100+ datasets found
  1. o

    NOW — New and Old Worlds: Database of fossil mammals

    • explore.openaire.eu
    Updated Nov 11, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    The NOW Community (2020). NOW — New and Old Worlds: Database of fossil mammals [Dataset]. http://doi.org/10.5281/zenodo.4268068
    Explore at:
    Dataset updated
    Nov 11, 2020
    Authors
    The NOW Community
    Description

    Overview NOW is a global database of fossil mammal occurrences, currently containing around 70, 000 locality-species entries. The database spans the last 66 million years, with the primary focus on the last 23 million years. Whereas the database contains a record on all continents, the main focus and coverage of the database historically have been on Eurasia. The database covers a large part of the mammalian fossil record known to research, focusing on classical and actively researched fossil localities. It is run by a management team in collaboration with an international advisory board of experts. Rather than a static archive, the database emphasizes the continuous integration of new knowledge of the community, continuous data curation, and consistency of scientific interpretations. The database records species occurrence at localities worldwide, as well as ecological characteristics of fossil species, geological contexts of localities and more. The database is primarily used for two purposes: for queries about other occurrences of particular taxa, their properties and the properties of localities in the spirit of an encyclopedia; and for large scale research and quantitative analyses of evolutionary processes, patterns, reconstructing past environments, as well as interpreting evolutionary contexts. Accessing the data The NOW data are fully open, requiring no logging in nor a community membership is necessary for using the data for any purpose. Now data can be accessed from www.nowdatabase.org/now/database/. The most updated data can be downloaded directly from the NOW user interface. In addition, archived versions are available. Citation Minimum required attribution Data (https://nowdatabase.org/now/database/) by The NOW Community / CC BY 4.0. http://doi.org/10.5281/zenodo.4268068 Suggested citation or attribution The NOW Community [year]. New and Old Worlds Database of Fossil Mammals (NOW). Licensed under CC BY 4.0. Retrieved [download date] from https://nowdatabase.org/now/database/. http://doi.org/10.5281/zenodo.4268068

  2. S

    Paleogene Central Asian Mammal Occurrence and Body Size Data

    • dataportal.senckenberg.de
    Updated Apr 11, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Fritz (2024). Paleogene Central Asian Mammal Occurrence and Body Size Data [Dataset]. https://dataportal.senckenberg.de/dataset/paleogene-central-asian-mammal-occurrence-and-body-size-data
    Explore at:
    Dataset updated
    Apr 11, 2024
    Dataset provided by
    SBiK-F - Geobiodiversity Research
    Authors
    Fritz
    Area covered
    Central Asia
    Description

    Occurrence dataset: A relatively large (~1500) dataset of fossil mammal occurrence data for the Paleocene, Eocene and Oligocene (66 Ma - 23 Ma) of Mongolia and Northern China above 30 degrees North. Occurrence data comprises species or genus name, specimen information where possible, geological unit specimen was found in, age (range) of specimen and/or geological unit and any other relevant information. Data taken from multiple sources. The majority comes from the Palaeobiology Database (PBDB), an open-access community dataset of global fossil occurrences (and some trait data) for all time periods and taxonomic groups. Our dataset used only the mammal records from our study region and time period. A very small amount of data (10's of occurrences) was taken from the NOW (New and Old Worlds) Database of fossil mammals (NOW database), another open-access community dataset. This database contains only mammal occurrence and trait data for fossil mammals throughout geological history and across the world. Additional occurrence data (~100) was collected first hand from the literature by Dr Gemma Benevento.

    Body Size dataset: Lower first molar (m1) length and width (which can be used to estimate mammal body size) was collected for approximately 60% of the individual species in the occurrence dataset (~430 species).

  3. d

    Now & Then: Modern and Historical Images of Philadelphia

    • catalog.data.gov
    • gimi9.com
    • +1more
    Updated Mar 31, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Skookul.com (2025). Now & Then: Modern and Historical Images of Philadelphia [Dataset]. https://catalog.data.gov/dataset/now-then-modern-and-historical-images-of-philadelphia
    Explore at:
    Dataset updated
    Mar 31, 2025
    Dataset provided by
    Skookul.com
    Area covered
    Philadelphia
    Description

    Now & Then provides access to historic and contemporary photographs of Philadelphia. When accessed via a location-aware web browser, the app loads photographs taken near the user's location. Historic photographs are from the PhillyHistory.org database. Contemporary photographs are from Panaramio.com.

