This dataset contains occurrence data of flora and fauna species. From the Netherlands on a 5 x 5 km scale, data from other countries are exact. Observations from Belgium are excluded and can be accessed on GBIF through Natuurpunt and Natagora. It summarizes the observations recorded by >175.000 volunteers.

Observations database for reporting of nature observations. Main observed species groups are butterflies, birds, vascular plants and mammals. These groups include 88% of observations.

The New York State Office of Parks, Recreation and Historic Preservation (OPRHP) oversees more than 250 state parks, historic sites, recreational trails, golf courses, boat launches and more, encompassing nearly 350,000 acres, that are visited by 74 million people annually. These facilities contribute to the economic vitality and quality of life of local communities and directly support New York’s tourism industry. Parks also provide a place for families and children to be active and exercise, promoting healthy lifestyles. The agency is responsible for the operation and stewardship of the state park system as well as advancing a statewide parks, historic preservation, and open space mission. The New York State Office of Parks, Recreation and Historic Preservation operates several nature centers throughout the state. Visitors to our nature centers learn about the abundance of natural resources to be found in state parks. Our state parks and historic sites are hosts to scenic viewsheds, geologic features and both common and rare flora and fauna. For more information, visit http://nysparks.com/environment/nature-centers/default.aspx

The Washington Natural Heritage Program maintains a database of rare and imperiled species and plant communities for the state. The Element Occurrence (EO) records that form the core of the Natural Heritage database include information on the location, status, characteristics, numbers, condition, and distribution of elements of biological diversity using established Natural Heritage Methodology developed by NatureServe and The Nature Conservancy (TNC). An Element Occurrence (EO) is an area of land and/or water in which a species or natural community is, or was, present. An EO should have practical conservation value for the Element as evidenced by potential continued (or historical) presence and/or regular recurrence at a given location. For species Elements, the EO often corresponds with the local population, but when appropriate may be a portion of a population or a group of nearby populations (e.g., metapopulation). For community Elements, the EO may represent a stand or patch of a natural community, or a cluster of stands or patches of a natural community. Because they are defined on the basis of biological information, EOs may cross jurisdictional boundaries. An Element Occurrence record is a data management tool that has both spatial and tabular components including a mappable feature and its supporting database. EOs are typically represented by bounded, mapped areas of land and/or water or, at small scales, the centroid point of this area. EO records are most commonly created for current or historically known occurrences of natural communities or native species of conservation interest. They may also be created, in some cases, for extirpated occurrences.

See full Resource Data Guide here.Abstract: The Natural Diversity Database Areas is a 1:24,000-scale, polygon feature-based layer that represents general locations of endangered, threatened and special concern species. The layer is based on information collected by DEEP biologists, cooperating scientists, conservation groups and landowners. In some cases an occurrence represents a location derived from literature, museum records and specimens. These data are compiled and maintained by the DEEP Bureau of Natural Resources, Natural Diversity Database Program. The layer is updated every six months and reflects information that has been submitted and accepted up to that point. The layer includes state and federally listed species. It does not include Critical Habitats, Natural Area Preserves, designated wetland areas or wildlife concentration areas. These general locations were created by randomly shifting the true locations of terrestrial species and then adding a 0.25 mile buffer distance to each point, and by mapping linear segments with a 300 foot buffer associated with aquatic, riparian and coastal species. The exact location of the species observation falls somewhere within the polygon area and not necessarily in the center. Attribute information includes the date when these data were last updated. Species names are withheld to protect sensitive species from collection and disturbance. Data is compiled at 1:24,000 scale. These data are updated every six months, approximately in June and December. It is important to use the most current data available.Purpose: This dataset was developed to help state agencies and landowners comply with the State Endangered Species Act. Under the Act, state agencies are required to ensure that any activity authorized, funded or performed by the state does not threatened the continued existence of endangered or threatened species or their essential habitat. Applicants for certain state and local permits may be required to consult with the Department of Energy and Environmental Protections's Natural Diversity Data Base (NDDB) as part of the permit process. Follow instructions provided in the appropriate permit guidance. If you require a federal endangered species review, work with your federal regulatory agency and review the US Fish & Wildlife IPaC tool. Natural Diversity Data Base Areas are intended to be used as a pre-screening tool to identify potential impacts to known locations of state listed species. To use this data for site-based endangered species review, locate the project boundaries and any additionally affected areas on the map. If any part of the project is within a NDDB Area then the project may have a conflict with listed species. In the case of a potential conflict, an Environmental Review Request (https://portal.ct.gov/deep-nddbrequest) should be made to the Natural Diversity Data Base for further review. The DEEP will provide recommendations for avoiding impacts to state listed species. Additional onsite surveys may be requested of the applicant depending on the nature and scope of a project. For this reason, applicants should apply early in the planning stages of a project. Not all land use choices will impact the particular species that is present. Often minor modifications to the proposed plan can alleviate conflicts with state listed species.Other uses of the data include targeting areas for conservation or site management to enhance and protect rare species habitats.Supplemental information: For additional information, refer to the Department of Energy and Environmental Protection En

