Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
322
datasets available to search
ShareScore release 0.7.1
Dataset results
322 results for “census”
Aspen Forest Stem Map and Tree Census at the University of Michigan Biological Station, Pellston, MI 1974-2018
In 1974, a one hectare plot was established at the University of Michigan Biological Station to further understand successional trajectories of birch and aspen forests in northern Michigan. Trees with a DBH greater than 5 cm were inventoried and later, the location of the tree within the plot was documented by the UMBS resident biologist. Plots were remeasured 5 additional times by different groups at the station.
CPC01 Annual census of Greater Prairie Chickens on leks at Konza Prairie
Location of leks and number of birds per lek are censused during late April and early May across Konza Prairie to document year to year densities of greater prairie chickens. This dataset is continued by CPC02 after 04/19/1999.
CPC02 Census of greater prairie chicken on leks at Konza Prairie
Location of leks and number of birds per lek are censused during late April and early May across Konza Prairie to document year to year densities of greater prairie chickens.
Census of species, diameter and location at the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico
Censuses are performed every 5 years, the last one was finished in 2012 and the quality control process in 2013. File LFDP_CENSUS1 contains data for the Census 1 (Survey 1,2,and 3) of pre LFDP including the Tag number Species code, quadrat location and date and stem diameter D130 (diameter measured at 130 cm from the ground (DBH). It also contains the diameter as recorded for all stems in survey 1, 2 and 3. LFDP_CENSUS1a has the same structure as LFDP_census1. In LFDP_census1a file, however, the stem diameters have been calculated to allocate "missed" stems that were found in survey 2, 3 or Census 2 to either Census 1 survey 1 (stems >=10 cm D130) or Census 1 survey 3 (stems >=1, <10 cm D130). We calculated the diameter the stem would have had, if it had been recorded at the same time the quadrat it was located in was assessed, in the appropriate survey for that stem size. To extrapolate the stem size back in time, we used the actual growth rate of that individual stem if more than one measurement was available. If only one diameter measurement was available we used the median growth rate for that species in the appropriate size class (median growthrate of stems <10 cm, or median for stems >=10, <30 cm D130). Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
El Yunque Chronosequence Tree Census data
The El Yunque Chronosequence plots consist of four sites, El Verde 1 (EV1), Sabana 1 (SB1), Sabana 2 (SB2), and Sabana 3 (SB3), which are located at the edges of El Yunque National Forest at sites to the south of El Verde and Sabana Field Stations. The plots represent a range of successional stages representing areas in agriculture or recently abandoned in 1936 but reforested after 1950, and areas in agriculture or recently abandoned in 1977 and reforested since that time. They range in size from ~0.5 to 1 ha, vary in elevation from ~150m to 550m a.s.l. and span a wide range of ages and land use histories (Table 1). Plot Name Size Age Elevation EV1 10,000 m2 (1 ha) >62 yrs but < 76 yrs ~ 550m SB1 4,625 m2 (~0.5 ha) >62 yrs but not primary forest ~100-150m SB2 6,400 m2 (~0.6 ha) >35 yrs but < 62 yrs ~100-150m SB3 4,800 m2 (~0.5 ha) Primary forest ~100-150m One of these plots (EV1) is south of El Verde Field Station, on Forest Service land just over the property boundary.  This area was in agriculture in 1936 but appeared forested in a 1950 aerial photograph, and there are differences in forest structure and species composition consistent with the known differences in land use history. The other three Chronosequence sites are just south of the Sabana Field Station on Forest Service Land on the opposite side of the forest from El Verde. One plot (SB2) is located in young secondary forest in an area immediately adjacent to an old teak plantation forest. Another plot (SB1) is located in an area that was sparsely forested in 1936 and which appeared reforested in 1950. The third plot in Sabana (SB3) is located in a patch of primary “tabonuco†(named for the abundance of this tree species) forest on a steep slope on the west side of the Sabana River. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundati
Tree Map for Census at the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico
This data set shows the Tag number, Quadrat location, Species code, diameter and XY coordinates of stems >=10 cm D130 present at the time of Hurricane Hugo and in the first census. The data set is composed of two files both with the same file structure. In LFDP_C1treemap.txt the diameters (Fdiam) are as recorded in the field data. In LFDP_C1TREEMAPa.txt the stem diameters (Fdiam) were calculated to allocate "missed" stems (stems >=10 cm D130) that were found in survey 2, 3 or Census 2 to Census 1 survey 1. We calculated the diameter the stem would have had, if it had been recorded at the same time the quadrat it was located in was assessed, in the appropriate survey for that stem size. To extrapolate the stem size back in time, we used the actual growth rate of that individual stem if more than one measurement was available. If only one diameter measurement was available we used the median growth rate for that species in the appropriate size class stems >=10, <30 cm D130). In our publications we will combine data sets LFDP_C1treemap.txt and LFDP_C1TREEMAPa.txt to make Census 1 and to reconstruct the forest for stems >= 10 cm D130 at the time of Hurricane Hugo. We have divided the data into two separate files to ensure that when stem diameters are compared to future censuses the diameter data in LFDP_C1TREEMAPa.txt are not used to calculate growth rates. The last corrections to the Census 1 data were made in May 2001. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Princi
Adelie penguin area-wide breeding population census, 1991-2024
The fundamental long-term objective of the seabird component of the Palmer LTER (PAL) has been to identify and understand the mechanistic processes that regulate the mean fitness (population growth rate) of regional penguin populations. Since the inception of PAL, Adélie penguin populations have effectively collapsed, gentoo penguin populations have increased dramatically and chinstrap penguin populations have remained relatively stable. These trends are spatially and temporally coherent with regional warming and decreasing sea ice duration. Adélie penguins are an ice-obligate polar species whose life history is intimately linked to the presence of sea ice, while chinstrap and gentoo penguins are ice-intolerant species whose life histories evolved in the sub-Antarctic, where sea ice is a less permanent feature of the marine ecosystem. The PAL study region includes five main islands on which Adélie penguin colonies have historically occurred, with each island containing a different number of spatially segregated sub-colonies. These colonies are censused to determine the total number of nests and chicks produced each year, and breeding success. Diet samples are acquired to understand diet composition (e.g., krill, fish) and krill length-frequencies. In general, krill constitute the most important component of the summer diets by mass of these three penguin species, but changes in PAL krill abundances have exhibited no long-term trends and thus far, have failed to explain the divergent patterns in penguin populations evident in our time series. Chick fledging masses are recorded as a cumulative measure of climate, weather, diet, and parental influences on chick health at the end of the breeding season. These data have provided valuable insights into the marine and terrestrial factors that influence Adélie penguin population fitness. No data were collected during the 2021-2022 season due to the Palmer Station pier rebuild.
Research Data of the 2014 Census of Open Access Repositories in Germany, Austria and Switzerland
<p>The "2014 Census of Open Access Repositories in Germany, Austria and Switzerland” (2014 Census) is a study on the green open access landscape conducted in the course of a project seminar at the Berlin School of Library and Information Science (BSLIS) at Humboldt-Universität zu Berlin. The 2014 Census not only succeeds the "2012 Census of Open Access Repositories in Germany"[1] but enhances it by adding an online survey to the qualitative analysis of the open access repository websites and the automatic validation of its metadata. Like in 2012 the 2014 Census gives insights into the development of open access repositories and current trends in repository design being of substantial use to open access repository operators.</p> <p>This 2014 Census data set represents the data collected in three different ways:</p> <ul> <li>qualitative analysis of the open access repository websites</li> <li>automatic validation of the metadata via OAI-PMH using the DINI-Validator [2] </li> <li>online survey of repository operators</li> </ul> <p>As in 2012 [3] the data set is provided in XLSX as well as in CSV format. The columns represent the criteria and the rows represent the analyzed open access repositories. In the XLSX file the header row gives the definition of each criterion in English and German. In the CSV "content" file the header row is in English short terms. The respective English and German definition can be found in the CSV "readme" file.</p> <p> </p> <p>[1] Vierkant, P. (2013). 2012 Census of Open Access Repositories in Germany: Turning Perceived Knowledge Into Sound Understanding. <em>D-Lib Magazine</em>, 19. http://dx.doi.org/10.1045/november2013-vierkant </p> <p>[2] http://oanet.cms.hu-berlin.de/validator/pages/validation_dini.xhtml</p> <p>[3] Vierkant, Paul; Voigt, Michaela; Dupski, Jens; David, Sammy; Lösch, Mathias (2013): 2012 Census of Open Access Repositories in Germany. fig<strong>share</strong>. <br /> http://dx.doi.org/10.6084/m9.figshare.677099</p>