  4. InvaCost: Economic cost estimates associated with biological invasions...

    • figshare.com
    xlsx
    Updated May 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Christophe DIAGNE; Boris Leroy; Rodolphe E. Gozlan; Anne-Charlotte Vaissière; Claire Assailly; Lise Nuninger; David Roiz; Frédéric Jourdain; Ivan Jaric; Franck Courchamp; Elena Angulo; Liliana Ballesteros-Mejia (2023). InvaCost: Economic cost estimates associated with biological invasions worldwide. [Dataset]. http://doi.org/10.6084/m9.figshare.12668570.v5
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Christophe DIAGNE; Boris Leroy; Rodolphe E. Gozlan; Anne-Charlotte Vaissière; Claire Assailly; Lise Nuninger; David Roiz; Frédéric Jourdain; Ivan Jaric; Franck Courchamp; Elena Angulo; Liliana Ballesteros-Mejia
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    InvaCost is the most up-to-date, comprehensive, standardized and robust data compilation and description of economic cost estimates associated with invasive species worldwide1. InvaCost has been constructed to provide a contemporary and freely available repository of monetary impacts that can be relevant for both research and evidence-based policy making. The ongoing work made by the InvaCost consortium2,3,4 leads to constantly improving the structure and content of the database (see sections below). The list of actual contributors to this data resource now largely exceeds the list of authors listed in this page. All details regarding the previous versions of InvaCost can be found by switching from one version to another using the “version” button above. IMPORTANT UPDATES: 1. All information, files, outcomes, updates and resources related to the InvaCost project are now available on a new website: http://invacost.fr/2. The names of the following columns have been changed between the previous and the current version: ‘Raw_cost_estimate_local_currency’ is now named ‘Raw_cost_estimate_original_currency’; ‘Min_Raw_cost_estimate_local_currency’ is now named ‘Min_Raw_cost_estimate_original_currency’; ‘Max_Raw_cost_estimate_local_currency’ is now named ‘Max_Raw_cost_estimate_original_currency’; ‘Cost_estimate_per_year_local_currency’ is now named ‘Cost_estimate_per_year_original_currency’3. The Frequently Asked Questions (FAQ) about the database and how to (1) understand it, (2) analyse it and (3) add new data are available at: https://farewe.github.io/invacost_FAQ/. There are over 60 questions (and responses), so there’s probably yours.4. Accordingly with the continuous development and updates of the database, a ‘living figure’ is now available online to display the evolving relative contributions of different taxonomic groups and regions to the overall cost estimates as the database is updated: https://borisleroy.com/invacost/invacost_livingfigure.html5. We have now added a new column called ‘InvaCost_ID’, which is now used to identify each cost entry in the current and future public versions of the database. As this new column only affects the identification of the cost entries and not their categorisation, this is not considered as a change of the structure of the whole database. Therefore, the first level of the version numbering remains ‘4’ (see VERSION NUMBERING section).

    CONTENT: This page contains four files: (1) 'InvaCost_database_v4.1' which contains 13,553 cost entries depicted by 66 descriptive columns; (2) ‘Descriptors 4.1’ provides full definition and details about the descriptive columns used in the database; (3) ‘Update_Invacost_4.1’ has details about the all the changes made between previous and current versions of InvaCost; (4) ‘InvaCost_template_4.1’ (downloadable file) provides an easier way of entering data in the spreadsheet, standardizing all the terms used on it as much as possible to avoid mistakes and saving time at post-refining stages (this file should be used by any external contributor to propose new cost data).

    METHODOLOGY: All the methodological details and tools used to build and populate this database are available in Diagne et al. 20201 and Angulo et al. 20215. Note that several papers used different approaches to investigate and analyse the database, and they are all available on our website http://invacost.fr/.

    VERSION NUMBERING: InvaCost is regularly updated with contributions from both authors and future users in order to improve it both quantitatively (by new cost information) and qualitatively (if errors are identified). Any reader or user can propose to update InvaCost by filling the ‘InvaCost_updates_template’ file with new entries or corrections, and sending it to our email address (updates@invacost.fr). Each updated public version of InvaCost is stored in this figShare repository, with a unique version number. For this purpose, we consider the original version of InvaCost publicly released in September 2020 as ‘InvaCost_1.0’. The further updated versions are named using the subsequent numbering (e.g., ‘InvaCost_2.0’, InvaCost_2.1’) and all information on changes made are provided in a dedicated file called ‘Updates-InvaCost’ (named using the same numbering, e.g., ‘Updates-InvaCost_2.0’, ‘Updates-InvaCost_2.1’). We consider changing the first level of this numbering (e.g. ‘InvaCost_3.x’ ‘InvaCost_4.x’) only when the structure of the database changes. Every user wanting to have the most up-to-date version of the database should refer to the latest released version.

    RECOMMENDATIONS: Every user should read the ‘Usage notes’ section of Diagne et al. 20201 before considering the database for analysis purposes or specific interpretation. InvaCost compiles cost data published in the literature, but does not aim to provide a ready-to-use dataset for specific analyses. While the cost data are described in a homogenized way in InvaCost, the intrinsic disparity, complexity, and heterogeneity of the cost data require specific data processing depending on the user objectives (see our FAQ). However, we provide necessary information and caveats about recorded costs, and we have now an open-source software designed to query and analyse this database6.

    CAUTION: InvaCost is currently being analysed by a network of international collaborators in the frame of the InvaCost project2,3,4 (see https://invacost.fr/en/outcomes/). Interested users may contact the InvaCost team if they wish to learn more about or contribute to these current efforts. Users are in no way prevented from performing their own independent analyses and collaboration with this network is not required. Nonetheless, users and contributors are encouraged to contact the InvaCost team before using the database, as the information contained may not be directly implementable for specific analyses.