The article presented a synthesis of expert opinions about open research remarked as a substantial influence on knowledge and innovation of concepts dissemination contained in published and unpublished manuscripts. The practise of open science reach increased in acceptance in recent years due to the challenging effort of the researchers who have written scientific articles.

This database categorizes 91 projects using nature-based solutions (NBS) in riverine environments across the United States. These 91 projects were identified in a non-exhaustive search of Federal, State, local, and other publicly available documentation. Eight publicly available reports and websites collectively described 45 projects, while the remaining projects were sourced from individual websites or articles that described one or two projects each. For each project, we identified the following: NBS strategy or strategies implemented, total cost, year implemented, project size, and project city and state. Here, project size refers to the stream length in feet influenced by the project. For some projects, details such as project cost and project size were not recorded in publicly available documents and reports.

Raw data supporting the Springer Nature Data Availability Statement (DAS) analysis in the State of Open Data 2024. SOOD_2024_special_analysis_DAS_SN.xlsx contains the DAS, DOI, publication date, DAS categories and related country by Insitution of any author.SOOD 2024_DAS_analysis_sharing.xlsx contains the summary data by country and data sharing type.Utilizing the Dimensions database, we identified articles containing key DAS identifiers such as “Data Availability Statement” or “Availability of Data and Materials” within their full text. Digital Object Identifiers (DOIs) of these articles were collected and matched against Springer Nature’s XML database to extract the DAS for each article. The extracted DAS were categorized into specific sharing types using text and data matching terms. For statements indicating that data are publicly available in a repository, we matched against a predefined list of repository identifiers, names, and URLs. The DAS were classified into the following categories:1. Data are available from the author on request. 2. Data are included in the manuscript or its supplementary material. 3. Some or all of the data are publicly available, for example in a repository.4. Figure source data are included with the manuscript. 5. Data availability is not applicable.6. Data are declared as not available by the author.7. Data available online but not in a repository.These categories are non-exclusive: more than one can apply to any one article. Publications outside the 2019–2023 range and non-article publication types (e.g., book chapters) that were initially included in the Dimensions search results were excluded from the final dataset. Articles were included in the final analysis after applying the exclusion criteria. Upon processing, it was found that only 370 results were returned for Botswana across the five-year period; due to this low number, Botswana was not included in the DAS focused country-level analysis. This analysis does not assess the accuracy of the DAS in the context of each individual article. There was no manual verification of the categories applied; as a result, terms used out of context could have led to misclassification. Approximately 5% of articles remained unclassified following text and data matching due to these limitations.

