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747 results for “Open Data”

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zenodo36/100

IPBES Invasive Alien Species Assessment in Linked Open Data format

This dataset contains the Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services in linked open data format. The structure of the file follows the IPBES ontology version 06: <a href="https://github.com/IPBES-Data/IPBES_Ontology">https://github.com/IPBES-Data/IPBES_Ontology</a> The report is published in 2023 and consists of 6 chapters and a Summary for Policy Makers. For more information about the report, see: <a href="https://www.ipbes.net/ias" rel="nofollow">https://www.ipbes.net/ias</a> For any questions and enquiries, please contact the IPBES Data and Knowledge Unit <a href="mailto:aidin.niamir@senckenberg.de">aidin.niamir@senckenberg.de</a>

opencc-by-4.0Apr 2024View details →

zenodo36/100

IPBES Values Assessment in Linked Open Data format

This dataset contains the Methodological Assessment Report on the Diverse Values and Valuation of Nature of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services in linked open data format. The structure of the file follows the IPBES ontology version 06: <a href="https://github.com/IPBES-Data/IPBES_Ontology">https://github.com/IPBES-Data/IPBES_Ontology</a> The report is published in 2022 and consists of 6 chapters and a Summary for Policy Makers. For more information about the report, see: <a href="https://www.ipbes.net/the-values-assessment">https://www.ipbes.net/the-values-assessment</a> For any questions and enquiries, please contact the IPBES Data and Knowledge Unit <a href="mailto:aidin.niamir@senckenberg.de">aidin.niamir@senckenberg.de</a>

opencc-by-4.0Apr 2024View details →

zenodo36/100

Dataset: A continuous open source data collection platform for architectural technical debt assessment

The dataset and replication package of the study "A continuous open source data collection platform for architectural technical debt assessment".   Abstract Architectural decisions are the most important source of technical debt.  In recent years, researchers spent an increasing amount of effort investigating this specific category of technical debt, with quantitative methods, and in particular static analysis, being the most common approach to investigate such a topic.   However, quantitative studies are susceptible, to varying degrees, to external validity threats, which hinder the generalisation of their findings. In response to this concern, researchers strive to expand the scope of their study by incorporating a larger number of projects into their analyses. This practice is typically executed on a case-by-case basis, necessitating substantial data collection efforts that have to be repeated for each new study.   To address this issue, this paper presents our initial attempt at tackling this problem and enabling researchers to study architectural smells at large scale, a well-known indicator of architectural technical debt. Specifically, we introduce a novel approach to data collection pipeline that leverages Apache Airflow to continuously generate up-to-date, large-scale datasets using Arcan, a tool for architectural smells detection (or any other tool). Finally, we present the publicly-available dataset resulting from the first three months of execution of the pipeline, that includes over 30,000 analysed commits and releases from over 10,000 open source GitHub projects written in 5 different programming languages and amounting to over a billion of lines of code analysed.

opencc-by-4.0Oct 2023View details →

dryad36/100

Opening the museum's vault: Historical field records preserve reliable ecological data

Museum specimens have long served as foundational data sources for ecological, evolutionary, and environmental research. Continued reimagining of museum collections is now also generating new types of data associated with, but beyond physical specimens, a concept known as "extended specimens". Field notes penned by generations of naturalists contain first-hand ecological observations associated with museum collections and comprise a form of extended specimens with the potential to provide novel ecological data spanning broad geographic and temporal scales. Despite their data-yielding potential, however, field notes remain underutilized in research due to their heterogeneous, unstandardized, and qualitative nature. We introduce an approach for transforming descriptive ecological notes into quantitative data suitable for statistical analysis. Tests with simulated and real-world published data show that field notes and our transformation approach retain reliable quantitative ecological information under a range of sample sizes and evolutionary scenarios. Unlocking the wealth of data contained within field records could facilitate investigations into the ecology of clades whose diversity, distribution, or other demographic features present challenges to traditional ecological studies, improve our understanding of long-term environmental and evolutionary change, and enhance predictions of future change.

opencc-zeroOct 2023View details →

zenodo36/100

Direct observation of chirality-induced spin selectivity in electron donor–acceptor molecules. Open data set

Data supporting the original figures 2 and 4 of the related publication.

