Find research datasets worth reusing

opencc-zeroJan 2016View details →

Data licences and organization type of contributors to the Global Biodiversity Information Facility as of 19 January 2016

Data from the Global Biodiversity Information Facility were extracted using R (version 3.2.0) on 9 July 2015 using the rgbif package (version 0.9.0) (Chamberlain, S., Ram, K., Barve, V. & Mcglinn, D. (2015) Package ‘rgbif’: Interface to the Global 'Biodiversity' Information Facility 'API' http://cran.r-project.org/web/packages/rgbif/rgbif.pdf). The ‘rights’ statements was extracted for all occurrence datasets with one or more observations. A total of 12,458 datasets were extracted, but only about 11% of the datasets have an explicit data-useage-rights statement at the dataset level. However, some datasets use the occurrence level ‘rights’ and ‘accessRights’ fields. To extract these data the rights information was obtained from the first record of each dataset where a rights statement was missing at the dataset level. The datasets were categorized into 13 different types depending on the origin of the observations. <ol> <li>Biodiversity Information Facility or data centre</li> <li>Botanical Garden or Herbarium</li> <li>Citizen science</li> <li>Commercial</li> <li>Data publisher</li> <li>Educational</li> <li>Government</li> <li>Museum</li> <li>Network</li> <li>Parks Authority or Nature Reserve</li> <li>Research institution</li> <li>Society</li> <li>Foundations</li> </ol>

opencc-by-sa-4.0Jun 2021View details →

Areas of global importance for conserving terrestrial biodiversity, carbon, and water

Content: This data repository contains the results of the NatureMap ( naturemap.earth/) conservation prioritization effort. The maps were created by jointly optimizing biodiversity and NCPs such as carbon and/or water. Usage notes: Maps are supplied at both 10km and 50km resolution unless specified differently in the manuscript. All maps that aim to find priority areas for all species considered in the analysis, utilize a series of representative sets. The ranks for each layer are area-specific and can be used to extract summary statistics by simple subsetting. For example: To obtain the top 30% of land area for biodiversity and carbon, one needs to create a mask of all areas lower than a value of 30 from the respective ranked layers. For convenience two files are supplied that contain the fraction of land area per grid cell times 1000. Multiplying those with the cell area (100km2, respectively 2500km2) gives the exact amount of land area in a given grid cell. These are labelled " globalgrid_mollweide_**km.tif " can be used to create masks for the priority maps. Spatial resolution: 10 and 50 km Geographic projection: World Mollweide Equal Area projection PROJ4 ( +proj=moll +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs ) Filename suffix description: 'minshort_speciestargets' =- Problem formulation where targets were achieved by minimzing a shortfall 'repruns10' =- The number of representative that were used to create the ranked layer 'biome.id' =- Species distribution were split by biome, thus creating separate targets for subpopulation 'withPA' =- Fractions of current protected areas (Date: WDPA 2019) were locked in as baseline and starting budget. Approximately 15% of the globe. Note that not entire grid cells, but fractions were locked in and build opon! 'carbon' =- Carbon was included in the prioritization and jointly optimized together with the other assets by giving it equal weighting (see manuscript) 'water' =- Water was included in the prioritization and jointly optimized together with the other assets by giving it equal weighting (see manuscript) License: CC-BY-SA 4.0 Citation: Jung, Martin, Andy Arnell, Xavier De Lamo, Shaenandhoa Garcia-Rangel, Matthew Lewis, Jennifer Mark, Cory Merow et al. (2021) "Areas of global importance for terrestrial biodiversity, carbon, and water." Nature Ecology & Evolution

opencc-by-4.0Sep 2021View details →

Data supplement for "Global agricultural trade and land system sustainability: implications for ecosystem carbon storage, biodiversity and human nutrition"

This data supplements the publication "Global agricultural trade and land system sustainability: implications for ecosystem carbon storage, biodiversity and human nutrition" by Thomas Kastner, Abhishek Chaudhary, Simone Gingrich, Alexandra Marques, U. Martin Persson, Giorgio Bidoglio, Gaëtane Le Provost, Florian Schwarzmüller, available here: <a href="https://doi.org/10.1016/j.oneear.2021.09.006">https://doi.org/10.1016/j.oneear.2021.09.006</a> For details, please refer to that publication.

