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.
506
datasets available to search
ShareScore release 0.7.1
Dataset results
506 results for “decision-making”
Resource allocation underlies parental decision-making during incubation in the Manx shearwater
Open the record for dataset details and reuse information.
Data from: Distinct developmental trajectories for risky and impulsive decision-making in chimpanzees
Open the record for dataset details and reuse information.
Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
Open the record for dataset details and reuse information.
Data from: Anthropogenic noise exposure over development increases baseline auditory activity and decision-making time in adult crickets
Open the record for dataset details and reuse information.
Code and data for: The evolution of ontogenetic decision-making in the wood of a clade of tropical plants
Open the record for dataset details and reuse information.
A decision-making framework to maximize the evolutionary potential of populations: Genetic and genomic insights from the common midwife toad (Alytes obstetricans) at its range limits
Open the record for dataset details and reuse information.
Macrosystems EDDIE Module 8: Using Ecological Forecasts to Guide Decision-Making (Instructor Materials)
Because of increased variability in populations, communities, and ecosystems due to land use and climate change, there is a pressing need to know the future state of ecological systems across space and time. Ecological forecasting is an emerging approach which provides an estimate of the future state of an ecological system with uncertainty, allowing society to preemptively prepare for fluctuations in important ecosystem services. However, forecasts must be effectively designed and communicated to those who need them to make decisions in order to realize their potential for protecting natural resources. In this module, students will explore real ecological forecast visualizations, identify ways to represent uncertainty, make management decisions using forecast visualizations, and learn decision support techniques. Lastly, students customize a forecast visualization for a specific stakeholder's decision needs. The overarching goal of this module is for students to understand how forecasts are connected to decision-making of stakeholders, or the managers, policy-makers, and other members of society who use forecasts to inform decision-making. The A-B-C structure of this module makes it flexible and adaptable to a range of student levels and course structures. This EDI data package contains instructional materials and the files necessary to teach the module. Readers are referred to the Zenodo data package (Woelmer et al. 2022; DOI: 10.5281/zenodo.7074674) for the R Shiny application code needed to run the module locally.
Heat and water loss vs shelter: a dilemma in thermoregulatory decision-making for a retreat-dwelling nocturnal gecko
<p>Understanding the interaction between upper voluntary thermal limit (VT<sub>max</sub>) and water loss may aid in predicting responses of ectotherms to increasing temperatures within microhabitats. However, the temperature (VT<sub>max</sub>) at which climate heating will force cool-climate, nocturnal lizards to abandon daytime retreats remains poorly known. Here, we developed a new laboratory protocol for determining VT<sub>max</sub> in the retreat-dwelling, viviparous <i>Woodworthia</i> Otago/Southland gecko, based on escape behaviour (abandonment of heated retreat). We compared the body temperature (T<sub>b</sub>) at VT<sub>max</sub>, and duration of heating, between two source groups with different thermal histories, and among three reproductive groups. We also examined continuous changes in T<sub>b</sub> (via an attached biologger) and total evaporative water loss (EWL) during heating. In the field, we measured T<sub>b</sub> and microhabitat thermal profiles to establish whether geckos reach VT<sub>max</sub> in nature. We found that VT<sub>max</sub> and duration of heating varied between source groups (and thus potentially with prior thermal experience), but not among reproductive groups. Moreover, geckos reached a peak temperature slightly higher than VT<sub>max</sub> before abandoning the retreat. Total EWL increased with increasing VT<sub>max</sub> and with the duration of heating. In the field, pregnant geckos with attached biologgers reached VT<sub>max</sub> temperature, and temperatures of some separately monitored microhabitats exceeded VT<sub>max</sub> in hot weather implying that some retreats must be abandoned to avoid overheating. Our results suggest that cool-climate nocturnal lizards that inhabit daytime retreats may abandon retreats more frequently if climate warming persists, implying a trade-off between retention of originally occupied shelter and ongoing water loss due to overheating.</p>
Data from: Incorporating herders' knowledge and ecosystem-based adaptation strategies in local decision-making
<p class="CxSpFirst"> 1. Ecosystem-based adaptation (EbA) relies upon the capacity of ecosystems to buffer communities against the adverse impacts of climate change. Maintaining ecosystems that deliver critical services to communities can also provide co-benefits beyond adaptation, such as climate mitigation and protection of biological diversity and livelihoods. EbA has to a limited extent drawn upon indigenous-and local knowledge (ILK) for defining critical services and for implementing EbA in decision-making. This is a paradox given that the primary focus of EbA is to enable communities to adapt to climate change.<br> 2. The purpose of this study was to elucidate EbA strategies that take into account the knowledge of Sámi reindeer herders about pastures in tundra regions. We first examined what constitutes critical services as perceived by Sámi reindeer herders through a synthesis of data and literature. We thereafter used content analysis of 91 land use cases from 2010-2018 to investigate to what extent the herders' knowledge and maps over seasonal pastures and migratory routes are used in local decision-making. Finally, we propose EbA strategies of relevance to Sámi communities and pastoral communities elsewhere.