PARESv3 : PArish REgistry Survey − Historical Census Table Dataset (19th, 20th centuries) − France
<h2>PARES Dataset v3</h2> <p>PARES (PArish REcord Survey) contains<strong> 535 images of handwritten census tables</strong> for years ranging from around <strong>1650 A.D. until 1850 A.D.</strong>.They come from two <strong>French cities</strong>, Vic-sur-Seille (French department of Moselle) and Echevronne (French department of Côte d'Or). While they mention very ancient times, the documents are handwritten transcriptions of even older documents and are quite recent, copied from original documents during the 1950's and 1960's for demographic studies led by the INED in France (<em>Institut National des études démographiques</em> − National Institute for Demographic Studies). These copies were made by only a few different writers.</p> <p>In this updated version of the dataset, each table row has been carefully annotated and transcribed. Please note that for each row transcription, we have specified the attribute to which each value corresponds.</p> <p>We published a paper, <a href="https://link.springer.com/article/10.1007/s10032-025-00531-z">The PARES Database: Information Extraction over Historical Parish Records,</a> in which we better describe the dataset and the tasks it's possible to run on it.</p> <p> </p>
Census of the Ecosystem of Decentralized Autonomous Organizations
<p>The dataset includes data from various Decentralized Autonomous Organizations (DAOs) platforms, namely Aragon, DAOHaus, DAOstack, Realms, Snapshot and Tally. DAOs are a new form of self-governed online communities deployed in the blockchain. DAO members typically use <em>governance tokens</em> to participate in the DAO decision-making process, often through a voting system where members submit proposals and vote on them.</p> <p>The description of the methods used for the generation of data, for processing it and the quality-assurance procedures performed on the data can be found here:<br><a href="https://doi.org/10.1145/3589335.3651481">https://doi.org/10.1145/3589335.3651481</a></p> <ul> <li>Recommended citation for this dataset:<br>Peña-Calvin, A., Arroyo, J., Schwartz, A., & Hassan, S. (2024). Concentration of Power and Participation in Online Governance: the Ecosystem of Decentralized Autonomous Organizations. Companion Proceedings of the ACM Web Conference, 13–17, 2024, Singapore, doi: <a href="https://doi.org/10.1145/3589335.3651481">https://doi.org/10.1145/3589335.3651481</a></li> </ul> <p>The dataset comprises three CSV files: deployments.csv, proposals.csv, and votes.csv, each containing essential information regarding DAOs deployments, their<br>proposals, and the corresponding votes.</p> <ul> <li>The file deployments.csv provides insights into the general aspects of DAO deployments, including the platform it is deployed in, the number of proposals, unique voters, votes cast, and estimated voting power.</li> <li>The proposals.csv file contains comprehensive information about all proposals associated with the deployments, including their date, the number of votes they received, and the total voting power voters employed on that proposal.</li> <li>In votes.csv, data regarding the votes cast for the deployment proposals is recorded. It includes the voter's blockchain address, the vote's weight in voting power, and the day it was cast.</li> </ul>
Herschel‐ATLAS/GAMA: a census of dust in optically selected galaxies from stacking at submillimetre wavelengths
<p> </p> <p>Stacked sub-millimetre fluxes, luminosities, and derived dust masses and temperatures for GAMA galaxies...</p> <ul> <li>as a function of stellar mass, optical colour and redshift: StackResults_g-r_Mstar</li> <li>as a function of r-band absolute magnitude, optical colour and redshift: StackResults_g-r_Mr</li> </ul> <p>See readme files for full details.</p>
Censuses Podarcis pityusensis Ibiza 2022
<p>This database compiles detailed information on <em>Podarcis pityusensis</em> censuses conducted across various urban and peri-urban sites, covering its geographical range.The dataset includes records of abundance and habitat characteristics for each surveyed site. Additionally, anthropogenic factors like population density and level of urbanization, have been collected.</p>
A census of research software in 171 academic institutional repositories.