NOTE: A more current version of the Protected Areas Database of the United States (PAD-US) is available: PAD-US 2.1 https://doi.org/10.5066/P92QM3NT. The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public land and voluntarily provided private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastre Theme (https://communities.geoplatform.gov/ngda-cadastre/). The PAD-US is an ongoing project with several published versions of a spatial database including areas dedicated to the preservation of biological diversity, and other natural (including extraction), recreational, or cultural uses, managed for these purposes through legal or other effective means. The database was originally designed to support biodiversity assessments; however, its scope expanded in recent years to include all public and nonprofit lands and waters. Most are public lands owned in fee; however, long-term easements, leases, agreements, Congressional (e.g. 'Wilderness Area'), Executive (e.g. 'National Monument'), and administrative designations (e.g. 'Area of Critical Environmental Concern') documented in agency management plans are also included. The PAD-US strives to be a complete inventory of public land and other protected areas, compiling “best available” data provided by managing agencies and organizations. The PAD-US geodatabase maps and describes areas with over twenty-five attributes in nine feature classes to support data management, queries, web mapping services, and analyses. NOTE: A more current version of the Protected Areas Database of the United States (PAD-US) is available: PAD-US 2.1 https://doi.org/10.5066/P92QM3NT This PAD-US Version 2.0 dataset includes a variety of updates and changes from the previous Version 1.4 dataset. The following list summarizes major updates and changes: 1) Expanded database structure with new layers: the geodatabase feature class structure now includes nine feature classes separating fee owned lands, conservation (and other) easements, management designations overlapping fee lands, marine areas, proclamation boundaries and various 'Combined' feature classes (e.g. 'Fee' + 'Easement' + 'Designation' feature classes); 2) Major update of the Federal estate including data from 8 agencies, developed in collaboration with the Federal Geographic Data Committee (FGDC) Federal Lands Working Group (FLWG, https://communities.geoplatform.gov/ngda-govunits/federal-lands-workgroup/); 3) Major updates to 30 States and limited additions to 16 other States; 4) Integration of The Nature Conservancy's (TNC) Secured Lands geodatabase; 5) Integration of Ducks Unlimited's (DU) Conservation and Recreation Lands (CARL) database; 6) Integration of The Trust for Public Land's (TPL) Conservation Almanac database; 7) The Nature Conservancy (TNC) Lands database update: the national source of lands owned in fee or managed by TNC; 8) National Conservation Easement Database (NCED) update: complete update of non-sensitive (suitable for publication in the public domain) easements; 9) Complete National Marine Protected Areas (MPA) update: from the NOAA MPA Inventory, including conservation measure ('GAP Status Code', 'IUCN Category') review by NOAA; 10) First integration of Bureau of Energy Ocean Management (BOEM) managed marine lands: BOEM submitted Outer Continental Shelf Area lands managed for natural resources (minerals, oil and gas), a significant and new addition to PAD-US; 11) Fee boundary overlap assessment: topology overlaps in the PAD-US 2.0 'Fee' feature class have been identified and are available for user and data-steward reference (See Logical_Consistency_Report Section). For more information regarding the PAD-US dataset please visit, https://usgs.gov/gapanalysis/PAD-US/. For more information about data aggregation please review the “Data Manual for PAD-US” available at https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/pad-us-data-manual .

Comprehensive dataset of 298 Nature preserves in Connecticut, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

GIS theme (divided into surface and point theme) with spatial objects from the Nature Database associated with the programme of activities of the same name, Mapping of habitat types. This group of activity types in the Nature Database concerns in particular the mapping of habitat types within the habitat areas, but also the State's mapping of valuable forest under Section 25 of the Forest Act.Flat theme delimits areas with the presence of the individual habitat types, and point theme indicates the position of midpoint of botanical documentation – typical circle with radius of 5 m. For each GIS object, the following attributes are displayed from each entry in the Nature Database: - Activity: The type of activity (entry form) to which the registration belongs. - Responsible institution: the authority or consulting firm that is the data controller; - Place name: Name or code used by the responsible institution for the specific location. - Field date: Date when the registration was made in the field - Habitat type: The habitat type, if any, indicated for each registration. In some cases, main and sub-nature types may be indicated, which will appear from the individual registration in the Nature Database. - State of Nature Index: For many registrations, a natural state index will have been calculated, cf. the Order on the classification and setting of targets for the natural state in international nature protection areas. The index goes from 0 (bad) to 1 (high). - Structural index: For many registrations, a structural index will have been calculated, cf. the Order on the classification and setting of targets for the state of nature in international nature protection areas. The index goes from 0 (bad) to 1 (high). - Species index: For many registrations, a species index will have been calculated, cf. the Order on the classification and setting of targets for the state of nature in international nature protection areas. The index goes from 0 (bad) to 1 (high). - ActID: Unique identification number of the activity in the Nature Database. AktID is included in the URL for displaying the complete registration form for each registration. - LINK: Link to display the complete registration form for each registration.