opencc-by-4.0Nov 2023View details →

zenodo36/100

Open Data, Open Code, Open Infrastructure Schematic Diagram

A schematic diagram of how social workflows, technical workflows, and project governance interact with the open data, open code, and open infrastructure (O3)

opencc-by-4.0Nov 2023View details →

zenodo36/100

Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects. Dataset

Tables containing the information about the projects funded by the Spanish AEI and publications acknowledging funding from Funder Registry. Both datasets where used in our publication: Public funding accountability: a linked open data-based methodology for analysing the scientific productivity and influence of funded projects.

opencc-by-nc-sa-4.0Mar 2023View details →

zenodo36/100

The outdated open-data

Dataset and experimental results. Details specified in README.txt

opencc-by-4.0Nov 2023View details →

zenodo36/100

Graded Incremental Test Data (Cycling, Running, Kayaking, Rowing): an open access dataset

Section 1:  Introduction   Brief overview of dataset contents: <ul> <li>Current database contains anonymised data collected during exercise testing services performed on male and female participants (cycling, rowing, kayaking and running) provided by the Human Performance Laboratory, School of Medicine, Trinity College Dublin, Dublin 2, Ireland.   </li> <li>835 graded incremental exercise test files (285 cycling, 266 rowing / kayaking, 284 running)</li> <li>Description file with each row representing a test file - COLUMNS: file name (AXXX), sport (cycling, running, rowing or kayaking)</li> <li>Anthropometric data of participants by sport (age, gender, height, body mass, BMI, skinfold thickness,% body fat, lean body mass and haematological data; namely, haemoglobin concentration (Hb), haematocrit (Hct), red blood cell (RBC) count and white blood cell (WBC) count )</li> <li>Test data (HR, VO2 and lactate data) at rest and across a range of exercise intensities</li> <li>Derived physiological indices quantifying each individual’s endurance profile</li> </ul>   Following a request from athletes seeking assessment by phone or e-mail the test protocol, risks, benefits and test and medical requirements, were explained verbally or by return e-mail. Subsequently, an appointment for an exercise assessment was arranged following the regulatory reflection period (7 days). Following this regulatory period each participant’s verbal consent was obtained pre-test, for participants under 18 years of age parent / guardian consent was obtained in writing. Ethics approval was obtained from the Faculty of Health Sciences ethics committee and all testing procedures were performed in compliance with Declaration of Helsinki guidelines.   All consenting participants were required to attend the laboratory on one occasion in a rested, carbohydrate loaded and well-hydrated state, and for male participants’ clean shaven in the facial region. All participants underwent a pre-test medical examination, including assessment of resting blood pressure, pulmonary function testing and haematological (Coulter Counter Act Diff, Beckmann Coulter, CA,US) review performed by a qualified medical doctor prior to exercise testing. Any person presenting with any cardiac abnormalities, respiratory difficulties, symptoms of cold or influenza, musculoskeletal injury that could impair performance, diabetes, hypertension, metabolic disorders, or any other contra-indicatory symptoms were excluded. In addition, participants completed a medical questionnaire detailing training history, previous personal and family health abnormalities, recent illness or injury, menstrual status for female participants, as well as details of recent travel and current vaccination status, and current medications, supplements and allergies. Barefoot height in metre (Holtain, Crymych, UK), body mass (counter balanced scales) in kilogram (Seca, Hamburg, Germany) and skinfold thickness in millimetre using a Harpenden skinfold caliper (Bath International, West Sussex, UK) were recorded pre-exercise.   Section 2: Testing protocols   2.1: Cycling   A continuous graded incremental exercise test (GxT) to volitional exhaustion was performed on an electromagnetically braked cycle ergometer (Lode Excalibur Sport, Groningen, The Netherlands). Participants initially identified a cycling position in which they were most comfortable by adjusting saddle height, saddle fore-aft position relative to the crank axis, saddle to handlebar distance and handlebar height. Participant’s feet were secured to the ergometer using their own cycling shoes with cleats and accompanying pedals. The protocol commenced with a 15-min warm-up at a workload of 120 Watt (W), followed by a 10-min rest. The GxT began with a 3-min stationary phase for resting data collection, followed by an active phase commencing at a workload of 100 or 120 W for female and male participants, respectively, and subsequently increasing by a 20, 30 or  40 W incremental increase every 3-min depending on gender and current competition category. During assessment participants maintained a constant self-selected cadence chosen during their warm-up (permitted window was 5 rev.min−1 within a permitted absolute range of 75 to 95 rev.min−1) and the test was terminated when a participant was no longer able to maintain a constant cadence.   