a multimodal digits database of 70000 samples (60000 for training and 10000 for test). The dataset is provided in six files as described below. Therefore, if a shuffle is performed on the training or test subsets, it must be performed in unison with the same order for the written digits, spoken digits and labels.   Files: <ul> <li>data_wr_train.npy: 60000 samples of 784-dimentional written digits for training;</li> <li>data_sp_train.npy: 60000 samples of 507-dimentional spoken digits for training;</li> <li>labels_train.npy: 60000 labels for the training subset;</li> <li>data_wr_test.npy: 10000 samples of 784-dimentional written digits for test;</li> <li>data_sp_test.npy: 10000 samples of 507-dimentional spoken digits for test;</li> <li>labels_test.npy: 10000 labels for the test subset.</li> </ul>   References: <ol> <li>Khacef, L. et al. (2020), "Brain-Inspired Self-Organization with Cellular Neuromorphic Computing for Multimodal Unsupervised Learning".</li> <li>LeCun, Y. & Cortes, C. (1998), “MNIST handwritten digit database”.</li> <li>Warden, P. (2018), “Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition”.</li> </ol>

opencc-by-4.0Mar 2017View details →

Experimental Organic Rankine Cycle database - v2016.12

Database on experimental Organic Rankine Cycle units. Dec. 2016 version. Supplementary materiel of the ICAE 2016 conference paper entitle "Performance Evaluation and Comparison of Experimental Organic Rankine Cycle Prototypes from Published Data" and the extended paper entitled "Organic Rankine cycle design and performance comparison based on experimental database" publish in Applied Energy - ICAE2016 Special Issue.

opencc-by-4.0Nov 2024View details →

DebDaB: A database of supraglacial debris thickness and physical properties

DebDaB: A database of supraglacial debris thickness and physical properties DebdaB is a database of measured and reported physical properties and thickness of supraglacial debris that is openly available and open to community submissions. The majority of the database (90%) is compiled from 172 sources in the literature, and the remaining 10% has not been published before. DebDaB contains 8,286 data entries for supraglacial debris thickness, of which 1,852 entries also include sub-debris ablation rates, 167 data entries of thermal conductivity of debris, 157 of aerodynamic surface roughness length, 77 of debris albedo, 56 of debris emissivity and 37 of debris porosity. The data are distributed over 83 glaciers in 13 regions in the Global Terrestrial Network for Glaciers.  This is version 2 of the dataset, corresponding to the revised version of the database after peer-review of its accompanying "Data descriptor manuscript" submitted for publication to the scientific journal "Earth System Science Data (ESSD)" from Copernicus Publications. The preprint is available at <a href="https://doi.org/10.5194/essd-2024-559">https://doi.org/10.5194/essd-2024-559 </a> DebDaB version 2 consists of the following files: <ul> <li>DebDaB_v2.zip : The actual DebDaB database, provided as a navigable Open Document Spreadsheet (.ods) with spreadsheet tabs for each of the debris properties. Additionally, the database is also provided as separate .csv files for each debris property, and as a GeoPackage (.gpkg). </li> <li>Readme_files.zip: A .txt file for each of the debris property tabs, describing all the fields in each tab. </li> <li>Templates_for_data_submission.zip: Templates (.csv files and additionally .xlsx files) for data submission for each of the debris properties in DebDaB. Data submissiosn to DebDaB should be sent to debriscoveredglaciers@ista.ac.at. </li> <li>DebDaB_data_sources.pdf: List of DebDaB sources from published literature. </li> <li>DebDaB_data_sources.bib: BibTeX list of DebDaB sources from published literature. </li> <li>Manuscript_codes.zip: The codes to download and process the data to generate the figures for data descriptor manuscript on ESSD.</li> </ul> The data descriptor manuscript is in open review stage at: <a href="https://essd.copernicus.org/preprints/essd-2024-559/">https://essd.copernicus.org/preprints/essd-2024-559/ </a> DebDaB is open to new data submissions, and therefore future data submissions of previously unpublished data to DebDaB will entail co-authorship on the DebDaB database on Zenodo.  According to the authors’ understanding of FAIR principles, authors of published literature and published data, that: <ul> <li>Correct existing data within DebDaB, in case of errors</li> <li>Send the raw data from digitised figures</li> <li>Submit additional data that was previously unavailable (for example, accurate coordinates or additional data or metadata which is not already available)</li> </ul> <div>will have the right to be added as co-authors on the database in Zenodo. The authors are working to reevaluate their policies to conform to changes or unusual circumstances in authorship contributions, and are happy to involve eager people in the core team.</div> <div> </div> <div>How to submit data: Please use the templates provided in the database files for data submissions and send it to debriscoveredglaciers@ista.ac.at. Authors who submit data will be asked to fill in a form regarding authorship contributions. </div> Important note on citations: DebDaB data users must cite the data descriptor manuscript (Fontrodona-Bach et al. 2025), the DebDaB zenodo repository (Groeneveld et al., 2025), and the original data sources when using the database, given that DebDaB is mostly a compilation of previously published data. To facilitate the citations of original data sources, each of the data entries in DebDaB contains the corresponding original reference and corresponding DOI. Manuscript citation: Fontrodona-Bach, A., Groeneveld, L., Miles, E., McCarthy, M., Shaw, T., Melo Velasco, V., and Pellicciotti, F.: DebDaB: A database of supraglacial debris thickness and physical properties, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2024-559, in review, 2025. Zenodo citation: Groeneveld, L., Fontrodona-Bach, A., Miles, E., McCarthy, M., Melo Velasco, V., Shaw, T., Pellicciotti, F., Bauder, A., Buri, P., Kneib, M., Kumar, A., Mishra, A., & Petersen, L. (2025). DebDaB: A database of supraglacial debris thickness and physical properties (Version v2) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.14514803" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.</a><a href="https://doi.org/10.5281/zenodo.14224835" target="_blank" rel="noopener">14224835</a> Original data sources citation: See DebDaB_data_sources.pdf or DebDaB_data_sources.bib The authors acknowledge the Debris-Covered Glaciers Working Group (DCGWG) from the International Association of Cryospheric Sciences (IACS) for setting the stage and drawing together the debris-covered glaciers community to focus on broader needs transcending a specific research topic, and starting the zenodo community on debris-covered glaciers, where this database is hosted.  Author contributions: The following spreadsheet states the contribution of each of the co-authors on the database:   <a href="https://docs.google.com/spreadsheets/d/1nTieH_ZkwqnUpHQMYn7bygEcV5RzX4DJuqZ_qd-_PzE/edit?usp=sharing" target="_blank" rel="noopener">Author contributions statement (click here)</a> A description of what each contribution field means is below: <ul> <li>Conceptualisation: This refers to the original idea and shaping of the database and is therefore closed.</li> <li>Data curation: The data managers of DebDaB. Primarily the quality checks and curation done to all the collected published and unpublished data. It may also include authors who have compiled a lot of measurements from sources the authors did not have, and merged them into DebDaB, or if someone else takes on the role of ingesting/homogenizing data in the future.</li> <li>Data collection: Field measurements as well as scouring past literature that the authors have missed, digitising sources, or advocating for old missing data sources to be entered into DebDaB.</li> <li>Formal analysis: In the case of methods being applied to derive debris property values from other measurements, such as the case for surface roughness and thermal conductivity.</li> <li>Supervision/funding: This refers to funding provided for the generation of DebDaB itself, but also funding for the data collection (measurements). </li> </ul>