<p> A dataset of metadata for 171 UK academic institutional repositories, including a census of research software contained.</p> <table> <tbody> <tr> <td><strong>URL</strong></td> <td>The OAI url</td> </tr> <tr> <td><strong>id</strong></td> <td>CORE Identifier</td> </tr> <tr> <td><strong>openDoarId</strong></td> <td>Open DOAR identifier</td> </tr> <tr> <td><strong>name</strong></td> <td>Name of repository</td> </tr> <tr> <td><strong>Russell_member</strong></td> <td>If the university is a member of the Russell Group of research intensive universities</td> </tr> <tr> <td><strong>RSE_group</strong></td> <td>If an RSE group is present (based on Soc of RSE data)</td> </tr> <tr> <td><strong>email</strong></td> <td>Redacted</td> </tr> <tr> <td><strong>uri</strong></td> <td>Not used</td> </tr> <tr> <td><strong>uni_sld</strong></td> <td>Second level domain (the part of the url between . And .ac.uk</td> </tr> <tr> <td><strong>homepageUrl</strong></td> <td>University website</td> </tr> <tr> <td><strong>source</strong></td> <td>Not used</td> </tr> <tr> <td><strong>ris_software</strong></td> <td>the Research Information System software used</td> </tr> <tr> <td><strong>ris_software_enum</strong></td> <td>Resolve ris_software into similar types (e.g. Eprints 3, EPrints3.3.16 both equal eprints)</td> </tr> <tr> <td><strong>metadataFormat</strong></td> <td>the protocol used for metadata</td> </tr> <tr> <td><strong>createdDate</strong></td> <td>Repository creation date</td> </tr> <tr> <td><strong>location</strong></td> <td>location of university</td> </tr> <tr> <td><strong>logo</strong></td> <td>University logo (resolves in error)</td> </tr> <tr> <td><strong>type</strong></td> <td>Only = Repository for this dataset. Can be = journal etc.</td> </tr> <tr> <td><strong>stats</strong></td> <td>Not used</td> </tr> <tr> <td><strong>contains_software_set</strong></td> <td>Whether the OAI-PMH software set is present in the repository.</td> </tr> <tr> <td><strong>Num_sw_records</strong></td> <td>The response of the OAI-PMH query for software (erroneous as discussed in paper)</td> </tr> <tr> <td><strong>Error</strong></td> <td>The category of error returned by the experiment’s OAI-PMH queries (see paper)</td> </tr> <tr> <td><strong>Manual_Num_sw_records</strong></td> <td>The true amount of software contained in the repository as found by a manual exhaustive search of each university website</td> </tr> <tr> <td><strong>Category</strong></td> <td>Whether the repository (a) contains software; (b) can contain software, but doesn’t yet; (c) has no separate type of research output called software or similar</td> </tr> </tbody> </table>
1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History
<p><strong>Context. </strong>This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 million cells.</p> <p><strong>Content.</strong> The data published in this repository correspond to a first release, i.e. a diachronic slice of one register every 8 to 9 years. Unfortunately, the remaining data are currently under embargo. Their publication will take place as soon as possible, and at the latest by the end of 2023. In the meantime, the data presented here correspond to a large subset of 2,844 pages, which already allows to investigate most research hypotheses.</p> <p><strong>Description. </strong>The population censuses, digitized by the <a href="https://www.lausanne.ch/vie-pratique/culture/bibliotheques-et-archives/archives.html">Archives of the city of Lausanne</a>, continuously cover the evolution of the population in Lausanne throughout the 19th century, starting in 1805, with only one long interruption from 1814 to 1831. Highly detailed, they are an invaluable source for studying migration, economic and social history, and traces of cultural exchanges not only with Bern, but also with France and Italy. Indeed, the system of tracing family origin, specific to Switzerland, allows to follow the migratory movements of families long before the censuses appeared. The bourgeoisie is also an essential economic tracer. In addition, censuses extensively describe the organization of the social fabric into family nuclei, around which gravitate various boarders, workers, servants or apprentices, often living in the same apartment with the family.