    RELATED LINKS AND PUBLICATIONS:

    1 Diagne, C., Leroy, B., Gozlan, R.E. et al. InvaCost, a public database of the economic costs of biological invasions worldwide. Sci Data 7, 277 (2020). https://doi.org/10.1038/s41597-020-00586-z

    2 Diagne C, Catford JA, Essl F, Nuñez MA, Courchamp F (2020) What are the economic costs of biological invasions? A complex topic requiring international and interdisciplinary expertise. NeoBiota 63: 25–37. https://doi.org/10.3897/neobiota.63.55260

    3 Researchgate page: https://www.researchgate.net/project/InvaCost-assessing-the-economic-costs-of-biological-invasions

    4 InvaCost workshop: https://www.biodiversitydynamics.fr/invacost-workshop/

    5 Angulo E, Diagne C, Ballesteros-Mejia L. et al. (2021) Non-English languages enrich scientific knowledge: the example of economic costs of biological invasions. Science of the Total Environment 775:144441. https://doi.org/10.1016/j.scitotenv.2020.144441

    6Leroy B, Kramer A M, Vaissière A-C, Courchamp F and Diagne C (2020) Analysing global economic costs of invasive alien species with the invacost R package. BioRXiv. doi: https://doi.org/10.1101/2020.12.10.419432

  5. GSDR - WeGov Now - Data

    • data.niaid.nih.gov
    Updated Jan 24, 2020
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    OpenStreetMap (2020). GSDR - WeGov Now - Data [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_2454149
    Explore at:
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    OpenStreetMap//www.openstreetmap.org/
    Alexey Noskov
    WeGovNowConsortium
    License

    Open Data Commons Attribution License (ODC-By) v1.0https://www.opendatacommons.org/licenses/by/1.0/
    License information was derived automatically

    Description

    A collection of data files for the WeGovNow project. It contains the source data provided by stake holders, OpenStreetMap data (under the OSM data license) and data generated by the IGIS.TK applications

  6. d

    DOB NOW: Electrical Permit Details

    • catalog.data.gov
    • data.cityofnewyork.us
    • +1more
    Updated Jul 26, 2025
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    data.cityofnewyork.us (2025). DOB NOW: Electrical Permit Details [Dataset]. https://catalog.data.gov/dataset/dob-now-electrical-permit-details
    Explore at:
    Dataset updated
    Jul 26, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    This dataset is part of the DOB NOW Electrical Permit Data Collection: https://data.cityofnewyork.us/browse?Data-Collection_Data-Collection=DOB+NOW+Electrical+Permits+Data This dataset contains details of the electrical scope of work. For each Job Filing Number, there can be multiple rows/records in this dataset. For example, there might be electrical work being performed in the basement as well as on the 4th floor. One row/record for Basement and one for the floor. The job might have some 101 to 200 amps Service Switches as well as some Up to 100 amps Service Switches, and there would be one row/record for each.

  7. n

    FH HUS Mutation Database

    • neuinfo.org
    • rrid.site
    • +2more
    Updated Jun 27, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2024). FH HUS Mutation Database [Dataset]. http://identifiers.org/RRID:SCR_008512
    Explore at:
    Dataset updated
    Jun 27, 2024
    Description