opencc-by-4.0Mar 2023View details →

Climate Policy Database

Recommended Citation Citing this version <pre><code>NewClimate Institute, Wageningen University and Research &amp; PBL Netherlands Environmental Assessment Agency. (2024).   Climate Policy Database. DOI: 10.5281/zenodo.154329464</code></pre> Citing all CPDB versions <pre><code>NewClimate Institute, Wageningen University and Research &amp; PBL Netherlands Environmental Assessment Agency. (2016).   Climate Policy Database. DOI: 10.5281/zenodo.7774109</code></pre> Peer reviewed publication Description The <a href="http://www.climatepolicydatabase.org">Climate Policy Database</a> (CDPB) is an open, collaborative tool to advance the data collection of the implementation status of climate policies. This project is funded by the European Union H2020 ELEVATE and ENGAGE projects and was, in its previous phase, funded under CD-Links. The database is maintained by NewClimate Institute with support from PBL Netherlands Environmental Assessment Agency and Wageningen University and Research. Although the CPDB exists since 2016, annual versions of the database have only been stored since 2019.  The Climate Policy Database is updated periodically. The latest version of the database can be downloaded on the CPDB website or accessed through a <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fpypi.org%2Fproject%2Fcpdb-api%2F&data=05%7C01%7C%7C49011f9a98bd4ff09fa708db92950abd%7C585861118d7348a084329a4ebaecc491%7C1%7C0%7C638264941080639305%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=S7DUrVJOMBNLT1gOB8S7%2FcnlWqFw8z6mBD3wHI%2F9krY%3D&reserved=0">Python API</a>. Each year, we also create a static database, which is included here for version control.

Database on vacancies in selected non-EU countries

This database is a revised version of the deliverable D3.1 of the Horizon Europe project 'Global Strategy for Skills, Migration and Development' (GS4S). For more information, please see the associated working paper: Locating Shortages in Migrants’ Origin Countries: A Big Data Approach, authored by Friedrich Poeschel.

opencc-by-4.0Mar 2021View details →

S77 | FCCDB | Food Contact Chemicals Database v5.0

This is the collection associated with list S77 FCCDB Food Contact Chemicals Database v5.0 on the NORMAN Suspect List Exchange. <a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a> The Food Contact Chemicals database (FCCdb, DOI: <a href="http://doi.org/10.5281/zenodo.4296944">10.5281/zenodo.4296944</a>) is a compilation of information on intentionally added food contact chemicals, extracted from publicly available sources such as legislation on food contact materials and industry inventories for different types of food contact materials. Where available, information from a few selected sources on hazardous properties and commercial use has been included as well. Further details on the information sources used are given in the READ ME worksheet of the excel file. The FCCdb intends to provide an overview of the diversity of food contact chemicals and their hazardous properties. Further details on the compilation and analysis of this dataseta can be found in the manuscript "Overview of intentionally used food contact chemicals and their hazards," by Ksenia J. Groh, Birgit Geueke, Olwenn Martin, Maricel Maffini, and Jane Muncke, published in Environmental International on November 30, 2020 (DOI: <a href="http://doi.org/10.1016/j.envint.2020.106225">10.1016/j.envint.2020.106225</a>). Structural information has been added to this dataset (downloaded from DOI: <a href="http://doi.org/10.5281/zenodo.4296944">10.5281/zenodo.4296944</a>) upon request of the authors by Parviel Chirsir (during an internship at LCSB, supervised by Emma Schymanski) using CompTox and PubChem resources, before being uploaded to the NORMAN-SLE. Details are provided in the READ ME worksheet. See changelog file for a record of changes. Please check the licensing on the original dataset for full re-use conditions (DOI: <a href="http://doi.org/10.5281/zenodo.4296944">10.5281/zenodo.4296944</a>)

opencc-by-4.0Jun 2018View details →

S29 | PHYTOTOXINS | Toxic Plant Phytotoxin (TPPT) Database

This is the collection associated with list S29 PHYTOTOXINS on the NORMAN Suspect List Exchange. <a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a> S29  PHYTOTOXINS  Toxic Plant Phytotoxin (TPPT) Database A comprehensive toxic plant-phytotoxin (TPPT) database provided by Günthardt et al 2018, DOI: <a href="https://pubs.acs.org/doi/10.1021/acs.jafc.8b01639">10.1021/acs.jafc.8b01639</a> More information on the <a href="https://www.agroscope.admin.ch/agroscope/en/home/publications/apps/tppt.html">Agroscope TPPT website</a>. Updated 20/11/2019 to correct InChIKey errors; updated 16/7/2022 to create merged SMILES column for PubChem deposition. 27/6/2025 added new CSV without duplicate CAS headers.

opencc-by-4.0Mar 2019View details →

S49 | CPPDBLISTB | Database of Chemicals possibly (List B) associated with Plastic Packaging (CPPdb)

This is the collection associated with list S49 CPPDBLISTB on the NORMAN Suspect List Exchange. <a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a> S49 | CPPDBLISTB | Database of Chemicals associated with Plastic Packaging (CPPdb) A database of chemicals likely (List A, 903 - in another upload) and possibly (List B, 3353 - this upload) associated with plastic packaging, with hazard data, from Groh et al 2019 DOI: <a href="https://doi.org/10.1016/j.scitotenv.2018.10.015">10.1016/j.scitotenv.2018.10.015</a>. Mapped to structures by CAS/Name by K. Groh & E. Schymanski. 2025: added new CSV file with duplicate headers renamed.  Latest version of original data (last update Oct 2018): DOI: <a href="http://doi.org/10.5281/zenodo.1287773">10.5281/zenodo.1287773</a>

opencc-by-4.0Apr 2024View details →

The Pathogen-Host Interactions Database, version 4.18

PHI-base is an online database (available at <a href="http://www.phi-base.org">phi-base.org</a>) that catalogues experimentally verified pathogenicity, virulence and effector genes from fungal, oomycete and bacterial pathogens, which infect animal, plant, fungal and insect hosts. PHI-base is a valuable resource in the discovery of genes in medically and agronomically important pathogens, which may be potential targets for chemical intervention. Each entry in PHI-base is curated by domain experts and is supported by strong experimental evidence (for example, gene disruption and gene complementation experiments), as well as literature references in which the original experiments are described. Each gene in PHI-base is presented with its nucleotide sequence and deduced amino acid sequence (available in a FASTA file), as well as a detailed description of the predicted protein's function during the host infection process. To facilitate data interoperability, we have annotated genes using ontologies, controlled vocabularies, and links to external sources (including UniProt, Gene Ontology, Enzyme Commission, NCBI Taxonomy, EMBL, PubMed and FRAC). This PHI-base dataset is a Frictionless Data Package that contains an export of the PHI-base database in CSV format (comma-separated values), plus a FASTA file with sequences for each gene in the database. This version of the dataset, version 4.18, contains 5,828 publications, covering 23,497 pathogen–host interactions and 10,614 pathogen genes across 335 pathogen species and 265 host species.