opencc-by-4.0Oct 2021View details →

Data and R-scripts for "Land-use trajectories for sustainable land system transformations: identifying leverage points in a global biodiversity hotspot" (V2)

Sustainable land system transformations are necessary to avert biodiversity and climate collapse. However, it remains unclear where entry points for transformations exist in complex land systems. Here, we conceptualize land systems along land-use trajectories, which allows us to identify and evaluate leverage points; i.e., entry points on the trajectory where targeted interventions have particular leverage to influence land-use decisions. We apply this framework in the biodiversity hotspot Madagascar. In the Northeast, smallholder agriculture results in a land-use trajectory originating in old-growth forests, spanning forest fragments, and reaching shifting hill rice cultivation and vanilla agroforests. Integrating interdisciplinary empirical data on seven taxa, five ecosystem services, and three measures of agricultural productivity, we assess trade-offs and co-benefits of land-use decisions at three leverage points along the trajectory. These trade-offs and co-benefits differ between leverage points: two leverage points are situated at the conversion of old-growth forests and forest fragments to shifting cultivation and agroforestry, resulting in considerable trade-offs, especially between endemic biodiversity and agricultural productivity. Here, interventions enabling smallholders to conserve forests are necessary. This is urgent since ongoing forest loss threatens to eliminate these leverage points due to path-dependency. The third leverage point allows for the restoration of land under shifting cultivation through vanilla agroforests and offers co-benefits between restoration goals and agricultural productivity. The co-occurring leverage points highlight that conservation and restoration are simultaneously necessary. Methodologically, the framework shows how leverage points can be identified, evaluated, and harnessed for land system transformations under the consideration of path-dependency along trajectories.

opencc-by-4.0Oct 2024View details →

Global knowledge and use of soil biodiversity: Results of an expert survey

A global survey on soil biodiversity (see file Global Biodiversity Survey.pdf provided as an attachment) was conducted over a three-week period in March 2022 by the Global Soil Partnership (GSP) of the Food and Agriculture Organization (FAO) of the United Nations, as part of the activities of the International Network on Soil Biodiversity (NETSOB). The survey intended to obtain information on the current status of knowledge and use of soil organisms worldwide, i.e., to identify who is doing what, where, and how, as well as the main gaps, pitfalls, and opportunities across existing national initiatives and research. The survey included 122 questions that characterized the work undertaken by experts regarding microbes, fauna, and their activity in soils, community & functional assessments, inventories, mapping and monitoring activities, ecosystem services, applications, and threats to soil biodiversity, education, and communication activities, as well as public policies related to soil biodiversity. The online survey was created using the software Survey Monkey v. 11 and was sent out to over 70 thousand e-mail addresses with a link to complete the survey.  Over 2,600 responses were received, representing >1,350 institutions from 135 countries, mainly from experts active in research and academia. The number of respondents was not equal for all questions, as the survey guided the respondents to different parts, depending on their replies. The 122 questions and the replies of the respondents are presented as separate tabs in the attached Excel file (Results survey for Zenodo.xlsx). The respondents and their identities, as well as their e-mails and any personal websites were removed in the current file to maintain anonymity. Institutional websites were maintained as long as they did not identify the respondent(s) directly.  A detailed written description of the survey results was prepared as a manuscript for a special issue of the journal Soil Organisms, volume 97 (Brown et al., 2025). The survey was prepared by a team of scientists from the Brazilian Corporation for Agricultural Research (Embrapa) and collaborating institutions, with assistance from the board of the International Network on Soil Biodiversity (NETSOB), and with funding provided by the FAO. The work was further supported by the Fundação de Apoio a Pesquisa e Desenvolvimento Agropecuário Edmundo Gastal (FAPEG), Brazil, a grant of CNPq (Processo No. 312824/2022-0) to GGB, and of the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant program (# 05901–2019) to ZL, who was also supported by Western University.