    The database has now been updated to include ALL mutations found in HUS patients, including those in Factor I(FI) and Membrane (MCP). Homology models are available for the domains of FI and MCP and all analysis previously available for Factor H (FH) are now also available for FI and MCP. All SNP records for FH, FI and MCP are also now included in the database on the SNP pages. Only those SNPs within coding regions will be included in the full list of mutations and within the advanced search. For more information on the different versions of the database click here. We have also redesigned the site in order to display information more clearly. Please let us know what you think of the new design. Home Information Mutations Models References Links Submit Contact Us Help Collaborators NEWS !! SEP 2009 The database has now been recovered. Please report any bugs that you notice. NEWS !! MAY 2009 We have suffered from a complete server failure this month but these issues have been sorted out and work is being carried out to restore all the data within our FH-HUS database. Sorry for any inconvenience this may have caused. NEWS !! JAN 2007 Mutations within complement Factor B have also been associated with aHUS. (Goicoechea de Jorge et al., 2007) NEW !! Nov 2006 FH-HUS Database Version 2.1 The database has now been updated to include ALL mutations found in HUS patients, including those in Factor I(FI) and Membrane (MCP). Homology models are available for the domains of FI and MCP and all analysis previously available for Factor H (FH) are now also available for FI and MCP. All SNP records for FH, FI and MCP are also now included in the database on the SNP pages. Only those SNPs within coding regions will be included in the full list of mutations and within the advanced search. For more information on the different versions of the database click here. We have also redesigned the site in order to display information more clearly. Please let us know what you think of the new design. Quick Search Enter Codon No : Choose Protein : Advanced Search Have you or someone you know been diagnosed with aHUS? The information contained on this web site is provided for scientific research purposes only. We do not give medical advice or recommend any particular treatment for specific individuals. Here are several links for patient information on aHUS: http://renux.dmed.ed.ac.uk/ http://en.wikipedia.org/ http://kidney.niddk.nih.gov http://www.webmd.com HUS HUS (Haemolytic Uraemic Syndrome) is a disease associated with microangiopathic haemolytic anemia, thrombocytopenia and acute renal failure. A subgroup of the syndrome is strongly associated with abnormalities within the complement regulator factor H gene. To read information on HUS click here. To read information on Factor H (FH) click here. FH Mutations There are currently 74 Factor H mutations, 10 Factor I mutations and 25 MCP mutations linked with HUS patients within this database. There are also 5 mutations within FH that are associated with MPGN patients. . Following HGVS guidelines, mutations are numbered starting from the ATG initiation codon and include the 18-residue signal peptide. The number of the codon with respect to the mature FH protein and consistent with the RSCB PDB entry for secreted FH (1haq.pdb) is shown alongside in parenthesis. Type I and Type II Phenotype Type I indicates that the mutant protein is either absent from the plasma or present in lower amounts. This indicates the mutation has a structural effect on the mutant protein - ie reducing the stability Type II indicates that the mutant protein is present in normal amounts in plasma. This indicates that the mutation has a functional effect on the protein ie affecting substrate binding References There are three references you can use to reference this database Saunders et al, 2007. The interactive Factor H-atypical hemolytic uremic syndrome mutation database and website: update and integration of membrane cofactor protein and Factor I mutations with structural models. Hum Mutat. 2007 28:222-234. Saunders et al, 2006. An interactive web database of factor H-associated hemolytic uremic syndrome mutations: insights into the structural consequences of disease-associated mutations. Hum Mutat. 2006 27:21-30. Saunders & Perkins, 2006. A user''s guide to the interactive Web database of factor H-associated hemolytic uremic syndrome. Semin Thromb Hemost. 2006 32:160-8. Abstract. BACKGROUND: cblC disease is a cause of hemolytic uremic syndrome (HUS), which has been primarily described in neonates and infants with severe renal and neurological lesions. PATIENTS: Two sisters aged 6 and 8.5 years presented with a latent hemolytic process characterized by undetectable or low plasma haptoglobin, respectively, associated with renal failure and gross proteinuria. Renal biopsies performed in both patients found typical findings of thrombotic microangiopathy suggesting the diagnosis of HUS. Both patients were free of neurologic signs. RESULTS: Biochemical investigations found a cobalamin processing deficiency of the cblC type. Search for additional factors susceptible to worsen endothelial damage revealed homozygosity 677C--> T mutation in the methylenetetrahydrofolate reductase gene as well as heterozygosity for a 3254T--> C mutation in factor H in the patient with the most severe clinical presentation. Long-term subcutaneous administration of hydroxocobalamin in combination with oral betaine and folic acid resulted in clinical and biological improvement in both patients. CONCLUSION: cblC disease may be a cause of chronic HUS with delayed onset in childhood. Superimposed mutation of factor H gene might influence clinical severity.

  8. Z

    Mammal Diversity Database

    • data.niaid.nih.gov
    • zenodo.org
    Updated Apr 6, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Mammal Diversity Database (2025). Mammal Diversity Database [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_4139722
    Explore at:
    Dataset updated
    Apr 6, 2025
    Dataset authored and provided by
    Mammal Diversity Database
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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: https://mammaldiversity.org. 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 American Society of Mammalogists (ASM; 2017-present), with logistical and planning support provided related grants at different time points (2025-present: NIH R35 to Upham; 2021-2023: NIH R21 to Upham, Reeder, Sterner, Sen; 2017-2019: NSF Vertlife Terrestrial grant). The ASM Biodiversity Committee 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 MDD About page 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 IUCN SSC Bat Specialist Group 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 2.1 (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:

    Codings of US state, country, continent, and biogeographic realm geographic categories for each species (fields of subregionDistribution, countryDistribution, continentDistribution, biogeographicRealm, respectively);

    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

    Integration between the MDD and the databases Hesperomys and Batnames for greater data accuracy and completeness.

    Updated data presentations by MDD student programmer Heru Handika:

    Improved website at https://www.mammaldiversity.org/ that is fully re-written, including a migration from Jekyll (https://jekyllrb.com/) to the Astro web-framework (https://astro.build/) with TypeScript (https://www.typescriptlang.org/), and Tailwind CSS (https://tailwindcss.com/) integration

    New MDD app wrote using the Flutter framework (https://flutter.dev/) and the Rust programming language (https://www.rust-lang.org/). It supports iOS, iPadOS, Android, Windows, Linux, and macOS. Details on installing the app are available at https://github.com/mammaldiversity/mdd_app.

    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

  9. d

    WA Now Index (LGATE-361) - Datasets - data.wa.gov.au

    • catalogue.data.wa.gov.au
    Updated Sep 28, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2022). WA Now Index (LGATE-361) - Datasets - data.wa.gov.au [Dataset]. https://catalogue.data.wa.gov.au/dataset/wa-now-index-lgate-361
    Explore at:
    Dataset updated
    Sep 28, 2022
    Area covered
    Western Australia
    Description

    The WA Now mosaic is comprised of approximately 1,200 individual mosaics, derived from imagery captured over 20 years plus and captured at various resolutions. To assist in the identifying the name, capture date and resolution of the individual mosaics in WA Now Mosaic (LGATE-320) (https://catalogue.data.wa.gov.au/dataset/wa-now-aerial-photography-mosaic), an index (in a variety of formats) has been made available for use by everyone.