opencc-by-4.0Nov 2021View details →

Modern China Geospatial Database - Main Dataset

MCGD_Data_V2.2 contains all the data that we have collected on locations in modern China, plus a number of locations outside of China that we encounter frequently in historical sources on China. All further updates will appear under the name "MCGD_Data" with a time stamp (e.g., MCGD_Data2023-06-21) You can also have access to this dataset and all the datasets that the ENP-China makes available on GitLab: https://gitlab.com/enpchina/IndexesEnp Altogether there are 464,970 entries. The data include seven variables: - Name:  Place names and their variants in Chinese, pinyin, and any recorded transliteration - Prov_Zh: Chinese province names in Chinese characters (新疆, 江蘇, 河北, etc.) - Prov_Py: Chinese province names in pinyin - LAT: Latitude coordinates - LONG: Longitude coordinates - LocID: Location identifiers - NameID: Location name identifiers The Name IDs all start with H followed by seven digits. This is the internal ID system of MCGD. Locations IDs that start with "D" are data points extracted from China Historical GIS (Harvard University); those that start with "E" are locations extracted from the data points in Geonames or data points we have added from various map sources. One of the main features of the MCGD Main Dataset is the systematic collection and compilation of place names from non-Chinese language historical sources. Locations were designated in transliteration systems that are hardly comprehensible today, which makes it very difficult to find the actual locations they correspond to. This dataset allows for the conversion from these obsolete transliterations to the current names and geocoordinates. From June 2021 onward, we have adopted a different file naming system to keep track of versions. From MCGD_Data_V1 we have moved to MCGD_Data_V2. In June 2022, we introduced time stamps, which result in the following naming convention: MCGD_Data_YYYY.MM.DD.    UPDATES MCGD_Data2025_08_06 introduces a significant update with the addition of the ‘Code’ column. This column categorizes place names as follows: <ul> <li> A: Canonical Chinese name </li> <li> C: Alternative Chinese name </li> <li> P: Romanized name in pinyin </li> <li> W: Romanized name in another transliteration system </li> </ul> When the codes P or W are doubled (PP, WW), this indicates that the place name does not match any existing Chinese name in the dataset. These unmatched names will be reviewed and linked progressively, rather than through a systematic batch process, due to their high volume.The coding system is designed to facilitate name-matching operations between MCGD and place names extracted from historical sources using programming tools. It also enables filtering for more precise and efficient matching. The dataset contains a total of 472,749 entries. MCGD_Data2025_02_28 includes a major change with the duplication of all the locations listed under Beijing, Shanghai, Tianjin, and Chongqing (北京, 上海, 天津, 重慶) and their listing under the name of the provinces to which they belonge origially before the creation of the four special municipalities after 1949. This is meant to facilitate the matching of data from historical sources. Each location has a unique NameID. Altogether there are 472,818 entries MCGD_Data2025_02_27 inclues an update on locations extracted from  Minguo zhengfu ge yuanhui keyuan yishang zhiyuanlu 國民政府各院部會科員以上職員錄 (Directory of staff members and above in the ministries and committees of the National Government). Nanjing: Guomin zhengfu wenguanchu yinzhuju 國民政府文官處印鑄局國民政府文官處印鑄局, 1944). We also made corrections in the Prov_Py and Prov_Zh columns as there were some misalignments between the pinyin name and the name in Chines characters. The file now includes 465,128 entries. MCGD_Data2024_03_23 includes an update on locations in Taiwan from the Asia Directories. Altogether there are 465,603 entries (of which 187 place names without geocoordinates, labelled in the Lat Long columns as "Unknown"). MCGD_Data2023.12.22 contains all the data that we have collected on locations in China, whatever the period. Altogether there are 465,603 entries (of which 187 place names without geocoordinates, labelled in the Lat Long columns as "Unknown"). The dataset also includes locations outside of China for the purpose of matching such locations to the place names extracted from historical sources. For example, one may need to locate individuals born outside of China. Rather than maintaining two separate files, we made the decision to incorporate all the place names found in historical sources in the gazetteer. Such place names can easily be removed by selecting all the entries where the 'Province' data is missing.