opencc-zeroAug 2021View details →

A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF)

Publication date: 2022-12-06T07:37:19-06:00 A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF) --- Global Biodiversity Information Facility (GBIF) facilitates access to billions of biodiversity data records. These records include detailed accounts of life on earth. To help records of specific life forms, GBIF provides a taxonomic backbone [1,2]. This backbone contains a long list of names used to describe species and associated hierarchies and taxonomic publications. These lists are sourced from datasets around the world. At time of writing (6 Dec 2022), GBIF publishes a simplified version of their taxonomic backbone at [https://hosted-datasets.gbif.org/datasets/backbone/](https://hosted-datasets.gbif.org/datasets/backbone/) [1]. This repository provides script to pre-process https://hosted-datasets.gbif.org/datasets/backbone/current/simple.txt.gz to help facilitate access and improve performance of the creation of search indexes. Pre-process steps currently include: 1. reducing amount of columns 2. reverse sort by id 3. reverse sort by name Contents --- README:     this file repackage-gbif-backbone.sh:     script used to repackage GBIF Simple Backbone. repackage-gbif-backbone.log:     log of repackaging of GBIF Simple Backbone. backbone-current-simple.txt.gz:     original GBIF backbone archive gbif-backbone-by-name.tsv.gz:     two columns, gzipped, tab-separated text file with columns name, and id     reverse sorted by name  gbif-backbone-by-name.tsv.sha256:     sha256 hash of the uncompressed gbif-backbone-by-name.tsv.gz gbif-backbone-by-id.tsv.gz:     20 columns, gzipped, tab-separated text file with first 20 columns of repackaged GBIF backbone file     reverse sorted by id gbif-backbone-by-id.tsv.sha256:     sha256 hash of the uncompressed gbif-backbone-by-id.tsv.gz References --- [1] Simplied GBIF Backbone Taxonomy. Accessed at https://hosted-datasets.gbif.org/datasets/backbone/ on 2022-12-06. [2] GBIF Secretariat (2021). GBIF Backbone Taxonomy. Checklist dataset https://doi.org/10.15468/39omei accessed via GBIF.org on 2021-08-18. Hash URIs --- This publication includes the following content uris: hash://sha256/82d5f2153b4533322692d95eeb18b0f103e1b2297e38bd9ea935b07ba86cd7d5 hash://sha256/50c155f66efb2efba0b8b624f8541e81cbe16a701d420a5073791fb993f72919 hash://sha256/9cd7d4c91292d86c726210446cd6fe45602505a7c0ea3b7c4f4f481f85f193ad (uncompressed) hash://sha256/f950dde25cce9ba9cce67caa1c68ce0c99cb31fe2dc9658fec85a987d9f31654 hash://sha256/f21c6b90f17c6083fcfb4853f3c581dcc2aadd291691fa128392a205321f420b (uncompressed) hash://sha256/5e0a4d1d2d1cccbdcc6b2c9831fafe61c54eb055f2d13ec40d9ac161889b9f89 hash://sha256/f6e477133d0585706ee5522963b204200cb3cd198f011cbf62be0fa8519763b5 (uncompressed)

opencc-zeroMar 2023View details →

Global Biodiversity Information Facility (GBIF): an exhaustive list of gbif record ids, dataset keys, and their associated Occurrence IDs, Institution Code, Collection Codes and Catalog Numbers. hash://sha256/ea88f03a7bfd1ba853fdbea3203d54ab81ac3cdc8e8da7c96bbbba9c4b05d933 hash://md5/c49fe34785354847b37ea4509261e130