  10. S

    Quaternary European Mammal Occurrence and Trait Data

    • dataportal.senckenberg.de
    Updated Apr 11, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Fritz (2024). Quaternary European Mammal Occurrence and Trait Data [Dataset]. https://dataportal.senckenberg.de/dataset/quaternary-european-mammal-occurrence-and-trait-data
    Explore at:
    Dataset updated
    Apr 11, 2024
    Dataset provided by
    SBiK-F - Geobiodiversity Research
    Authors
    Fritz
    Description

    Occurrence dataset: A large dataset of fossil mammal occurrence data for the Quaternary (Pleistocene and Holocene) of Europe. Occurrence data comprises species or genus name, specimen information where possible, geological unit specimen was found in, age (range) of specimen and/or geological unit and any other relevant information. Data taken from multiple sources, including the Palaeobiology Database (PBDB), an open-access community dataset of global fossil occurrences (and some trait data) for all time periods and taxonomic groups. Our dataset used only the mammal records from our study region and time period. Data was taken from the NOW (New and Old Worlds) Database of fossil mammals (NOW database), another open-access community dataset. This database contains only mammal occurrence and trait data for fossil mammals throughout geological history and across the world. All additional occurrence data was collected first hand from the literature.

    Trait dataset: Trait data for species in the occurrence dataset. Including (but not limited to) body size data, collected as lower first molar length and width).

  11. s

    Data from: Kabat Database of Sequences of Proteins of Immunological Interest...

    • scicrunch.org
    • rrid.site
    • +3more
    Updated Jul 12, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2025). Kabat Database of Sequences of Proteins of Immunological Interest [Dataset]. http://identifiers.org/RRID:SCR_006465
    Explore at:
    Dataset updated
    Jul 12, 2025
    Description

    The Kabat Database determines the combining site of antibodies based on the available amino acid sequences. The precise delineation of complementarity determining regions (CDR) of both light and heavy chains provides the first example of how properly aligned sequences can be used to derive structural and functional information of biological macromolecules. The Kabat database now includes nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules, and other proteins of immunological interest. The Kabat Database searching and analysis tools package is an ASP.NET web-based portal containing lookup tools, sequence matching tools, alignment tools, length distribution tools, positional correlation tools and much more. The searching and analysis tools are custom made for the aligned data sets contained in both the SQL Server and ASCII text flat file formats. The searching and analysis tools may be run on a single PC workstation or in a distributed environment. The analysis tools are written in ASP.NET and C# and are available in Visual Studio .NET 2003/2005/2008 formats. The Kabat Database was initially started in 1970 to determine the combining site of antibodies based on the available amino acid sequences at that time. Bence Jones proteins, mostly from human, were aligned, using the now-known Kabat numbering system, and a quantitative measure, variability, was calculated for every position. Three peaks, at positions 24-34, 50-56 and 89-97, were identified and proposed to form the complementarity determining regions (CDR) of light chains. Subsequently, antibody heavy chain amino acid sequences were also aligned using a different numbering system, since the locations of their CDRs (31-35B, 50-65 and 95-102) are different from those of the light chains. CDRL1 starts right after the first invariant Cys 23 of light chains, while CDRH1 is eight amino acid residues away from the first invariant Cys 22 of heavy chains. During the past 30 years, the Kabat database has grown to include nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules and other proteins of immunological interest. It has been used extensively by immunologists to derive useful structural and functional information from the primary sequences of these proteins.

  12. Amount of data created, consumed, and stored 2010-2023, with forecasts to...

    • statista.com
    Updated Jun 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2025). Amount of data created, consumed, and stored 2010-2023, with forecasts to 2028 [Dataset]. https://www.statista.com/statistics/871513/worldwide-data-created/
    Explore at:
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2024
    Area covered
    Worldwide
    Description

    The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

  13. d

    Data from: 2023 National Offshore Wind data set (NOW-23)

    • catalog.data.gov
    • data.openei.org
    • +2more
    Updated Feb 25, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Renewable Energy Laboratory (2025). 2023 National Offshore Wind data set (NOW-23) [Dataset]. https://catalog.data.gov/dataset/us-offshore-wind-resource-data-for-2000-2019
    Explore at:
    Dataset updated
    Feb 25, 2025
    Dataset provided by
    National Renewable Energy Laboratory
    Description

    The 2023 National Offshore Wind data set (NOW-23) is the latest wind resource data set for offshore regions in the United States, which supersedes, for its offshore component, the Wind Integration National Dataset (WIND) Toolkit, which was published about a decade ago and is currently one of the primary resources for stakeholders conducting wind resource assessments in the continental United States. The NOW-23 data set was produced using the Weather Research and Forecasting Model (WRF) version 4.2.1. A regional approach was used: for each offshore region, the WRF setup was selected based on validation against available observations. The WRF model was initialized with the European Centre for Medium Range Weather Forecasts 5 Reanalysis (ERA-5) data set, using a 6-hour refresh rate. The model is configured with an initial horizontal grid spacing of 6 km and an internal nested domain that refined the spatial resolution to 2 km. The model is run with 61 vertical levels, with 12 levels in the lower 300m of the atmosphere, stretching from 5 m to 45 m in height. The MYNN planetary boundary layer and surface layer schemes were used the North Atlantic, Mid Atlantic, Great Lakes, Hawaii, and North Pacific regions. On the other hand, using the YSU planetary boundary layer and MM5 surface layer schemes resulted in a better skill in the South Atlantic, Gulf of Mexico, and South Pacific regions. A more detailed description of the WRF model setup can be found in the WRF namelist files linked at the bottom of this page. For all regions, the NOW-23 data set coverage starts on January 1, 2000. For Hawaii and the North Pacific regions, NOW-23 goes until December 31, 2019. For the South Pacific region, the model goes until 31 December, 2022. For all other regions, the model covers until December 31, 2020. Outputs are available at 5 minute resolution, and for all regions we have also included output files at hourly resolution. The NOW-23 data are provided here as HDF5 files. Examples of how to use the HSDS Service to Access the NOW-23 files are linked below. A list of the variables included in the NOW-23 files is also linked below. No filters have been applied to the raw WRF output.