opencc-by-4.0Jan 2018View details →

Mammal Diversity Database

Accurate taxonomy is central to the study of biological diversity, as it provides the needed evolutionary framework for taxon sampling and interpreting results. While the number of recognized species in the class Mammalia has increased through time, tabulation of those increases has relied on the sporadic release of revisionary compendia like the Mammal Species of the World (MSW) series. Here, we present the Mammal Diversity Database (MDD), a digital, publically accessible, and updateable list of all mammalian species, now available online: <a href="https://mammaldiversity.org">https://mammaldiversity.org</a>. The MDD will continue to be updated as manuscripts describing new species and higher taxonomic changes are released. Starting from the baseline of the 3rd edition of MSW (MSW3), we performed a review of taxonomic changes published since 2004 and digitally linked species names to their original descriptions and subsequent revisionary articles in an interactive, hierarchical database. The MDD provides the mammalogical community with an updateable online database of taxonomic changes, joining digital efforts already established for amphibians (AmphibiaWeb, AMNH’s Amphibian Species of the World), birds (e.g., Avibase, IOC World Bird List, HBW Alive), non-avian reptiles (The Reptile Database), and fish (e.g., FishBase, Catalog of Fishes). Development for this work is funded primarily by the <a href="http://www.mammalsociety.org/">American Society of Mammalogists</a> (ASM; 2017-present), with logistical and planning support provided related grants at different time points (2025-present: <a href="https://reporter.nih.gov/search/jHonNExiyEulTWBDs1zc-Q/project-details/11022146">NIH R35</a> to Upham; 2021-2023: <a href="https://reporter.nih.gov/search/jHonNExiyEulTWBDs1zc-Q/project-details/10289637">NIH R21</a> to Upham, Reeder, Sterner, Sen; 2017-2019: <a href="http://vertlife.org/grant/">NSF Vertlife Terrestrial grant</a>). The <a href="http://www.mammalsociety.org/committees/biodiversity">ASM Biodiversity Committee</a> compiles and maintains the MDD, curating regular releases that are downloadable in comma-delimited format. Downstream goals include expanded hosting of ecological, trait, and taxonomic data. Overall, this initiative aims to promote the ASM’s role as a leader in high quality research on mammalian biology. A new section on Subjective Decisions has been added to the <a href="https://www.mammaldiversity.org/about.html">MDD About page</a> for use in summarizing opinion-based decisions of the MDD team that depart from the most recently published peer-reviewed article on a given taxon. Some of these decisions are made in collaboratoration with the Global Bat Taxonomy Working Group of the <a href="https://www.iucnbsg.org/">IUCN SSC Bat Specialist Group</a> to promote harmonization between the MDD and batnames.org. Future subjective decisions will also be authored by the MDD Taxonomic Subcommittees that we are assembling in early 2024. VERSIONS Version 2.3 (1 Sep 2025). This is an incremental release that documents 6,836 total species, of which 113 are recently extinct (+1 from previous version: Galea tixiensis, found to have gone extinct in the past 500 years) and 6,723 are extant (17 domestic extant, 6,705 wild extant). There are 224 species flagged for further review. The Cell-by-Cell Tracked Differerences file ("Diff-AllChanges_v2.2-v2.3.csv") lists 1,325 changes to cells in the matrix that occurred between v2.2 and v2.3 as arranged by column, new value, and old value. This detailed tracking complements the Summary Tracked Differences file ("Diff_v2.2-v2.3.csv"), which documents 65 taxonomic changes made since MDD v2.2. Differences include 27 new species recognized (16 de novo, 11 split), 7 synonymizations (lumps), 4 genera newly added (Nagasorex, Breviforamen, Incanomys, Aethalodelphis) and 2 genera lumped (Sagmatias--changed to Aethalodelphis; and Maxomys--all species transferred to Crunomys), as well as 27 species with genus name changes and 3 tribes added. The typeVoucher field is now filled for 6,189 accepted species, with corresponding typeKind categorizations for all those (e.g., holotype, lectotype, neotype, syntype). Hyperlinks to those type specimens are available in typeVoucherURIs for 3,682 species. Links to authority species citations in the authoritySpeciesLink field are now available for 6,442 species. In total, there was a net increase of 21 species and 2 genera of recognized extant or recently extinct mammals since MDD v2.2. Note also that the 1500th species of bat was also recognized in MDD v2.3 -- Pipistrellus etula described by Torrent et al. (2025) -- see press release by Bat Conservational International (forthcoming). Version 2.2 (13 Jun 2025). This is an incremental release that documents 6,815 total species, of which 112 are recently extinct (identical to previous version) and 6,703 are extant (17 domestic extant, 6,686 wild extant). There are still 223 species flagged for further review. The Cell-by-Cell Tracked Differerences file ("Diff-AllChanges_v2.1-v2.2.csv") lists 6,638 changes to cells in the matrix that occurred between v2.1 and v2.2 as arranged by column, new value, and old value. The majority of these changes are to higher taxonomic categories that were a focus of the curation this version (tribe: 533 changes; superorder: 133; superfamily: 1,541; suborder: 1,764; subgenus: 445; subfamily: 415; subclass: 5; specificEpithet: 8; parvorder: 572; infraorder: 287; genus: 20). This detailed tracking complements the Summary Tracked Differences file ("Diff_v2.1-v2.2.csv"), which documents 382 taxonomic changes made since MDD v2.1. Differences include 14 new species recognized (13 de novo, 4 split), 3 synonymizations (lumps), 2 genera split and newly added (Pipistrellus to Alionoctula; Phodopus to Cricetiscus), 20 species with genus name changes, 2 species epithet changes, 340 higher taxonomy changes (as mentioned above), and 107 species with common name changes (spelling or geographic consistency). The typeVoucher field is now filled for 5,948 accepted species, with corresponding typeKind categorizations for all those (e.g., holotype, lectotype, neotype, syntype). Hyperlinks to those type specimens are available in typeVoucherURIs for 3,649 species. Links to authority species citations in the authoritySpeciesLink field are now available for 6,420 species. In total, there was a net increase of 14 species and 2 genera of recognized extant or recently extinct mammals since MDD v2.1. Version 2.1 (6 Apr 2025). This is an incremental release that documents 6,801 total species, of which 112 are recently extinct (compared to 113 previously; Lagostomus crassus was lumped into L. maximus) and 6,689 are extant (17 domestic extant, 6,672 wild extant). There are now 223 species flagged for further review. A new addition to the MDD in v2.1 is the inclusion of a Cell-by-Cell Tracked Differerences file ("Diff-AllChanges_v2.0-v2.1.csv"), which lists 4,683 changes to cells in the matrix that occurred between v2.0 and v2.1 as arranged by column, new value, and old value. This detailed tracking complements the Summary Tracked Differences file ("Diff_v2.0-v2.1.csv"), which documents 215 taxonomic changes made since the MDD v2.0 taxonomic cutoff of 15 Aug 2024. Differences include 57 new species recognized (26 de novo, 31 split), 14 synonymizations (lumps), 1 species removal for unavailable name, 4 genera split and newly added (Afropipistrellus, Casiomys, Megascapheus, Nyctinomus), 20 species with genus name changes, 6 spelling changes, 2 tribe changes, and 114 species with common name changes (spelling or geographic consistency). The typeVoucher field is now filled for 5,918 accepted species, with corresponding typeKind categorizations for all those (e.g., holotype, lectotype, neotype, syntype). Hyperlinks to those type specimens are available in typeVoucherURIs for 3,641 species. Links to authority species citations in the authoritySpeciesLink field are now available for 6,406 species. In total, there was a net increase of 42 species and 4 genera of recognized extant or recently extinct mammals since MDD v2.0. Version 2.0 (15 Aug 2024 cutoff date — 11 Mar 2025 publication date). This is a major release – MDD2 – that documents 7 years of taxonomic curation efforts since the taxonomic cutoff of MDD v1.0 (15 Aug 2017). The MDD2 includes 6,759 total species, of which 113 are recently extinct and 6,646 are extant (17 domestic extant, 6,629 wild extant). There are now 217 species flagged for further review (125 Artiodactyla, 57 Primates, 12 Lagomorpha, 7 Rodentia, 8 Carnivora, 6 Perissodactyla, 1 Microbiotheria, 1 Diprotodontia). Key updates in MDD2 include: <ol> <li>Codings of US state, country, continent, and biogeographic realm geographic categories for each species (fields of subregionDistribution, countryDistribution, continentDistribution, biogeographicRealm, respectively);</li> <li>Curated Species-level Synonyms file ("Species_Syn_v2.0.csv") containing 50,230 valid and synonymous species-rank names, including name combinations and type locality and specimen information for the first time; and</li> <li>Integration between the MDD and the databases Hesperomys and Batnames for greater data accuracy and completeness.