The Global Biodiversity Information Facility (GBIF) indexes thousands of biodiversity datasets from Natural History Collections, citizen science initiatives (e.g., iNaturalist, eBird), and other sources. As part of the index process, GBIF associates at least two identifiers with indexed records: a record id (aka gbifID) and a dataset id (aka dataset key). These ids are central to do lookup, reference data, and package interpreted data products. This publication contains an exhaustive list of GBIF IDs and ids associated by their data providers as derived from: GBIF.org (01 March 2023) GBIF Occurrence Download https://doi.org/10.15468/dl.pk3trq The resource (size: ~260GB) provided by GBIF had content id hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97 and was used to generate the resource included in this publication using <pre><code class="language-bash">preston cat 'zip:hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97!/0015281-230224095556074.csv'\ | cut -f 1,2,3,37,38,39\ | gzip\ > gbifid.tsv.gz </code></pre> with the content id of gbifid.tsv.gz (size: ~35GB) being hash://sha256/a339e32e10edaad585f61f2ded06cbb23e0618c65a6360db18d7d729054940a8 . the first 10 lines of gbifid.tsv.gz as extracted via <pre><code>preston cat --remote https://zenodo.org/record/7789866/files,https://linker.bio hash://sha256/a339e32e10edaad585f61f2ded06cbb23e0618c65a6360db18d7d729054940a8\ | gunzip\ | head</code></pre> are: <pre><code>gbifID datasetKey occurrenceID institutionCode collectionCode catalogNumber 2997162320 c71c8000-9fc7-422c-804a-ce6abe751771 3399442 CEPEC CEPEC CEPEC00109669 2997162309 c71c8000-9fc7-422c-804a-ce6abe751771 2733085 CEPEC CEPEC CEPEC00000818 2997162317 c71c8000-9fc7-422c-804a-ce6abe751771 2733086 CEPEC CEPEC CEPEC00000888 2997162313 c71c8000-9fc7-422c-804a-ce6abe751771 3399443 CEPEC CEPEC CEPEC00109744 2997162306 c71c8000-9fc7-422c-804a-ce6abe751771 2733087 CEPEC CEPEC CEPEC00000889 2997162316 c71c8000-9fc7-422c-804a-ce6abe751771 3399440 CEPEC CEPEC CEPEC00109605 2997162324 c71c8000-9fc7-422c-804a-ce6abe751771 2733088 CEPEC CEPEC CEPEC00000890 2997162308 c71c8000-9fc7-422c-804a-ce6abe751771 3399441 CEPEC CEPEC CEPEC00109615 2997162303 c71c8000-9fc7-422c-804a-ce6abe751771 2733089 CEPEC CEPEC CEPEC00000891</code></pre> Note that at time of writing, the html resource associated with the occurrence id 2997162320, and data set key c71c8000-9fc7-422c-804a-ce6abe751771 (extracted from of the first data row example above) are available via: https://gbif.org/occurrence/2997162320 and https://gbif.org/dataset/c71c8000-9fc7-422c-804a-ce6abe751771 respectively. This resource was initially created to help integrate with Bionomia (https://bionomia.net) to help associate people identifiers provided by bionomia to their original records via their GBIF ids. Bionomia re-uses GBIF records ids as a way to define links between records and the people (e.g., curators, collectors, identifiers) that worked on them.  In other words, this resource provides a versioned translation table from the GBIF data universe (as defined by GBIF record ids, and dataset keys) to the data collections that exist (and evolve) independent of it.  Note that the resource identified by hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97 was not included in this publication it was too big (260GB) to fit. You may be able to retrieve the resource from its original location at https://api.gbif.org/v1/occurrence/download/request/0015281-230224095556074.zip .

opencc-by-4.0Feb 2017View details →

Supplementary material 1: Global Biodiversity Information Facility: Taxa and Records from: Integrating and visualizing primary data from prospective and legacy taxonomic literature - Biodiversity Data Journal 3: e5063 (12 May 2015) https://doi.org/10.3897/BDJ.3.e5063

All records in GBIF with taxonomic ranks (kingdom, phylum, class, order, and species), basis of record (e.g., preserved specimen), and count of records, exported from GBIF on 7 December 2014.

Fig. 5 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 5: Das Suchportal des Botanik-Knotens von GBIF-Deutschland, einer der mehreren im Internet verfügbaren Zugangspunkte zu den Daten des GBIF-Netzwerks.