  14. Database Management System Market Research Report 2033

    • growthmarketreports.com
    csv, pdf, pptx
    Updated Jun 30, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Growth Market Reports (2025). Database Management System Market Research Report 2033 [Dataset]. https://growthmarketreports.com/report/database-management-system-market-global-industry-analysis
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jun 30, 2025
    Dataset authored and provided by
    Growth Market Reports
    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Database Management System Market Outlook




    According to our latest research, the global Database Management System (DBMS) market size reached USD 79.3 billion in 2024, demonstrating robust expansion with a CAGR of 13.2% from 2025 to 2033, and is forecasted to attain USD 236.8 billion by 2033. The market’s rapid growth is primarily driven by the exponential increase in data generation across industries, the rising adoption of cloud-based solutions, and the growing need for real-time data analytics and security. As organizations increasingly recognize the strategic value of data, DBMS solutions are becoming indispensable for efficient data storage, access, and management.




    A major growth factor propelling the Database Management System market is the surge in digital transformation initiatives across both public and private sectors. Industries such as BFSI, healthcare, retail, and manufacturing are generating vast volumes of structured and unstructured data, necessitating sophisticated DBMS platforms for effective data handling. The proliferation of IoT devices, social media, and e-commerce platforms has further amplified the need for scalable and secure database solutions that can process diverse data types in real time. Additionally, the integration of artificial intelligence and machine learning with DBMS is enabling organizations to derive actionable insights, automate routine processes, and improve decision-making, thereby fueling market demand.




    Another key driver is the shift towards cloud-based database management systems, which offer unparalleled flexibility, scalability, and cost efficiency compared to traditional on-premises solutions. Cloud DBMS platforms are particularly attractive to small and medium enterprises (SMEs) that lack the resources for extensive IT infrastructure investments, allowing them to leverage enterprise-grade data management capabilities on a subscription basis. Furthermore, with the advent of hybrid and multi-cloud environments, organizations can now optimize their data architecture for performance, redundancy, and compliance, further accelerating the adoption of cloud DBMS solutions globally.




    Regulatory compliance and data security concerns are also catalyzing the growth of the Database Management System market. Governments and industry bodies worldwide are introducing stringent regulations around data privacy, storage, and access, compelling organizations to upgrade their database infrastructure. Advanced DBMS solutions now incorporate robust encryption, granular access controls, and automated compliance monitoring, ensuring that sensitive data is protected and regulatory obligations are met. This heightened focus on data governance is prompting enterprises to invest in next-generation DBMS technologies, thereby expanding the market’s growth trajectory.




    Regionally, North America continues to dominate the Database Management System market owing to its advanced IT infrastructure, strong presence of leading market players, and early adoption of emerging technologies. Europe follows closely, driven by stringent data protection regulations and increasing digitalization across industries. The Asia Pacific region is witnessing the fastest growth, fueled by rapid urbanization, burgeoning IT and telecom sectors, and a rising number of SMEs embracing cloud-based solutions. Latin America and the Middle East & Africa are also experiencing steady growth, supported by expanding internet penetration and government-led digital initiatives. This regional diversity ensures that the DBMS market remains dynamic and resilient to global economic fluctuations.





    Component Analysis




    The Database Management System market is distinctly segmented by component into software and services, each playing a critical role in the overall ecosystem. The software segment, which encompasses both relational and non-relational DBMS platforms, forms the backbone of the market and accounts for the majority of revenue share. This dominance is attributed to the conti

  15. Pacific Northwest Salmon Habitat Project Database

    • data.wu.ac.at
    html
    Updated Feb 8, 2018
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    National Oceanic and Atmospheric Administration, Department of Commerce (2018). Pacific Northwest Salmon Habitat Project Database [Dataset]. https://data.wu.ac.at/schema/data_gov/ZDA5M2UyZjAtNmM4Yy00YWUzLWI4YjQtNDUzYTFmNjdjOTNk
    Explore at:
    htmlAvailable download formats
    Dataset updated
    Feb 8, 2018
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Area covered
    551366337fe1d6ddd7a46ba8428022cc945c374e
    Description

    In the Pacific Northwest Salmon Habitat Project Database Across the Pacific Northwest, both public and private agents are working to improve riverine habitat for a variety of reasons, including improving conditions for threatened and endangered salmon. These projects are moving forward with little or no knowledge of specific linkages between restoration actions and the responses of target species. Targeted effectiveness monitoring of these actions is required to redress this lack of mechanistic understanding, but such monitoring is, in turn, dependent on detailed restoration information (i.e. implementation monitoring). We created a standardized data dictionary of project types now being applied throughout the region (now RPA 73 in the FCRPS Biop) to assemble a standardized database of restoration projects. The database was designed specifically to address the needs of regional monitoring programs that evaluate the effectiveness of restoration actions.