Heart rate (HR) data were recorded continuously by radio-telemetry using a Cosmed HR monitor (Cosmed, Rome, Italy). During the test, blood samples were collected from the middle finger of the right hand at the end of the second minute of each 3-min interval. The fingertip was cleaned to remove any sweat or blood and lanced using a long point sterile lancet (Braun, Melsungen, Germany). The blood sample was collected into a heparinised capillary tube (Brand, Wertheim, Germany) by holding the tube horizontal to the droplet and allowing transfer by capillary action. Subsequently, a 25μL aliquot of whole blood was drawn from the capillary tube using a YSI syringepet (YSI, OH, USA) and added into the chamber of a YSI 1500 Sport lactate analyser (YSI, OH, USA) for determination of non-lysed [Lac] in mmol.L−1. The lactate analyser was calibrated to the manufacturer’s requirements (± 0.05 mmol.L−1) before each test using a standard solution (YSI, OH, USA) of known concentration (5 mmol.L−1) and analyser linearity was confirmed using either a 15 or 30 mmol.L-1 standard solution (YSI, OH, USA).   Gas exchange variables including respiration rate (Rf in breaths.min-1), minute ventilation (VE in L.min-1), oxygen consumption (VO2 in L.min-1 and in mL.kg-1.min-1) and carbon dioxide production (VCO2 in L.min-1), were measured on a breath-by-breath basis throughout the test, using a cardiopulmonary exercise testing unit (CPET) and an associated software package (Cosmed, Rome, Italy). Participants wore a face mask (Hans Rudolf, KA, USA) which was connected to the CPET unit. The metabolic unit was calibrated prior to each test using ambient air and an alpha certified gas mixture containing 16% O2, 5% CO2 and 79% N2 (Cosmed, Rome, Italy). Volume calibration was performed using a 3L gas calibration syringe (Cosmed, Rome, Italy). Barometric pressure recorded by the CPET was confirmed by recording barometric pressure using a laboratory grade barometer.   Following testing mean HR and mean VO2 data at rest and during each exercise increment were computed and tabulated over the final minute of each 3-min interval. A graphical plot of [Lac], mean VO2 and mean HR versus cycling workload was constructed and analysed to quantify physiological endurance indices, see Data Analysis section. Data for VO2 peak in L.min-1 (absolute) and in mL.kg-1.min-1 (relative) and VE peak in L.min-1 were reported as the peak data recorded over any 10 consecutive breaths recorded during the last minute of the final exercise increment.   2.2:       Running protocol   A continuous graded incremental exercise test (GxT) to volitional exhaustion was performed on a motorised treadmill (Powerjog, Birmingham, UK). The running protocol, performed at a gradient of 0%, commenced with a 15-min warm-up at a velocity (km.h-1) which was lower than the participant’s reported typical weekly long run (>60 min) on-road training velocity. Subsequently, the warm-up was followed by a 10 minute rest / dynamic stretching phase. From a safety perspective during all running GxT participants wore a suspended lightweight safety harness to minimise any potential falls risk. The GxT began with a 3-min stationary phase for resting data collection, followed by an active phase commencing at a sub-maximal running velocity which was lower than the participant’s reported typical weekly long run (>60 min) on-road training velocity, and subsequently increased by ≥ 1 km.h-1 every 3-min depending on gender and current competition category. The test was terminated when a participant was no longer able to maintain the imposed treadmill.   Measurement variables, equipment and pre-test calibration procedures, timing and procedure for measurement of selected variables and subsequent data analysis were as outlined in Section 2.1.   2.3:       Rowing / kayaking protocol   A discontinuous graded incremental exercise test (GxT) to volitional exhaustion was performed on a Concept 2C rowing ergometer (Concept, VA, US) in rowers or a Dansprint kayak ergometer (Dansprint, Hvidovre, Denmark) in flat-water kayakers. The protocol commenced with a 15-min low-intensity warm-up at a workload (W) dependent on gender, sport and competition category, followed by a 10-min rest. For rowing the flywheel damping (120, 125 or 130W) was set dependent on gender and competition category. For kayaking the bungee cord tension was adjusted by individual participants to suit their requirements. A discontinuous protocol of 3-min exercise at a targeted load followed by a 1-min rest phase to facilitate stationary earlobe capillary blood sample collection and resetting of ergometer display (Dansprint ergometer) was used. The GxT began with a 3-min stationary phase for resting data collection, followed by an active phase commencing at a sub-maximal load 80 to 120 W for rowing, 50 to 90 W for kayaking and subsequently increased by 20,30 or 40 W every 3-min depending on gender, sport and current competition category. The test was terminated when a participant was no longer able to maintain the targeted workload.  Measurement variables, equipment and pre-test calibration procedures, timing and procedure for measurement of selected variables and subsequent data analysis were as outlined in Section 2.1.   3.1:       Data analysis   Constructed graphical plots (HR, VO2 and [Lac] versus load / velocity) were analysed to quantify the following; load / velocity at TLac, HR at TLac, [Lac] at TLac, % of VO2 peak at TLac, % of HRmax at TLac, load / velocity and HR at a nominal [Lac] of 2 mmol.L-1,  load / velocity, VO2 and [Lac} at a nominal HR of 160 beats.min-1. Load at TLac was determined using segmental regression analysis. Two linear segments were plotted that minimised the squared sum of the residuals between the plotted points and best fit lines. The intersection of these the two linear segments was defined as the relevant breakpoint or threshold, (Raleigh et al. 2018. Int J Exerc Sci, 11, 391-403.   4.1:       Terms of Use   The attached database is provided as a research or educational asset / tool for coach, athlete and exercise science / exercise medicine education and usage only.