Fig. 2 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 2:Tatenflüsse über das Internet im GBIF-Netzwerk zwischen Nutzer, Suchportal und Datenlieferant.

Fig. 3 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 3: Die Zuordnung der Daten aus dem relationalen Datenschema der Sammlungsdatenbank zu den ABCD-Elementen wird im Mapping festgelegt und ist in einer komfortablen Oberfläche mit dem Internet- Browser möglich.

Fig. 1 in Freier Zugang zu den Informationen der Artenvielfalt - Wie werde ich Teil der Global Biodiversity Information Facility (GBIF)?

Fig. 1: Die Wrapper-Software umgibt die bestehenden Sammlungsdatenbanken mit einer zusätzlichen Abstraktionsschicht und bietet so eine definierte Schnittstelle zwischen den existierenden Datenbanksystemen und den GBIF-Suchportalen.

Fig.1 in Die Global Biodiversity Information Facility (GBIF) - Struktur, Aufgaben und Ziele

Fig.1: Das Knotensystem GBIF Deutschland und seine Anbindung an GBIF International. Die Daten fliessen aus den Teilprojekten in die Datenbanksysteme der einzelnen Knoten, denen ein BioCASE-Wrapper aufgesetzt ist, der auf dem ABCD-Datenmodell basiert. Damit ist es möglich, alle angebundenen Daten über das Datenportal von GBIF International im Internet abzurufen bzw. verfügbar zu machen. GBIF International stellt ausserdem die Wrapper-Software DiGIR, welche auf dem Darwin Core 2 aufbaut, zur Verfügung. Einzelne Teilprojekte, wie z.B. DIG mit BIODAT im Knoten Evertebraten I, setzen eigene Datenbanklösungen ein und fungieren daher als direkte GBIF Datenprovider. Die Angaben entsprechen dem Stand Anfang April 2005.

opencc-by-4.0Jun 2022View details →

A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF) - 2021-11-26

A Repackaged Taxonomic Backbone of Global Biodiversity Information Facility (GBIF) --- Global Biodiversity Information Facility (GBIF) facilitates access to billions of biodiversity data records. These records include detailed accounts of life on earth. To help records of specific life forms, GBIF provides a taxonomic backbone [1,2]. This backbone contains a long list of names used to describe species and associated hierarchies and taxonomic publications. These lists are sourced from datasets around the world. At time of writing (18 Aug 2021), GBIF publishes a simplified version of their taxonomic backbone at [https://hosted-datasets.gbif.org/datasets/backbone/](https://hosted-datasets.gbif.org/datasets/backbone/) [1]. This repository provides script to pre-process https://hosted-datasets.gbif.org/datasets/backbone/backbone-current-simple.txt.gz to help facilitate access and improve performance of the creation of search indexes. Pre-process steps currently include: 1. reducing amount of columns 2. reverse sort by id 3. reverse sort by name Contents --- README:     this file repackage-gbif-backbone.sh:     script used to repackage GBIF Simple Backbone. backbone-current-simple.txt.gz:     original GBIF backbone archive gbif-backbone-by-name.tsv.gz:     two columns, gzipped, tab-separated text file with columns name, and id     reverse sorted by name gbif-backbone-by-name.tsv.sha256:     sha256 hash of the uncompressed gbif-backbone-by-name.tsv.gz gbif-backbone-by-id.tsv.gz:     20 columns, gzipped, tab-separated text file with first 20 columns of repackaged GBIF backbone file     reverse sorted by id gbif-backbone-by-id.tsv.sha256:     sha256 hash of the uncompressed gbif-backbone-by-id.tsv.gz References --- [1] Simplied GBIF Backbone Taxonomy. Accessed at https://hosted-datasets.gbif.org/datasets/backbone/ on 2021-08-18. [2] GBIF Secretariat (2021). GBIF Backbone Taxonomy. Checklist dataset https://doi.org/10.15468/39omei accessed via GBIF.org on 2021-08-18. Hash URIs --- This publication includes the following content uris: repackage-gbif-backbone.sh:     hash://sha256/073ac5490252c4ccbbd4f516d391faebe62c9fde9e4d75ae870441a86c382527 backbone-current-simple.txt.gz:     hash://sha256/15cbfc038e666356af27248935f79e408ed51fd8c0b49a668fed8dbf72591502     hash://sha256/1f78788a4a046dcbcf1e36c7658a1e333ca60e7586a372238d58b938d91fde51 (uncompressed) gbif-backbone-by-name.tsv.gz:     hash://sha256/6e11ae9961a9498b60d4bdeb489d6c1f5da9c2732310edaecdc79bd287b79ef4     hash://sha256/934ce05dbd067abb209168bd1d9389f122d051e1b7374b5d757a12e86f8da9a5 (uncompressed) gbif-backbone-by-id.tsv.gz:     hash://sha256/c434c7d3622421b17dadcd119391b32a66edee59f484d4cab924d92fd17713e2     hash://sha256/e2cf9116a21966315b0482d391052223e21c8e916ae0c097dfd37bed017b815b (uncompressed)