</p> <p><strong>Production. </strong>The structure and richness of censuses have also provided an opportunity to develop automatic methods for processing structured documents. The processing of censuses includes several steps, from the identification of text segments to the restructuring of information as digital tabular data, through Handwritten Text Recognition and the automatic segmentation of the structure using neural networks. Please note that the detailed extraction methodology, as well as the complete evaluation of performance and reliability is published in:</p> <ul> <li>Petitpierre R., Rappo L., Kramer M. (2023). <em>An end-to-end pipeline for historical censuses processing</em>. International Journal on Document Analysis and Recognition (IJDAR). doi: <a href="https://doi.org/10.1007/s10032-023-00428-9">10.1007/s10032-023-00428-9</a></li> </ul> <p><strong>Data structure.</strong> The data are structured in rows and columns, with each row corresponding to a household. Multiple entries in the same column for a single household are separated by vertical bars ⟨|⟩. The center point ⟨·⟩ indicates an empty entry. For some columns (e.g., street name, house number, owner name), an empty entry indicates that the last non-empty value should be carried over. The page number is in the last column.</p> <p><strong>Liability. </strong>The data presented here are not curated nor verified. They are the raw results of the extraction, the reliability of which was thoroughly assessed in the above-mentioned publication. We insist on the fact that for any reuse of this data for research purposes, the implementation of an appropriate methodology is necessary. This may typically include string distance heuristics, or statistical methodologies to deal with noise and uncertainty.</p>
Lausanne Historical Censuses Dataset HTR 35k
<p>This training dataset includes a total of 34,913 manually transcribed text segments. It is dedicated to the handwritten text recognition (HTR) of historical sources, typically tabular records, such as censuses. This dataset is based on a sample of 83 pages from the 19th century (1805-1898) censuses of Lausanne, Switzerland. The primary language of the documents is French, although many germanic names and toponyms are also found.</p> <p>The training data are formatted and provided on the model of the Bentham dataset. The format thus simply consists in a list of jpeg images, one per text segments, and their corresponding transcription, stored in a txt file. The file naming convention is 'yyyy-ppp-n', where 'y' stands for the year of publication of the census, and 'p' for the page number.</p> <p>The digitized documents are provided by the <a href="http://www.lausanne.ch/vie-pratique/culture/bibliotheques-et-archives/archives.html">Archives of the City of Lausanne</a>.</p> <p>Please note that the annotation and extraction methodology, as well as the complete evaluation of performance, including HTR benchmark and post-correction performance is published in :</p> <ul> <li>Petitpierre R., Rappo L., Kramer M. (2023). <em>An end-to-end pipeline for historical censuses processing</em>. International Journal on Document Analysis and Recognition (IJDAR). doi: <a href="https://doi.org/10.1007/s10032-023-00428-9">10.1007/s10032-023-00428-9</a></li> </ul> <p>Tabular dataset resulting from automatic extraction are also available on Zenodo :</p> <ul> <li>Petitpierre R., Rappo L., Kramer M., di Lenardo I. (2023). <em>1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History</em>. Zenodo. doi: <a href="https://doi.org/10.5281/zenodo.7711640">10.5281/zenodo.7711640</a></li> </ul>
Pulse Profiles and Times of Arrival Measurements from a Rotating Radio Transient Census with the Irish LOFAR station
<p>The reduced data produced as a part of a census of rotating radio transients (RRATs) with the Irish LOFAR station.</p> <p> </p> <p>This deposit contains:</p> <ul> <li>Metadata regarding observed data</li> <li>A copy of RFI-zapped, single pulse archives</li> <li>A copy of the time-flattened periodic emission archives</li> <li>A copy of the measured pulse times of arrival</li> <li>Ephemerides used and produced as a part of the work</li> </ul> <p>Additional data can be made available on request to the author.</p>
A dataset of metadata for UK academic institutional repositories, including a census of research software contained.