</li> <li>Updated data presentations by MDD student programmer <a href="https://www.hhandika.com/">Heru Handika</a>: <ol> <li>Improved website at <a href="https://www.mammaldiversity.org/">https://www.mammaldiversity.org/</a> that is fully re-written, including a migration from Jekyll (<a href="https://jekyllrb.com/">https://jekyllrb.com/</a>) to the Astro web-framework (<a href="https://astro.build/">https://astro.build/</a>) with TypeScript (<a href="https://www.typescriptlang.org/">https://www.typescriptlang.org/</a>), and Tailwind CSS (<a href="https://tailwindcss.com/">https://tailwindcss.com/</a>) integration</li> <li>New MDD app wrote using the Flutter framework (<a href="https://flutter.dev/">https://flutter.dev/</a>) and the Rust programming language (<a href="https://www.rust-lang.org/">https://www.rust-lang.org/</a>). It supports iOS, iPadOS, Android, Windows, Linux, and macOS. Details on installing the app are available at <a href="https://github.com/mammaldiversity/mdd_app">https://github.com/mammaldiversity/mdd_app</a>.</li> </ol> </li> </ol> The typeVoucher field (formerly called 'holotypeVoucher') is now filled for 5,837 accepted species, with corresponding typeKind categorizations for all those (e.g., holotype, lectotype, neotype, syntype). Hyperlinks to those type specimens are available in typeVoucherURIs for 3,617 species. Links to authority species citations in the authoritySpeciesLink field are now available for 6,072 species. The Tracked Differences file ("Diff_v1.13-v2.0.csv") documents taxonomic changes made since the last MDD version, including 41 during the one month between taxonomic cutoffs. Differences include 6 new species recognized (2 de novo, 4 split), 0 synonymizations (lumps), 0 species with genus or other name changes, and 35 species with common name spelling changes (including 25 to add accent marks). In total, there was a net increase of 6 species and 0 genera of recognized extant or recently extinct mammals since MDD v1.13. Version 1.13 (13 July 2024). This is an incremental release that documents 6,753 total species, of which 113 are recently extinct (addition of 6 species since v1.12) and 6,640 are extant (17 domestic extant, 6,623 wild extant). There are still 27 species flagged for further review. The typeVoucher field (formerly called 'holotypeVoucher') is now filled for an incredible 5,801 accepted species, as compared to 2,727 species previously, thanks to the efforts of the MDD team with expanding the field to non-holotypes. The new field typeKind denotes which kind of type specimen is listed (e.g., holotype, lectotype, neotype, syntype). Also newly expanded is the direct link to authority species citations in the authoritySpeciesLink field — which went from 2,782 in the v1.12 to 6,057 links in the present version! The Tracked Differences file ("Diff_v1.12.1-v1.13.csv") documents taxonomic changes made since the last MDD version, including 85 during the last 6 months (compares to 115 changes from v1.11-v1.12). Differences include 49 new species recognized (24 de novo, 25 split), 12 synonymizations (lumps), 2 species with genus name changes, 2 genus additions (Pudu to Pudella, Petinomys to Olisthomys), 2 species with epithet changes (based on priority/preoccupation), 12 species with epithet spelling changes (based on gender matching), and 2 species of Ctenomys that were removed due to unavailable names (to help flag that available names need to be proposed). In total, there was a net increase of 35 species and 2 genera of recognized extant or recently extinct mammals since MDD v1.12. Version 1.12.1 (30 January 2024). This is minor release that fixes a spelling error in a new species to Euryoryzomys cerqueirai (from E. cerqueriai). This version is also the first to display country-based maps on the per species pages as populated from the 'countryDistribution' field (e.g., see: https://www.mammaldiversity.org/explore.html#genus=Peromyscus&species=maniculatus&id=1002307). Thanks to Jorrit Poelen for some stellar work here! Version 1.12 (5 January 2024). This is an incremental release that documents 6,718 total species, of which 107 are recently extinct (addition of 2 species since v1.11) and 6,611 are extant (17 domestic extant, 6,594 wild extant). There are now 27 species flagged for further review. The holotypeVoucher field is filled for 2,727 accepted species thanks to the efforts of the MDD team (35 NA's indicate a real lack of actual voucher--in need of neotype). The Tracked Differences file ("Diff_v1.11-v1.12.csv") documents taxonomic changes made since the last MDD version, which include 115 changes during the last 8 months (compares to 194 changes from v1.10-v1.11 and 117 changes from v1.9 to v1.10, and ~30 changes between versions before that). Differences include 77 new species recognized (38 de novo, 38 split, 1 revalidation), 8 synonymizations (lumps), 31 species with genus name changes, 7 genus additions (Bisbalus, Passalites, Subulo, Neoeptesicus, Mictomys, Cnephaeus, Cordimus) and 1 genus lump (Nesoromys), and 1 removed domestic species (Homo sapiens, given a revised MDD definition of domestication to be 'domesticated by human artificial selection'; see About page). In total, there was a net increase of 69 species and net increase of 6 genera of recognized extant or recently extinct mammals since MDD v1.11. Version 1.11 (15 April 2023). This is an incremental release that documents 6,649 total species, of which 105 are recently extinct (addition of 4 species since v1.10) and 6,544 are extant (18 domestic extant, 6,526 wild extant). There are now only 21 species flagged for further review. The holotypeVoucher field is filled for 2,731 accepted species thanks to the efforts of the MDD team (NA's indicate a real lack of actual voucher--in need of neotype). The Tracked Differences file ("Diff_v1.10-v1.11.csv") documents taxonomic changes made since the last MDD version, which have been extensive recently due to enhanced activity, leading to a whopping 194 changes during the last 4 months (compares to 117 changes in the last version, and ~30 changes between previous versions). Differences include 64 new species recognized (15 de novo, 49 split), 29 synonymizations (lumps, including 2 domestic species: Bos domesticus into Bos javanicus, and Bos indicus into Bos taurus), 1 species removal (Makalata obscura, now considered nomen dubium), 36 species with genus name changes, 5 genus additions (Otohylomys, Baeodon, Neusticomys, Poecilictis, and Parachoerus) and 7 genus lumps (Crossogale, Aeorestes, Dasypterus, Koopmania, Pediolagus, Petropseudes, Catagonus), 5 species epithet changes to clear up confusion, 47 species epithet spelling changes to match gender or the original description (this was a major emphasis of this version– to come into harmony with batnames.org and hesperomys.com), and 1 error fix in the spelling of the common name "Australian Humpback Dolphin". In total, there was a net increase of 34 species and net decrease of 2 genera of recognized extant or recently extinct mammals since MDD v1.10. Version 1.10 (3 Dec 2022). This is an incremental release that documents 6,615 total species, of which 101 are recently extinct and 6,514 are extant (20 domestic extant, 6,494 wild extant). There are now 33 species flagged for further review (subtraction of Dromiciops mondaca, which was synonymized under D. gliroides). The holotypeVoucher field is now filled for 2,731 accepted species thanks to the continued efforts of Ingrid Rochon, Connor Burgin, and also now Bruce Patterson (NA's indicate a real lack of actual voucher--in need of neotype). The Tracked Differences file ("Diff_v1.9-v1.10.csv") documents taxonomic changes made since the last MDD version, which was 8 months ago (1 April 2022) so 117 changes are included now versus the ~30 changes between previous versions. Differences include 49 new species recognized (22 de novo, 27 split), 30 synonymizations (lumps), 29 species with genus name changes (affecting Lissonycteris -> Myonycteris, Aonyx/Lutrogale -> Lutra, Eothenomys -> Anteliomys, Ellobius -> Bramus, Proedromys -> Mictomicrotus, Lasiopodomys back to Stenocranius, and Cephalophus -> Cephalophorus), 3 species epithet changes to clear up confusion, 5 species epithet spelling changes to match gender or the original description, and 1 error fix shifting Capra hircus to domestic status as the domestic form of C. aegagrus. In total, there was a net increase of 19 species and 5 genera of recognized extant or recently extinct mammals since MDD v1.9. Version 1.9.1 (29 Jun 2022). This is a patch release that adds the field 'holotypeVoucherURIs' to the MDD taxonomy file for use in linking the type specimens to external website(s), including the hosting museum collection. Currently this feature is experimental. The taxonomy still includes 6,596 total species, of which 101 are recently extinct & 6,495 are extant (19 domestic extant, 6,476 wild extant). Version 1.9 (1 Apr 2022). This is an incremental release that documents 6,596 total species, of which 101 are recently extinct and 6,495 are extant (19 domestic extant, 6,476 wild extant). There are now 34 species flagged for further review (addition of 6 species related to the split of Lagenorhynchus dolphins, along with the previous inclusion of some Cebus species). The holotypeVoucher field is now filled for 2,662 accepted species thanks to the continued efforts of Ingrid Rochon and Connor Burgin (NA's indicate a real lack of actual voucher--in need of neotype). The Tracked Differences file ("Diff_v1.8-v1.9.csv") documents taxonomic changes made since the last MDD version, and here includes 15 new species recognized (8 de novo, 7 split), 10 synonymizations (lumps), 2 species with genus name changes (Brachylagus idahoensis to Sylvilagus idahoensis and Nycticebus pygmaeus to Xanthonycticebus pygmaeus), and 1 range extension (for Marmosa alstoni extended to Panama; https://doi.org/10.5281/zenodo.6374907). In total, there was a net increase of 5 recognized species of extant or recently extinct mammals