<br> 3. Our analysis revealed that reindeer herders and organizations representing their interests perceived threats from green energy development, tourism, recreation, public road construction and powerlines. These threats included the loss of key habitats and the loss of connectivity for migration between seasonal pastures. Herders' knowledge is incorporated through participatory tools to protect the ecosystems and services crucial for herders, but multiple competing land uses result in incremental loss of pastures regardless. <br> 4. Synthesis and application. Pastoralists need access to diverse resources on seasonal pastures and the ability to move between pastures when snow, ice, rainfall and the timing of critical service supplies changes. Drawing on herders' knowledge to elicit EbA strategies is vital for buffering the adverse effects of climate change. EbA that incorporates indigenous perspectives cannot purely rely on co-benefit approaches. Fundamental trade-offs exist between adaptation needs and other land uses, such as infrastructure, tourism and green energy development</p>
Data from: Statistically testing the role of individual learning and decision-making in trapline foraging
Trapline foraging, a behavior consisting of repeated visitation to spatially fixed resources in a predictable sequence, has been observed over diverse taxa and is important ecologically for efficient resource gathering. Despite this, few null models exist to test the significance of suspected traplines, particularly for studies interested in the role of individual decision-making in the formation of traplines versus the role of resource layouts and random movement patterns. Here we present a spatially explicit, individual-based null model, which may be used to test whether resource layout and realistic forager movement may account for sequence repeats in suspected traplines. In our model, we generate resource visitation sequences by modeling a forager without spatial memory using a random walk to discover and visit spatially-fixed resources. We quantify traplining using Determinism, a metric derived from recurrence quantification analysis. Using both simulated and empirical bee foraging data, we compared our model with two existing null models—a completely random model and a sample randomization model. The former creates null sequences by randomly selecting available resources, while the latter randomizes the order of visits in observed sequences. We found that our model has a higher propensity of being (correctly) rejected than a sample randomization model for trapliners, and a lower propensity of being (incorrectly) rejected for non-trapliners compared to a completely random model. The use of a spatially explicit individual-based null model to test the statistical significance of patterns in empirical data is a novel approach that may be useful for other spatial and individual-based processes.
Qualitative raw data and behavioral analysis for understanding VMMC policy decision-making
<p>Faced with declining donor funding for HIV, low- and middle-income countries must identify efficient and cost-effective ways to integrate HIV prevention programs into public health systems for long-term sustainability. In Zambia, donor support to the voluntary medical male circumcision (VMMC) program, which previously funded non-governmental organizations as implementing partners, is increasingly being directed through government structures instead. We developed a framework to understand how the behaviors of individual decision-makers within the government could be barriers to this transition. We interviewed key stakeholders from the national, provincial, and district levels of the Ministry of Health, and from donors and partners funding and implementing Zambia's VMMC program, exploring the decisions required to attain a sustainable VMMC program and the behavioral dynamics involved at personal and institutional levels. Using pattern identification and theme matching to analyze the content of the responses, we derived three core decision-making phases in the transition to a sustainable VMMC program: 1) developing an alternative funding strategy, 2) developing a policy for early-infant (0-2 months) and early-adolescent (15-17 years) male circumcision, which is crucial to sustainable HIV prevention; and 3) identifying integrated and efficient implementation models. We formulated a framework showing how, in each phase, a range of behavioral dynamics can form barriers that hinder effective decision-making among stakeholders at the same level (e.g., national ministries and donors) or across levels (e.g., national, provincial and district). Our research methodology and the resulting framework offer a systematic approach for in-depth investigations into organizational decision-making in public health programs, as well as development programs beyond VMMC and HIV prevention. It provides the insights necessary to map organizational development and policy-making transition plans to sustainability, by explaining tangible factors such as organizational processes and systems, as well as intangibles such as the behaviors of policymakers and institutional actors.</p>
Needs-based approaches for representing personal transportation decision-making
<p>Data from a Utah State University research study, "Needs-based approaches for representing personal transportation decision-making". This version includes data from the focus group portion of the study. </p>
Distinct decision-making properties underlying the species specificity of group formation of flies