This dataset underpins research undertaken by the Data Publishing team at Springer Nature which analysed the impact of Data Availability Statements on Nature journal editors, and how researchers choose to share their data.Mandatory Data Availability Statements were introduced by Nature journals in 2016 which require researchers to state how their data can be accessed.The dataset comprises of a single Excel file, which include the journal title, unique ID for each published article, subject areas, and the estimated time required to include a Data Availability Statement as reported by the journals' editorial staff. The median time per journal is also calculated.The full text of the Data Availability statement is included, and the statements are coded according to the data sharing method described.This dataset supports a paper that has been peer reviewed and accepted for presentation at the International Digital Curation Conference 2018. The paper has been submitted to the International Journal of Digital Curation. At the time of dataset release the full paper is available as a preprint in BioRxiv.

List of Natural Products databases mentioned in scientific litterature since 2000The Table1_s3 is the most recent version.The table "stereoOverlapTable" references the percentage of agreement in terms of stereochemistry between databases when the latter share molecules.

Comprehensive dataset of 1,313 Nature preserves in France as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This dataset compiles the identifying details of Springer Nature Group published journals. This covers journals published by Springer Nature, Nature Portfolio, Palgrave Macmillan, Springer, BioMed Central, and Scientific American, It accounts for both current (as of Oct. 22) and archived journals.

It compiles identifiers of each journal where possible: Title, Alternative title, eBook and Print ISSN, Title ID, Active years, Primary language, Publisher and imprint, Access type, Default licence and Platform URL.

In particular aid for Springer Negotiations of 2022/23, it identifies the ISSN used via UnSub.org (and Jisc) for relevant journals, a URL link to the editorial board of current journals, and a subject area has also been assigned to each journal.

This dataset is designed to further aid data analysis by universitites in preparations for the Springer Negotiations 2022/23 (following the success of the Elsevier Negotiations in 2021/22).

Further information and sources can be found in the attached ReadMe file. Both CSV and XLSX files contain the same data in two different formats.