<p>A dataset of metadata for UK academic institutional repositories, including a census of research software contained.</p> <table> <tbody> <tr> <td><strong>URL</strong></td> <td>The OAI url</td> </tr> <tr> <td><strong>id</strong></td> <td>CORE Identifier</td> </tr> <tr> <td><strong>openDoarId</strong></td> <td>Open DOAR identifier</td> </tr> <tr> <td><strong>name</strong></td> <td>Name of repository</td> </tr> <tr> <td><strong>Russell_member</strong></td> <td>If the university is a member of the Russell Group of research intensive universities</td> </tr> <tr> <td><strong>RSE_group</strong></td> <td>If an RSE group is present (based on Soc of RSE data)</td> </tr> <tr> <td><strong>email</strong></td> <td>Redacted</td> </tr> <tr> <td><strong>uri</strong></td> <td>Not used</td> </tr> <tr> <td><strong>uni_sld</strong></td> <td>Second level domain (the part of the url between . And .ac.uk</td> </tr> <tr> <td><strong>homepageUrl</strong></td> <td>University website</td> </tr> <tr> <td><strong>source</strong></td> <td>Not used</td> </tr> <tr> <td><strong>ris_software</strong></td> <td>the Research Information System software used</td> </tr> <tr> <td><strong>ris_software_enum</strong></td> <td>Resolve ris_software into similar types (e.g. Eprints 3, EPrints3.3.16 both equal eprints)</td> </tr> <tr> <td><strong>metadataFormat</strong></td> <td>the protocol used for metadata</td> </tr> <tr> <td><strong>createdDate</strong></td> <td>Repository creation date</td> </tr> <tr> <td><strong>location</strong></td> <td>location of university</td> </tr> <tr> <td><strong>logo</strong></td> <td>University logo (resolves in error)</td> </tr> <tr> <td><strong>type</strong></td> <td>Only = Repository for this dataset. Can be = journal etc.</td> </tr> <tr> <td><strong>stats</strong></td> <td>Not used</td> </tr> <tr> <td><strong>contains_software_set</strong></td> <td>Whether the OAI-PMH software set is present in the repository.</td> </tr> <tr> <td><strong>Num_sw_records</strong></td> <td>The response of the OAI-PMH query for software (erroneous as discussed in paper)</td> </tr> <tr> <td><strong>Error</strong></td> <td>The category of error returned by the experiment’s OAI-PMH queries (see paper)</td> </tr> <tr> <td><strong>Manual_Num_sw_records</strong></td> <td>The true amount of software contained in the repository as found by a manual exhaustive search of each university website</td> </tr> <tr> <td><strong>Category</strong></td> <td>Whether the repository (a) contains software; (b) can contain software, but doesn’t yet; (c) has no separate type of research output called software or similar</td> </tr> </tbody> </table> <p> </p>
Itasca Biological Station Bear Paw Point Breeding Bird Census, MN (1979-2025)
This dataset is part of an ongoing effort that began in 1979 at the University of Minnesota Itasca Biological Station to conduct an annual census of breeding bird territories on Bear Paw Point every spring. Students enrolled in Field Ornithology used an established 50x50 meter grid (11.5 hectares total plot size) and walked gridlines, identifying bird songs and estimating the number of singing males heard to determine the number of breeding territories for different species present on Bear Paw Point.
Baltimore Ecosystem Study: Estimates of population in focal watersheds based on 2010 census
This dataset includes population estimates for eight focal sub-watersheds in the Baltimore Ecosystem Study based on the proportion of 2010 census blocks located within the watershed. These data can facilitate per capita calculations of watershed fluxes.
Point-count bird censusing: bird abundance and diversity in CAP LTER Phoenix Area Social Survey neighborhoods throughout the greater Phoenix metropolitan area, 2006-2016
The Phoenix Area Social Survey (PASS) parallels the Ecological Survey of Central Arizona (formerly, Survey 200) as a long-term monitoring program of the CAP LTER. Every five years, the PASS research team surveys households in selected neighborhoods in the metropolitan Phoenix area to better understand perceptions, values, and behaviors of several key environmental issues, including water conservation, urban growth, air pollution, land conservation, biodiversity and urban climate change, as well as perceptions about their neighborhoods. The survey was piloted in 2001-2002 in eight neighborhoods in Phoenix with 302 respondents, and grew to over 40 neighborhoods and 800 households in 2005. Bird survey locations were established in each of the PASS neighborhoods, colocated as much as possible with the corresponding ESCA survey location in the neighborhood. Bird surveys were conducted biannualy (spring, winter) approximately the year of and the year after each PASS. In a given season, each bird survey location is visited independently by three birders who count all birds seen or heard within a 15-minute window.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.