since MDD v1.8. Version 1.8 (1 Feb 2022). This is an incremental release that documents 6,591 total species, of which 101 are recently extinct and 6,490 are extant (19 domestic extant, 6,471 wild extant). There are still 28 species flagged for further review (e.g., some Cebus species). The holotypeVoucher field is now filled for 2,665 accepted species thanks to the continued efforts of Ingrid Rochon and Connor Burgin (NA's indicate a real lack of actual voucher--in need of neotype). The Tracked Differences file ("Diff_v1.7-v1.8.csv") documents taxonomic changes made since the last MDD version, and here includes 27 new species recognized (21 de novo, 6 split), 3 synonymizations, 1 genus change (Nasuella into Nasua, resulting in a reduction in the total number of genera), and 3 species name changes (2 based on new genetic evidence and naming priority, 1 on a spelling change). In total, there was a net increase of 24 recognized species of extant or recently extinct mammals since MDD v1.7. Version 1.7 (6 Nov 2021). This is an incremental release that documents 6,567 total species, of which 101 are recently extinct and 6,466 are extant (19 domestic extant, 6,447 wild extant). There are now 28 species flagged for further review (e.g., some Cebus species). The holotypeVoucher field is now filled for 2,512 accepted species thanks to the continued efforts of Ingrid Rochon and Connor Burgin (including a reduction of NA's from 103 to 26). The Tracked Differences file ("Diff_v1.6-v1.7.csv") documents taxonomic changes made since the last MDD version, and here includes 19 new species recognized (13 de novo, 6 split), 9 synonymizations, 12 genus changes, and 2 de-extinctions due to taxonomic changes (extinct Gazella bilkis synonymized under extant Gazella arabica following Bärmann et al. 2013; extinct Pseudomys gouldii changed to extant since extant Pseudomys fieldi was synonymized under it in the MDD v1.6 following Roycroft et al. 2021). In total, there was a net increase of 10 recognized species of extant or recently extinct mammals since MDD v1.6. Version 1.6 (10 Aug 2021). This is an incremental release that documents 6,557 total species, of which 103 are recently extinct and 6,454 are extant (19 domestic extant, 6,435 wild extant). There are 29 species still flagged for further review (e.g., some Cebus species). The holotypeVoucher field is now filled for 2,548 accepted species thanks to the continued efforts of Ingrid Rochon. The Tracked Differences file ("Diff_v1.5-v1.6.csv") documents taxonomic changes made since the last MDD version, and here includes 9 new species recognized (5 de novo, 4 split), 5 synonymizations, 1 removal (Dryomys yarkandensis invalid while in pre-print), and 18 genus changes. Version 1.5 (11 Jun 2021). This is an incremental release that documents 6,554 total species, of which 103 are recently extinct and 6,451 are extant (19 domestic extant, 6,432 wild extant). There are 29 species still flagged for further review (e.g., some Cebus species). The holotypeVoucher field, which now filled for 2,459 accepted species thanks to the continued efforts of Ingrid Rochon. We also continue to maintain the Tracked Differences file ("Diff_v1.4-v1.5.csv") which documents which taxonomic changes were made per species since the last MDD version. We still plan to retrospectively assemble these diff files for previous versions as well. Version 1.4 (11 Apr 2021). This is an incremental release that documents 6,533 total species, of which 103 are recently extinct, 19 are domestic extant, and 6,411 are wild extant. There are 29 species still flagged for further review (e.g., some Cebus species). Especially improved in this version is the holotypeVoucher field, which now filled for 2,153 accepted species thanks to the heroic efforts of Ingrid Rochon (nearly 1/3 of mammals!!). Additionally, this time we added a Tracked Differences file ("Diff_v1.31-v1.4.csv") which documents which taxonomic changes were made per species since the last MDD version. We plan to retrospectively assemble these diff files for previous versions as well. Note also that the per-species notes (taxonomyNotes) are now updated through all mammals including Chiroptera thanks to the careful efforts of David Huckaby and Connor Burgin. Those notes should help clarify changes since MSW3, which is the well-recognized baseline for mammal taxonomy from which the MDD is updating. Version 1.3.1 (8 Jan 2021). This is an patch release that, like v1.3, documents 6,513 total species, but also (i) fixes some bugs in the type locality listings; and (ii) completes the improved documentation in the per-species notes across all orders including Chiroptera (carefully curated by David Huckaby and Connor Burgin; thanks both!). These completed notes clarify changes since MSW3, which is the well-recognized baseline for mammal taxonomy from which the MDD is updating. Version 1.3 (28 Dec 2020). This is an incremental release that documents 6,513 total species, of which 103 are recently extinct, 19 are domestic extant, and 6,391 are wild extant. There are 29 species still flagged for further review (e.g., some Cebus species). Especially improved in this version are the per-species notes, which have been carefully curated by David Huckaby and Connor Burgin for all mammal orders except Chiroptera (expect those updates in the next version). These notes were written to help clarify changes since MSW3, which is the well-recognized baseline for mammal taxonomy from which the MDD is updating. Version 1.2 (24 Sep 2020). This is a major update, though still incremental toward a more definitive forthcoming release. This release documents 6,485 total species, of which 103 are recently extinct, 19 are domestic extant, and 6,363 are wild extant. Ten species are still "flagged" for further review. This taxonomy and associated data (type locality, authorities, common names) are improved by reference to the Handbook of the Mammals of the World series. Additionally, justifications and citations are now provided for any subjective decisions made, the most substantial of which has been the recommendations of Groves and Grubb (2011)’s compendium Ungulate Taxonomy. That taxonomy of Perissodactyla and non-cetacean Artiodactyla was fully included in the v1.0 release of the MDD (Burgin et al. 2018). However, since Groves and Grubb (2011) was based primarily on qualitative morphological diagnoses with small sample sizes, it has since become controversial in the mammalogical community (e.g., (Holbrook 2013; Gutiérrez and Garbino 2018)). Many specialists have subsequently reverted to the taxonomic arrangement presented by Peter Grubb in MSW3. In current versions of the MDD, we use MSW3 as a baseline for ungulate taxonomy, leaving out all changes made by Groves and Grubb (2011) with the exception of those supported by other published research. Note: this MDD v1.2 taxonomy is also paired with species-level geographic range maps for 6,362 species, available at <a href="https://doi.org/10.5281/zenodo.6644198">https://doi.org/10.5281/zenodo.6644198</a> as mirrored from the data publication of Marsh et al. 2022 (<a href="https://doi.org/10.1111/jbi.14330">https://doi.org/10.1111/jbi.14330</a>). This range map data set differs from the 6,485 total species in MDD v1.2, as follows: <ul> <li>excludes all recently extinct (103) and domestic species (20; correcting for Capra hircus that was coded as 'domestic=0' rather than 'domestic=1' originally);</li> <li>excludes 2 species for which no spatial information was available (Nycticeius aenobarbus and Phoniscus aerosus); and</li> <li>includes 2 species (Elaphurus davidianus and Oryx dammah) that are extinct in the wild (EW) in IUCN, but which have recent range information and were coded in the MDD as extant.</li> </ul> Version 1.1 (29 Mar 2019). This is an incremental release that documents 6,526 total species, of which 100 are recently extinct, 17 are domestic extant, and 6,409 are wild extant.  Of those, 212 species are "flagged" for further review (mostly ungulates from Groves & Grubb, 2011). Version 1.0 (1 Feb 2018; described in <a href="https://doi.org/10.1093/jmammal/gyx147">https://doi.org/10.1093/jmammal/gyx147</a>). We found 6,495 species of currently recognized mammals (96 recently extinct, 6,399 extant), compared to 5,416 in MSW3 (75 extinct, 5,341 extant)—an increase of 1,079 species in about 13 years, including 11 species newly described as having gone extinct in the last 500 years. We tabulate 1,251 new species recognitions, at least 172 unions, and multiple major, higher-level changes, including an additional 88 genera (1,314 now, compared to 1,226 in MSW3) and 14 newly recognized families (167 compared to 153). Analyses of the description of new species through time and across biogeographic regions show a long-term global rate of ~25 species recognized per year, with the Indomalayan biogeographic region as the overall most species-dense for mammals globally (127.1 species/km2), followed by Australasia-Oceania (90.6) and the Neotropics (85.1).   CITATIONS BURGIN, C. J., J. P. COLELLA, P. L. KAHN, AND N. S. UPHAM. 2018. How many species of mammals are there? Journal of Mammalogy 99:1–14. GROVES, C., AND P. GRUBB. 2011. Ungulate Taxonomy. JHU Press. GUTIÉRREZ, E. E., AND G. S. T. GARBINO. 2018. Species delimitation based on diagnosis and monophyly, and its importance for advancing mammalian taxonomy. Zoological Research:97. HOLBROOK, L. T. 2013. Taxonomy Interrupted. Journal of Mammalian Evolution 20:153–154. WILSON, D. E., AND D. M. REEDER. 2005. Mammal species of the world: a taxonomic and geographic reference, 3rd ed. 3rd edition. Johns Hopkins University Press, Baltimore, MD.