opencc-by-4.0Mar 2022View details →

zenodo36/100

Data from: The maintenance and emergence of diversity promotes open-ended evolution in a prebiotic context

This data was collected during the study entitled “The maintenance and emergence of diversity promotes open-ended evolution in a prebiotic context."   We explored how selective contexts shape the evolution of innovation, using in vitro selection with single-stranded DNA (ssDNA) as an empirical model for pre-cellular evolution. During this selection regime, a diverse pool of 76-bp ssDNA (consisting of a random 40-nt region, flanked by 18-nt primer binding sites) was incubated with a target substrate, during which sequences were able to bind to the substrate. Following incubation, unbound sequences were discarded, while bound sequences were partitioned and amplified via PCR and used in subsequent rounds of selection.    Our experimental design consisted of 8 cycles of selection with either streptavidin-coated magnetic beads or yeast cells (Kluyveromyces lactis) as the binding substrate. We also included two variable selection regimes, where four rounds of selection were completed with one substrate before switching to the other target for the remaining four rounds (3 replicate populations per treatment). All replicates from rounds 1, 4, 7, and 8 were purified and submitted for next-generation sequencing (Illumina NovaSeq S4 2x150-bp lane), along with the random starting library. Sequencing generated a mean of 29,741,261 pair-end reads per sample, which were assembled and normalized to ~100,000 reads per sample used for analysis, which are included here.   The file names are organized in the following format: Selection Treatment_Round of Selection_Replicate #. For example, “Beads_R1_1” indicates a population that was selected with beads as the binding substrate following Round 1 of selection, replicate population 1 (out of 3 replicates). Scripts used to list contigs (EditFastas.l) and measure the frequencies of each sequence (CountSeqs.l ) are also included.

opencc-by-4.0Mar 2024View details →

zenodo36/100

GloHydroRes - a global dataset combining open-source hydropower plant and reservoir data

<div> <div> <div> <div> </div> </div> </div> </div> <div> <div> <div> <div> <div> <div> Analyzing the impacts of drought and climate change on hydropower requires detailed data not only on hydropower attributes such as plant type, head, and installed capacity, but also on reservoir characteristics like area, depth, and volume. Current open-source hydropower datasets typically lack information on reservoirs, while reservoir datasets often omit hydropower details. GloHydroRes is a global dataset that integrates open-source hydropower and reservoir data, offering 29 attributes, including key information such as installed capacity, plant type, dam height, reservoir depth, area, volume, and river name. Overall, GloHydroRes provides data on 7,775 hydropower plants across 128 countries. </div> </div> </div> </div> <div> <div> <div> </div> </div> </div> </div> </div>

opencc-by-4.0Sep 2024View details →

zenodo36/100

Opening education in the MENA region: In-depth interviews and Focus Group data with experts in open education in Egypt, Jordan, Lebanon, Morocco and Palestine.