    The database currently (2010) contains spatially referenced, project-level data on over 35,000 restoration actions initiated at over 56,000 locations in the last 15 years (98% of projects report start or end dates in the last 15 years) in the states of Washington, Oregon, Idaho and Montana, USA. 60 percent of projects report cost. Total cost for projects in the database with cost information is over 2 BILLION dollars. Data sources include federal, state, local, NGO, and tribal contributors. The process of database production identified difficulties in the design of regional project tracking systems. The technical design issues range from low-level information (such as what defines a project or a location) to high-level issues that include data validation and legalities of inter-agency data sharing. The completed database will inform efficient monitoring design, effectiveness assessments, and restoration project planning/prioritization. We are currently focusing on comparing completed restoration projects with datasets of ecological need including standardizing the way limiting factors/habitat concerns are described in salmon recovery plans, and then asking if projects are being placed to address these ecological needs. Pacific Northwest Salmon Habitat Project Oracle Database.

  16. Fishes of Texas Project (FoTX) Database - Darwin Core

    • gbif.org
    • demo.gbif.org
    Updated Jul 1, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Dean A. Hendrickson; Adam E. Cohen; Dean A. Hendrickson; Adam E. Cohen (2025). Fishes of Texas Project (FoTX) Database - Darwin Core [Dataset]. http://doi.org/10.17603/c3wc70
    Explore at:
    Dataset updated
    Jul 1, 2025
    Dataset provided by
    Global Biodiversity Information Facilityhttps://www.gbif.org/
    University of Texas at Austin, Biodiversity Collections
    Authors
    Dean A. Hendrickson; Adam E. Cohen; Dean A. Hendrickson; Adam E. Cohen
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Description

    The Fishes of Texas Project aims to provide reliable occurrences of fishes from the entire extents of all the drainage basins that intersect Texas. Starting in 2006, with the database of specimens held in the University of Texas' Ichthyology Collection (TNHCi), we added specimen data collected from our study area from all of the museums we could find to create the initial version of the Fishes of Texas database. At the time, many of those were not online and all had their data in diverse formats and development of biodiversity data standards was in its infancy. We laboriously compiled these disparate sources into a schema derived from that of the Specify Collections Management software. We retain the verbatim data received from the data donors, but then did our own processing and quality control starting by normalizing formats and taxonomy. We manually georeferenced all localities, allowing us to map species to find outliers and, as possible, examined specimens and corrected determinations for misidentified specimens. We photographed specimens and original labels of many specimens examined. Uncertainty in dates is expressed using begin and end dates. Uncertainty in locations is expressed with a radius, that with coordinates (lat., long.), defines a circle in which the collection is determined to have occurred. The institutions holding examined specimens have been informed of our re-determinations and other corrections, but we do not control repatriation, so users may find our records for some specimens conflict with the data they might now independently publish. The database continues to grow and evolve, initially holding only specimen records from 44 institutions, now includes data from 116 institutions including non-specimen sources such as state and federal agencies, citizen scientists, peer and non-peer reviewed literature and word of mouth accounts. Thus, the dataset contains many records that are not openly published, for use by researchers and resource managers interested in the fish fauna of Texas and adjoining parts of its river basins. The same data can also be queried and explored in diverse ways via our website (http://www.fishesoftexas.org), where users will find additional documentation and other data-exploration tools. Please use our contact information there to notify us of any errors or other issues.

  17. d

    Archaeological Inventory Database, Minnesota.

    • datadiscoverystudio.org
    Updated Sep 1, 2017
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2017). Archaeological Inventory Database, Minnesota. [Dataset]. http://datadiscoverystudio.org/geoportal/rest/metadata/item/5fcf2cb4e4d84b649fe73c5c4ad73d86/html
    Explore at:
    Dataset updated
    Sep 1, 2017
    Description

    description: The State Historic Preservation Office (SHPO) Archaeological database, now maintained by The Office of the State Archaeologist (OSA), consists of archaeological properties identified and inventoried by SHPO, OSA, cooperating state and federal agencies, and professional archaeologists in the course of their archaeological research activities. For the past 30 years, these activities have been carried out through provisions of the National Historic Preservation Act, the Minnesota Historic Sites Act, and the Minnesota Field Archaeology Act.; abstract: The State Historic Preservation Office (SHPO) Archaeological database, now maintained by The Office of the State Archaeologist (OSA), consists of archaeological properties identified and inventoried by SHPO, OSA, cooperating state and federal agencies, and professional archaeologists in the course of their archaeological research activities. For the past 30 years, these activities have been carried out through provisions of the National Historic Preservation Act, the Minnesota Historic Sites Act, and the Minnesota Field Archaeology Act.