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The global distribution of known and undiscovered ant biodiversity

Invertebrates constitute the majority of animal species and are critical for ecosystem functioning and services. Nonetheless, global invertebrate biodiversity patterns and their congruences with vertebrates remain largely unknown. We resolve the first high-resolution (~20-km) global diversity map for a major invertebrate clade, ants, using biodiversity informatics, range modeling, and machine learning to synthesize existing knowledge and predict the distribution of undiscovered diversity. We find that ants and different vertebrate groups have distinct features in their patterns of richness and rarity, underscoring the need to consider a diversity of taxa in conservation. However, despite their phylogenetic and physiological divergence, ant distributions are not highly anomalous relative to variation among vertebrate clades. Furthermore, our models predict rarity centers largely overlap (78%), suggesting that general forces shape endemism patterns across taxa. This raises confidence that conservation of areas important for small-ranged vertebrates will benefit invertebrates while providing a "treasure map" to guide future discovery.

opencc-zeroJul 2022View details →

Fig. 7 in The global distribution of known and undiscovered ant biodiversity

Fig. 7. Globalprotection status of richness andrarity centers. Richness andrarity centers (top 10% of area) are overlaid with protected areas usingdata retrieved from the World Database of Protected Areas (protectedplanet.net) and processed. Biodiversity centers for ants based on current sampling (top row), predicted ant centers under universal high sampling (second row), and vertebrate centers (bottom row) are presented.

Fig. 6 in The global distribution of known and undiscovered ant biodiversity

Fig. 6. Empirical andpredicted raritycenters of Eastern Asiaand Oceania. Raritycentersbased on currentknowledge andprojectedby a Random Forestmodelunder a "universal high sampling" scenario. See Fig. 3 for more explanation.

Fig. 3 in The global distribution of known and undiscovered ant biodiversity

Fig. 3. Machine learningpredictshowincreased samplingcouldchangeour understandingof antrichness andrarity centers. Random Forestmodelswere trained topredict ant speciesrichness andrarity values asafunction of climate (7 vars.),topography,biogeographic realm, vertebratebiodiversity, andsampling density. Wethen used the models to predict (A) richness and rarity values under a "universal high sampling" scenario, revealing which areas may drop out of the top 10% with increased global sampling (red), which are robust to sampling (purple), and which centers are predicted to enter the top 10% with increased sampling (blue). The latter represents a treasure map indicating areas that should be prioritized for future sampling. The top 10% areas for vertebrates are indicated by hatched regions. (B) Overlap fractions for empirical and projected center designations for richness and rarity, and Spearman's correlations continuous richness and rarity values.

Fig. 2 in The global distribution of known and undiscovered ant biodiversity

Fig. 2. Global patterns of ant rarity and comparison with terrestrial vertebrates. (A) The concordance of different rarity (i.e., rarity-weighted richness, a metric indicating a concentration of small-ranged species) centers (top 10% of area) for amphibians, birds, mammals, reptiles, and ants. (B) Continuous rarity maps for ants and vertebrates. (C) Spearman's correlation matrix for grid cell–level rarity across taxa.