The two data sets presented here are part of a study which aimed at identifying cultural barriers in the adoption of open education in higher education in the Middle East, specifically in Egypt, Jordan, Lebanon, Morocco and Palestine. This study was conducted in the context of OpenMed – “Opening up Education in South-Mediterranean countries” (<a href="https://openmedproject.eu/">https://openmedproject.eu/</a>), an international cooperation project co-funded by the <a href="http://eacea.ec.europa.eu/erasmus-plus/actions/key-action-2-cooperation-for-innovation-and-exchange-good-practices/capacity-0_en">Erasmus+ Capacity Building in Higher Education programme</a> of the European Union during the period 15 October 2015 – 14 October 2018. The first document presents the transcripts of in-depth interviews (N=7) conducted in February 2018 through Skype with open education experts, from seven universities: namely: Alexandria University (Egypt), Cairo University (Egypt), German Jordanian University (Jordan), Princess Sumaya University of Technology (Jordan), Notre Dame University (Lebanon), Birzeit University (Palestine) and An-Najah University (Palestine). The second document is a transcript of a focus group which took place in Agadir (Morocco) in May 2018, with open education experts from eight universities: Alexandria University (Egypt), Cadi Ayyad University (Morocco), Cairo University (Egypt), German Jordanian University (Jordan), Ibn Zohr University (Morocco), Princess Sumaya University of Technology (Jordan), and An-Najah University (Palestine). Both the interviews and the focus group were conducted in English, digitally recorded and transcribed verbatim. For a rationale on the cultural factors impacting adoption of open educational practices see: <ul> <li>Maya-Jariego, I. (2017). Localising Open Educational Resources and Massive Open Online Courses. In F. Nascimbeni, D. Burgos, A. Vetrò, E. Bassi, D. Villar-Onrubia, K. Winpenny, I. Maya Jariego, O. Mimi, R. Qasim, & C. Stefanelli (Eds.), Open Education: fundamentals and approaches. A learning journey opening up teaching in higher education. Erasmus+ Programme of the European Union.</li> </ul> Project n.: 561651-EPP-1-2015-1-IT-EPPKA2-CBHE-JP

opencc-by-4.0Jun 2018View details →

zenodo36/100

Global Socio-Economic and Environmental data for PyPSA-Earth: An Open Optimisation Model of the Earth Energy System.

PyPSA-Earth is an open model dataset of the global power system at different network levels that cover our Earth. The African model can be built using the code provided at <a href="https://github.com/pypsa-meets-africa/pypsa-africa">https://github.com/pypsa-meets-africa/pypsa-africa</a>. Other regions follow soon under the same code base. Since the GitHub codebase is not suited for handling large changing files, we provide here separate data bundles and cutouts to be downloaded and extracted as noted in the <a href="https://pypsa-meets-africa.readthedocs.io/en/latest/index.html">documentation</a> The below-provided data files contain various open data for improving energy system modelling decisions. A thorough description with license restrictions will follow soon.

opencc-by-4.0Jan 2022View details →

zenodo36/100

Even when you know it is a placebo, you experience less sadness: First evidence from an experimental open-label placebo investigation (Open Data and Open Materials)

Open Data and Open Materials of: Even when you know it is a placebo, you experience less sadness: First evidence from an experimental open-label placebo investigation. Journal of Affective Disorders. Background: Recent studies demonstrate substantial effects of deceptive placebo on experimentally induced sadness, even on autonomic activity. Whether deception is necessary, remains to be elucidated. We investigated the effect of an open-label placebo (OLP) treatment, i.e. an openly administered placebo delivered with a convincing rationale for its sadness-protecting effect. Methods: Eighty-four healthy females were randomized to an OLP group or a no-treatment control group. All participants received the same detailed information about the OLP effect, only the OLP group received an OLP nasal spray. Before and after the OLP intervention, participants underwent a sad mood induction procedure combining self-deprecating statements (Velten's method) and sad music. Sadness was assessed by the Positive and Negative Affect Schedule (PANAS-X). Autonomic activity was measured continuously. Results: Participants in the OLP group reported a significantly attenuated increase in sadness upon mood induction and less sadness after induction compared to the control group (d = 0.79). Regardless of intervention, heart rate decreased during mood inductions with a more pronounced deceleration in the second mood induction. Limitations: Generalizability is limited due to the selective sample and the reliance on an experimentally controlled mood induction. Conclusion: OLP treatment had a beneficial effect on perceived sadness, at least at the subjective level. Hence, deception may not necessarily be required for placebos to modulate experienced sad mood. Investigating the beneficial effects of OLP in (sub-)clinical samples would seem a promising and required next step towards a clinical use of placebo-associated positive treatment expectations.