opencc-by-4.0Oct 2023View details →

Frontiere della Transizione Energetica. Un database cartografico sui permessi di ricerca per materie prime critiche in Italia.

La principale strategia istituzionale per limitare il riscaldamento globale e realizzare un futuro a bassa intensità di carbonio si risolve, ad oggi, nella transizione a forme di energia "pulite". Le tecnologie di base di questa transizione come batterie ricaricabili, pannelli solari e turbine eoliche sono tuttavia caratterizzate da un'alta intensità minerale, ossia dalla necessità di reperire alcune materie prime in nuove e ben più ingenti quantità rispetto a precedenti cicli di accumulazione. All'interno dell'Eurozona, la sostanziale dipendenza dalle importazioni di CRM ha prodotto un forte stimolo all'esplorazione di risorse minerarie indigene tramite, per esempio, il Raw Materials Act (2023) ed altre iniziative comunitarie. All'interno di questo scenario europeo, già si assiste ad una significativa espansione delle concessioni per permessi di ricerca mineraria in diversi territori della penisola italiana. Al di là dei casi isolati è però complicato tracciare un quadro d'insieme di questa espansione. Almeno due fattori concorrono a rendere difficoltosa questa informazione: da un lato, la scarsa consapevolezza rispetto alla reale intensità minerale della transizione energetica e quindi la sostanziale mancanza di un dibattito tanto pubblico quanto accademico, dall'altro dalla straordinaria frammentazione istituzionale che caratterizza la gestione delle risorse minerarie in Italia, la cui autorizzazione spetta alle Regioni. Questo dataset sopperisce a questa mancanza. Sono qui raccolti e progressivamente aggiornati i dati cartografici relativi ai permessi di ricerca mineraria per materie prime critiche (CRM) ad oggi attivi in Italia, con l'obiettivo di rendere unitari, leggibili e accessibili i dati geografici relativi a queste concessioni. I dati raccolti sono di pubblico dominio e reperiti nelle diverse banche dati regionali. Ad ogni poligono sono associati alcuni indicatori di tipo qualitativo e quantitativo. In conclusione, questo dataset risponde alla necessità di tracciare le dimensioni geografiche di un fenomeno emergente che, data la sua fase iniziale di sviluppo, è ancora poco leggibile dal punto di vista materiale pur promettendo trasformazioni di ampio raggio su ecosistemi e società locali.

18S V9 metabarcoding reference databases and naive-bayes classifier

18S metabarcoding databases and naive-bayes classifiers specific to the V9 region. Built from the <a href="https://pr2-database.org/">PR2 database</a> using Qiime2 (version 2023.2)<a href="https://github.com/BenKaehler/q2-clawback">.</a> Includes a naive-bayes classifier for use with Qiime2. Sequences were dereplicated with Rescript --p-mode 'uniq' , retaining identical sequence records that have differing taxonomies.Primers used:EMP 18S 1391f: GTACACACCGCCCGTCEMP 18S EukBr: TGATCCTTCTGCAGGTTCACCTACStats19,470 unique sequences39,170 total sequences11,748 unique taxa Note: there were 221,085 sequences in the original PR2 database. Many were filtered out due to the in-silico extraction with our V9 primers.<h3>File Descriptions</h3>Files in bold are recommended for taxonomic classification.Create naive-bayes classifier for 18S PR2 database.md:  Markdown with code used to generate databases |pr2_v5.0.0_SSU_18S-V9_uniq-classifier.qza: Unweighted naive-bayes classifier for 18S V9 (primers 1391f, EukBr), extracted from PR2 v5.0.1, dereplicated, generated by qiime2-2023.2 |pr2_version_5.0.0_SSU_18S-V9_uniq_seqs.qza: Sequences for 18S V9 (primers 1391f, EukBr), extracted from PR2 v5.0.1, dereplicated, generated by qiime2-2023.2 |pr2_version_5.0.0_SSU_18S-V9_uniq_tax.qza: Taxa for pr2_version_5.0.0_SSU_18S-V9_uniq_seqs.qza (dereplicated) |pr2_version_5.0.0_SSU_18S-V9_seqs.qza: Sequences for 18S V9 (primers 1391f, EukBr), extracted from PR2 v5.0.1, NOT dereplicated, generated by qiime2-2023.2 |pr2_version_5.0.0_SSU_18S-V9_tax.qza: Taxa for pr2_version_5.0.0_SSU_18S-V9_seqs.qza (NOT dereplicated) pr2_version_5.0.0_SSU_mothur.fasta: SSU sequences downloaded from PR2 v 5.0.1  |pr2_version_5.0.0_SSU_mothur.tax: SSU taxa downloaded from PR2 v5.0.1 |pr2_version_5.0.0_taxonomy.xlsx: Detailed taxonomy downloaded from PR2 v5.0.1 |

Global Violent Deaths (GVD) database 2004-2021, 2023 update, version 1.0

The <a href="https://www.smallarmssurvey.org/database/global-violent-deaths-gvd">Global Violent Deaths (GVD) database</a> integrates indicators on the major causes of lethal interpersonal and communal violence—intentional and unintentional homicides, killings in legal interventions, and direct conflict deaths—and combines them in a single violent deaths indicator. These indicators are also reported in a disaggregated format by the sex of the victim and perpetration mechanism, namely firearm killings. The GVD database tracks this information across 222 countries and territories worldwide yearly from 2004 and reports both crude counts and rates per 100,000 population. The input data is retrieved from reliable sources, such as governments, national and international organizations, trusted non-governmental organizations, and verified media outlets. Missing data points are estimated using the methods described in this document. The GVD database is updated annually by the <a href="https://www.smallarmssurvey.org/">Small Arms Survey</a>, an associated programme of the Geneva Graduate Institute, which strengthens the capacity of governments and practitioners to reduce illicit arms flows and armed violence. This is done through three mutually reinforcing activities: the generation of policy-relevant knowledge, the development of authoritative resources and tools, and the provision of training and other services. The GVD database benefits from financial support from governments and organizations, and notably its core donors, who are publicly disclosed <a href="https://www.smallarmssurvey.org/who-we-are/funding-and-finance">online</a>. The Small Arms Survey follows rigorous procedures to ensure that the input data, the applied methods, and the results are of reasonable quality. If the user encounters apparent errors, they should contact us via email at <a href="mailto:media@smallarmssurvey.org">media@smallarmssurvey.org</a>. Regions, sub-regions, countries, and territories are defined based on the classification system used by the UN Statistical Division (2013 revision), except for Kosovo, England and Wales, Northern Ireland, and Scotland. The names and designations reported in the database do not imply any sort of endorsement by the Small Arms Survey.