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890-2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change. The recording scheme implemented at nature reserves offers unique opportunities for addressing community-level change across replicate local communities. These data have been systematically collected not as independent monitoring efforts, but using a shared and carefully standardized protocol adapted for each local community. Thus, variability in observation effort is of much less concern than in most other distributed cross-taxon phenological monitoring schemes. To enable analyses of higher-level taxonomical groups, we have included taxonomic classifications for the species in the database. The compilation of the data in a common database was initiated in the context of the project “Linking environmental change to biodiversity change: long-term and large-scale data on European boreal forest biodiversity” (EBFB), funded for 2011-2015 by the Academy of Finland, and continued with the help of other funding to OO since 2016. We organized a series of project meetings that were essential for data acquisition, digitalization and unification. These meetings were organized in Ekaterinburg (Russia) by the Institute of Plant and Animal Ecology, Ural Branch of RAS (Russian Academy of Sciences) in 2011; in Petrozavodsk (Russia) by the Forest Research Institute, at the Karelian Research Center, RAS in 2013; in Miass (Russia) by the Ilmen Nature Reserve in 2014; in Krasnoyarsk (Russia) by the Stolby Nature Reserve in 2014; in Artybash (Russia) by the Altaisky Nature Reserve in 2015; in Listvyanka, Lake Baikal (Russia) by the Zapovednoe Pribajkalje Nature Reserve in 2016; in Roztochja (Ukraine) by the Ministry of Natural Resources of Ukraine in 2016; in Puschino (Russia) by the Prioksko-Terrasnyj Nature Reserve in 2017, in Vyshinino (Russia) by the Kenozero National Park in 2018, and in St Petersburg (Russia) by the Komarov Botanical Institute of the Russian Academy of Sciences in 2019. The compilation of the data into a common database was conducted by the database coordinators (EM and CL) in Helsinki (Finland). Those participants that already held the data in digital format submitted it in the original format, and those that had the data only in paper format digitized it using Excel-based templates developed in the project meetings. Submitted data were processed by the database coordinators according to the following steps: The data were formatted so that each observation (the phenological date of a particular event in a particular locality and year) formed one row in the data table (e.g. un-pivoting tables that involved several years as the columns). The phenological event names were split into event type (e.g. “first occurrence“) and species name. The event type names (provided originally typically in Russian) were translated into English and the species names (usually provided in Russian) were identified to scientific names, using dictionaries that were partly developed and verified in the project meetings. All scientific names were periodically verified by mapping them to the Global Biodiversity Information Facility (GBIF) backbone taxonomy. We associated each data record with the following set of information fields: (1) project name, i.e. the source organization, (2) dataset name, (3) locality name, (4) unique taxon identifier, (5) scientific taxon name, and (6) event type. We imported the data records in the main database (maintained as an EarthCape database at https://ecn.ecdb.io). During the import, the taxonomic names, locality names, and dataset names were matched against already existing records.

Survey data underlying Springer Nature whitepaper 'Practical challenges for researchers in data sharing'. Data were collected between April and May in 2017 by contacting registrants to nature.com, biomedcentral.com and springer.com.The dataset is made up of 7,719 respondents from 126 different countries.Related infographic: https://doi.org/10.6084/m9.figshare.5996786

Raw Data for Nature manuscript 2022-05-07139B

The static theme. The theme shows the state of light-open habitat nature within the habitat areas mapped in the period 2016-2019. Data from the Nature Database. Note that several habitat types can be mapped on the same area with different percentages. The theme includes information on the state of nature, species index class and structural index class, as well as the structural parameters presented in the Natura 2000 baseline analyses 2022-2027. Presented data is quality-assured, nationwide data that is publicly available. This is data collected and quality assured in connection with the implementation of the governmental surveillance programme - NOVANA. The practical implementation of the monitoring and subsequent data processing can be found in the technical instructions on the DCE website and in the annual NOVANA reports. File name: Np3b2020_lysaaben_natur2016_2019

The Vermont Fish and Wildlife Department's Natural Heritage Inventory (NHI) maintains a database of rare, threatened and endangered species and natural (plant) communities in Vermont. The Department is a member of the network of Natural Heritage Programs and Conservation Data Centres network that collaborates with NatureServe, which is the umbrella organization. The Element Occurrence (EO) records that form the core of the Natural Heritage Inventory database include information on the location, status, characteristics, numbers, condition, and distribution of elements of biological diversity using established Natural Heritage Methodology developed by NatureServe and The Nature Conservancy. An Element Occurrence (EO) is an area of land and/or water in which a species or natural community is, or was, present. An EO should have practical conservation value for the Element as evidenced by potential continued (or historical) presence and/or regular recurrence at a given location. For species Elements, the EO often corresponds with the local population, but when appropriate may be a portion of a population or a group of nearby populations (e.g., metapopulation). For community Elements, the EO may represent a stand or patch of a natural community, or a cluster of stands or patches of a natural community. Because they are defined on the basis of biological information, EOs may cross jurisdictional boundaries. An Element Occurrence record is a data management tool that has both spatial and tabular components including a mappable feature and its supporting database. EOs are typically represented by bounded, mapped areas of land and/or water or, at small scales, the centroid point of this area. EO records are most commonly created for current or historically known occurrences of natural communities or native species of conservation interest.