opencc-by-4.0Feb 2022View details →

dryad36/100

Open data for spatial public health research

Background Preventive and health-promoting policies can guide (place and space-specific) factors influencing human health, such as the physical and social environment. Required is data that can lead to a more nuanced decision-making process and identify both, existing and future challenges. Along with the rise of new technologies, and thus the multiple opportunities to use and process data, new options have emerged to measure and monitor factors that affect health. Thus, in recent years, several gateways for open data (including governmental and geospatial data) became available. At present, an increasing number of research institutions as well as (state and private) companies and citizens' initiatives provide data. However, there is a lack of overviews covering the range of such offerings regarding health. In particular, for geographically differentiated analyses, there are challenges related to data availability at different spatial levels and the growing number of data providers. Objectives To provide an overview of open data resources available in the context of space and health to date. It also describes the technical and legal conditions for using open data Results An up-to-date summary of results including information on relevant data access and terms of use is provided along with a web visualization. All data is available for further use under an open license.

opencc-zeroFeb 2022View details →

zenodo36/100

TRINITY open access data repository data set 2 by Budapest University of Technology and Economics

Horizon 2020 programme supports access to and reuse of research data generated by Horizon 2020 projects through the Open Research Data Pilot (ORDP). To support the validation of scientific results, the pilot focuses on providing access to data needed to validate the scientific results. There are several types of such data, e.g. machine learning data sets, models, measurements, statistical results of experiments, survey outcomes, etc. This deliverable summarizes the data that are expected to be collected in the course of the project and where and how they are stored. The aspect of providing open access to research data (as required by the European Commission’s Open Research Data Pilot, <a href="https://www.openaire.eu/what-is-the-open-research-data-pilot">https://www.openaire.eu/what-is-the-open-research-data-pilot</a>) is addressed in Section 3. Finally, in Section 4 we describe the data sets that were or are expected to be generated within the TRINITY projects and made freely available.

opencc-by-3.0Mar 2022View details →

zenodo36/100

TRINITY open access data repository by Budapest University of Technology and Economics

opencc-by-3.0Mar 2022View details →

zenodo36/100

Open data repository, An et al., Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images

Open data repository of journal article "Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images" by Jeehye An et al. At time of publication of this dataset, the manuscript is still under revision. This dataset contains mouse T2 weighted MRI data, and manually and automated segmented ischemic stroke lesion masks for developing and evaluating a deep learning-based automated lesion segmentation. All files are in NIFTI format.

opencc-by-4.0Mar 2022View details →

zenodo36/100

Analytics, Visualisation and Machine Learning of General Practitioner Prescribing using Open Health Data

Open Prescription data used in Postgraduate project into Northern Ireland General Practice prescribing.

opencc-by-4.0Apr 2022View details →

dryad36/100

Data from: Building communities of teaching practice and data-driven open education resources with NEON faculty mentoring networks

With the growing availability and accessibility of big data in ecology, we face an urgent need to train the next generation of scientists in data science practices and tools. One of the biggest barriers for implementing a data-driven curriculum in undergraduate classrooms is the lack of training and support for educators to develop their own skills and time to incorporate these principles into existing courses or develop new ones. Alongside the research goals of the National Ecological Observatory Network (NEON), providing education and training are key components for building a community of scientists and users equipped to utilize large-scale ecological and environmental data. To address this need, the NEON Data Education Fellows program formed as a collaborative Faculty Mentoring Network (FMN) between scientists from NEON and university faculty interested in using NEON data and resources in their ecology classrooms. Like other FMNs, this group has two main goals: 1) to provide tools, resources, and support for faculty interested in developing data-driven curriculum, and (2) to make teaching materials that have been implemented and tested in the classroom available as open educational resources for other educators. We hosted this program using an open education and collaboration platform from the Quantitative Undergraduate Biology Education and Synthesis (QUBES) project. Here, we share lessons learned from facilitating five FMN cohorts and emphasize the successes, pitfalls, and opportunities for developing open education resources through community-driven collaborations.

opencc-zeroMay 2022View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record