GEroNIMO project EP database related to KERs

European Patents dataset performed using <a href="http://www.lens.org">www.lens.org</a> free database for the 7 Key Exploitable Results (KER) identified on the Grant Agreement and selected keywords for GEroNIMO projects. Set up parameters included.

Ascon SCA software and hardware databases

<h2>Software and hardware side-channel analysis databases for attack on Ascon AEAD  </h2>This repository contains datasets collected for side-channel analysis attack on Ascon AEAD.The repository is divided into two folders, one for software side-channel analysis and one for hardware side-channel analysis: - cw.zip    - ascon_collect.ipynb : Jupyter Notebook used to collect the traces for the unprotected Ascon implementation    -  ascon_protected_collect.ipynb : Jupyter Notebook used to collect the traces for the protected Ascon implementation    - simpleserial-ascon : Ascon firmwares used to collect the traces- hw.zip    - ascon_g_protected        - test_ascon.py : Script to test the protected Ascon implementation        - collect_lecroy.py : Script to collect traces for unprotected Ascon implementation with Lecroy oscilloscope        - rtl_src : RTL source files for the protected Ascon implementation    - ascon_g_unprotected        - test_ascon.py : Script to test the unprotected Ascon implementation        - collect_lecroy.py : Script to collect traces for unprotected Ascon implementation with Lecroy oscilloscope        - rtl_src : RTL source files for the unprotected Ascon implementation- helpers.zip    - ASCON.py : Python implementation of Ascon    - SASEBO.py : Helper functions to communicate with the SAKURA-G board    - lecroy3.py : Helper functions for Lecroy oscilloscope    - ascon_helper.py : Helper functions for Ascon    - convert_trs_to_h5.py : Script to convert Trsfile traceset to HDF5 database ascon_cw_protected.h5 : Side-channel database for software protected Ascon implementationascon_cw_unprotected.h5 : Side-channel database for software unprotected Ascon implementationascon_hw_protected.h5 : Side-channel database for hardware protected Ascon implementationascon_hw_unprotected.h5 : Side-channel database for hardware unprotected Ascon implementation ascon_cw_protected.trs : Traces for software protected Ascon implementationascon_cw_unprotected.trs : Traces for software unprotected Ascon implementationascon_hw_protected.trs : Traces for hardware protected Ascon implementationascon_hw_unprotected.trs : Traces for hardware unprotected Ascon implementation <h3>Ascon authenticated encryption attack on a Chipwhisperer STM32F4 </h3>The dataset was used for side-channel attack on Ascon initialization phase attack of the authenticated encryption mode on a ChipWhisperer STM32F4 target board.The power traces are collected with the ChipWhisperer-Lite oscilloscope at a sampling rate of 4x the target clock frequency, and captures the first call of the round function of the Chi function of Ascon permutation.The code used to collect the traces is also available in this repository, and the trace collection can be replicated with a ChipWhisperer-Lite and a STM32F4 target board. <h3>Ascon authenticated encryption attack on a SAKURA-G FPGA</h3>The hardware designs of the unprotected and protected Ascon implementations are available in the `hw` folder.Both implementations are written in VHDL/Verilog and can be synthesized for Spartan6 (XC6SLX75) with Xilinx ISE.Traces are collected with a Lecroy WaveRunner 610Zi oscilloscope at a sampling rate of 500 MS/s. <h3>Databases description:</h3>Database                                 | Ntraces                  | Traces (samples) | Label* (bytes)  | Metadata (bytes)                                                 | Nf          | Nr           |                              |                         | Key | Nonce | Plaintext | Associated data | Ciphertext | Tagascon_cw_unprotected.h5      | 100,000 | 100,000  | 772                       | 64                    | 16   | 16       | 4             | 4                        | 4               | 16ascon_cw_protected.h5          | 500,000 | 500,000  | 1408                     | 64                    | 32   | 32       | 16           | 16                      | 16             | 32ascon_hw_unprotected.h5      | 100,000 | 100,000  | 6,000                    | 64                    | 16   | 16       | 4             | 4                        | 4               | 16ascon_hw_protected.h5          | 500,000 | 500,000  | 10,000                  | 64                    | 32   | 32       | 8             | 8                        | 8               | 32 *Label computed with the intermediate_value leakage model described in `ascon_helper.py`

Fault Analysis Database with Features (FADbF)

This repository is also available in GitHub: <a href="https://github.com/leandroensina/FADbF">https://github.com/leandroensina/FADbF</a>The FADbF dataset companions the paper entitled "Fault Distance Estimation for Transmission Lines with Dynamic Regressor Selection", published in Neural Computing and Applications, doi: <a href="https://doi.org/10.1007/s00521-023-09155-y">10.1007/s00521-023-09155-y</a>. More information about the dataset can be found in this reference.Associated Tasks: classification and regressionInstances: 168,000Attributes: 128, including the two possible targetsAdditional Information: this database comprises several attributes extracted from time series of fault simulations of a transmission line with 500 kV, 414 km, and 60 Hz. In total, we extracted 21 features separately for each of the three phases for both voltage and current waveforms along two post-fault cycles from a single terminal, resulting in 126 attributes (21 * 3 * 2 = 126) in addition to the two possible targets, i.e., fault type (classification task) and fault location (regression task). If desired, the fault type can also be used as a feature for the fault location task.

Maize Phosphorus Leaf Deficiency (MPLD) Database | Compact Scientific Camera (original-processed)

This database presents samples of maize leaves placed on a withe background, representing three levels of phosphorus deficiency: complete absence of the nutrient (labeled -P), half dose of the required phosphorus for normal plant development (-P50), and complete supply (C).Its composed of two folders:<ul><li>Original_dataset: 722 jpg images of 1280 x 1020 pixels size divided into '_C', '-P' and '-P50' folders for class labels.</li><li>Processed_dataset: 2433 png images of 224 x 224 pixels size divided into '-C', '-P' and '-P50' folders for class labels.</li></ul>

Space Weather ElectroMagnetic Database for Ireland (SWEMDI)

This is a database containing electromagnetic (EM) data that can contribute to better understand and quantify the electric fields caused by space weather events at the Earth's surface, and the physical properties of Ireland’s lithosphere. The database is named Space Weather Electromagnetic Database for Ireland (SWEMDI). It contains measured electromagnetic time series using magnetotelluric equipment, electromagnetic tensor relationships, 3D electrical resistivity model of Ireland's lithosphere, modelled electric and magnetic time series for Ireland between 1991 and 2018, documents and publications that used parts of this database, and a series of scripts that were used to generate the database.