  18. Finland Consumer Confidence Indicator: Own Economy Now

    • ceicdata.com
    Updated May 15, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    CEICdata.com (2019). Finland Consumer Confidence Indicator: Own Economy Now [Dataset]. https://www.ceicdata.com/en/finland/consumer-confidence-indicator/consumer-confidence-indicator-own-economy-now
    Explore at:
    Dataset updated
    May 15, 2019
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    May 1, 2017 - Apr 1, 2018
    Area covered
    Finland
    Variables measured
    Consumer Survey
    Description

    Finland Consumer Confidence Indicator: Own Economy Now data was reported at 8.300 % in Oct 2018. This records an increase from the previous number of 6.400 % for Sep 2018. Finland Consumer Confidence Indicator: Own Economy Now data is updated monthly, averaging 4.400 % from Oct 1995 (Median) to Oct 2018, with 277 observations. The data reached an all-time high of 9.800 % in Aug 2006 and a record low of -4.000 % in Oct 1995. Finland Consumer Confidence Indicator: Own Economy Now data remains active status in CEIC and is reported by Statistics Finland. The data is categorized under Global Database’s Finland – Table FI.H008: Consumer Confidence Indicator.

  19. .now TLD Whois Database | Whois Data Center

    • whoisdatacenter.com
    csv
    Updated Oct 9, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    AllHeart Web Inc (2024). .now TLD Whois Database | Whois Data Center [Dataset]. https://whoisdatacenter.com/tld/.now/
    Explore at:
    csvAvailable download formats
    Dataset updated
    Oct 9, 2024
    Dataset provided by
    AllHeart Web
    Authors
    AllHeart Web Inc
    License

    https://whoisdatacenter.com/terms-of-use/https://whoisdatacenter.com/terms-of-use/

    Time period covered
    Aug 2, 2025 - Dec 31, 2025
    Description

    .NOW Whois Database, discover comprehensive ownership details, registration dates, and more for .NOW TLD with Whois Data Center.

  20. O

    Open Database Connectivity Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Jan 6, 2025
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Pro Market Reports (2025). Open Database Connectivity Market Report [Dataset]. https://www.promarketreports.com/reports/open-database-connectivity-market-7981
    Explore at:
    doc, ppt, pdfAvailable download formats
    Dataset updated
    Jan 6, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The ODBC market offers a range of products to cater to diverse customer requirements. Multi-tier ODBC drivers are designed for complex data environments that require connectivity to multiple databases simultaneously. Single-tier ODBC drivers are suitable for simpler data environments where connectivity to a single database is sufficient. Cloud-based ODBC solutions provide the benefits of cloud computing, such as scalability, flexibility, and ease of maintenance. On-premise ODBC solutions offer greater control and customization options for organizations with specific data management requirements. Recent developments include: April 2023: Amazon DocumentDB (with MongoDB compatibility) is a scalable, incredibly durable, fully managed database service for running mission-critical MongoDB workloads. Amazon DocumentDB recently disclosed a new ODBC connection that allows Microsoft Excel and PowerBI to connect to Amazon DocumentDB clusters. With the ODBC connector, anyone may now query and view data stored in DocumentDB from programs that allow ODBC access., February 2021: The open-source data networking technology called Apache Arrow Flight, which Dremio co-developed and which dramatically increases data transmission rates, will now be supported by Dremio, a pioneer in the field of data lake transformation. Using over ten-year-old technologies like Java Database Connectivity (JDBC) and Open Database Connectivity (ODBC), client applications can now communicate with Dremio's data lake service more swiftly than they could previously..

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
The NOW Community (2020). NOW — New and Old Worlds: Database of fossil mammals [Dataset]. http://doi.org/10.5281/zenodo.4268068

NOW — New and Old Worlds: Database of fossil mammals

Explore at:
67 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Nov 11, 2020
Authors
The NOW Community
Description

Overview NOW is a global database of fossil mammal occurrences, currently containing around 70, 000 locality-species entries. The database spans the last 66 million years, with the primary focus on the last 23 million years. Whereas the database contains a record on all continents, the main focus and coverage of the database historically have been on Eurasia. The database covers a large part of the mammalian fossil record known to research, focusing on classical and actively researched fossil localities. It is run by a management team in collaboration with an international advisory board of experts. Rather than a static archive, the database emphasizes the continuous integration of new knowledge of the community, continuous data curation, and consistency of scientific interpretations. The database records species occurrence at localities worldwide, as well as ecological characteristics of fossil species, geological contexts of localities and more. The database is primarily used for two purposes: for queries about other occurrences of particular taxa, their properties and the properties of localities in the spirit of an encyclopedia; and for large scale research and quantitative analyses of evolutionary processes, patterns, reconstructing past environments, as well as interpreting evolutionary contexts. Accessing the data The NOW data are fully open, requiring no logging in nor a community membership is necessary for using the data for any purpose. Now data can be accessed from www.nowdatabase.org/now/database/. The most updated data can be downloaded directly from the NOW user interface. In addition, archived versions are available. Citation Minimum required attribution Data (https://nowdatabase.org/now/database/) by The NOW Community / CC BY 4.0. http://doi.org/10.5281/zenodo.4268068 Suggested citation or attribution The NOW Community [year]. New and Old Worlds Database of Fossil Mammals (NOW). Licensed under CC BY 4.0. Retrieved [download date] from https://nowdatabase.org/now/database/. http://doi.org/10.5281/zenodo.4268068

Search
Clear search
Close search
Google apps
Main menu