<p>Many animal species form groups. Group characteristics differ between species, suggesting that the decision-making of individuals for grouping varies across species. However, the actual decision-making properties that lead to interspecific differences in group characteristics remain unclear. Here, we compared the group formation processes of two Drosophilinae fly species, Colocasiomyia alocasiae and Drosophila melanogaster, which form dense and sparse groups, respectively. A high-throughput tracking system revealed that C. alocasiae flies formed groups faster than D. melanogaster flies, and the probability of C. alocasiae remaining in groups was far higher than that of D. melanogaster. C. alocasiae flies joined groups even when the group size was small, whereas D. melanogaster flies joined groups only when the group size was sufficiently large. C. alocasiae flies attenuated their walking speed when the inter-individual distance between flies became small, whereas such behavioural properties were not clearly observed in D. melanogaster. Furthermore, depriving C. alocasiae flies of visual input affected grouping behaviours, resulting in a severe reduction in group formation. These findings show that C. alocasiae decision-making regarding grouping, which greatly depends on vision, is significantly different from D. melanogaster, leading to species-specific group-formation properties.</p>
The role of contextual factors in decision-making by General Practitioners on paediatric referral to the Emergency Department: A Discrete Choice Experiment
<p>A General Practitioner’s (GP) decision to refer a patient to the emergency department (ED) requires consideration of a multitude of factors, and significant variation in GP referral patterns to secondary care has been recorded. This study examines the contextual factors that influence GPs when referring a paediatric patient with potentially self-limiting clinical symptoms to the ED.</p> <p>Utilizing a discrete choice experiment, survey data was collected from GPs in Ireland (n = 142) to elicit factors influencing this decision across five attributes: time/day of visit, repeat presentation, parents’ capacity to cope, parent requesting a referral, and access to a paediatric outpatient clinic/day unit.</p> <p>Using mixed logit models, all attributes were statistically significant, with repeat presentation and parents lacking the capacity to cope with a sick child identified as the strongest contextual factors leading to the decision to refer to the ED.</p> <p> </p> <p>Files explained:</p> <p>1. Survey Questions.docx details the survey.</p> <p>2. Ngene DCE design.ngd: Ngene™ file used to set-up the DCE.</p> <p>3. Survey Data File.xlsx is the source file detailing responses to the survey.</p> <p>4. Stata Data File Formatted for DCE.dta is the file formatted for the DCE for analysis</p> <p> </p> <p>Note:</p> <p><em>Data collection for a second survey for a patient with intellectual disability and limited communication skills was carried out at the same time as this survey. Data from this second study (Q4.1 – Q4.7 & Q6.1 – Q6.7) are not included in these files. </em></p>
Additional Material for Debiasing architectural decision-making: a workshop-based training approach
<p>This additional material was created to enable full replication of the experiment described in the paper:<br> "Klara Borowa, Maria Jarek, Gabriela Mystkowska, Weronika Paszko and Andrzej Zalewski: <strong>Debiasing architectural decision-making: a workshop-based training approach</strong>".<br> The paper was accepted for publication at ECSA 2022 (The 16th European Conference on Software Architecture).<br> <br> The folder contains the following files:<br> Coding-details.xlsx - the coding scheme, as well as coding results. Contains all code counts for each team participating in the experiment.<br> Experiment-meeting-plan.pdf - contains the plan for the 3-hour meeting during which the experiment was conducted, as well as a timetable of when each meeting took place and who organised it.<br> Debiasing-workshop-slides.pdf - slides used during the debiasing workshop.<br> Debiasing-workshop-plan.pdf - detailed instruction for workshop organisers, what should be said and done during the workshop.<br> Participants_questionnaire_and_results.xlsx - questionnaire questions used to obtain information about participants, as well as questionnaire results for all 44 participants.</p>
Decision-making for selection home with use Ordered Weighted Averaging (OWA operator)
<p> این مجموعه داده شامل داده های پرسشنامه برای خرید مسکن در شهر تهران است. از خریداران مسکن خواسته شده که برای خرید مسکن در شهر تهران چه معیارهایی برای آن ها در خرید خانه دارای اولویت می باشد. این معیارها شامل قیمت مسکن، سن بنا، متراژ، تعداد اتاق، محل واحد در مجتمع، پارکینگ، آسانسور، داشتن انباری، محله یا منطقه خاص، امکانات لوکس می باشد. در ادامه نیز فرآیندهای محاسباتی، نمودارها و جداول برای پیشنهاد خانه توسط عملگر میانگین وزن دار مرتب نیز در فایل های نام گذاری شده قرار گرفته است.</p>
Data of paper entitled "The Impact of Financial Influencers, Social Influencers, and FOMO Economy on the Decision-Making of Investment on Millennial Generation and Gen Z of Indonesia"
<p>The repository contains:</p> <ol> <li>Result of inner model of PLS</li> <li>Result of outer model of PLS</li> <li>Questionnaire result</li> </ol>
The Decision-Making Process Behind Library Adoption
<p>This is the Factors/Process Book for the research paper "The Decision-Making Process Behind Library Adoption", submitted to: The 35th IEEE International Conference on Software Maintenance and Evolution (ICSME).</p>
The Decision-Making Process Behind Software Library Adoption
<p>Dataset supporting journal publication "The Decision-Making Process Behind Software Library Adoption".</p>
Decision-Making Tool for Road Preventive Maintenance Using Vehicle Vibration Data
<p>Corresponding data set for Tran-SET Project No. 18PLSU08. Abstract of the final report is stated below for reference:</p> <p>"Automated and timely road pavement damage inspection is critical to the preventive maintenance and the long-term sustainability and resilience of roads in Region 6. Current road inspection practices rely heavily on a manual process. Sensor-based methods (e.g., LiDAR scanning) are promising but can be too expensive for a wider adoption. This study employs a crowdsourcing approach of using the vibration patterns of regular vehicles in inferring specific types of road damages. A cloud-based smart phone app and system was developed to collect real-time vehicle vibrations, location data, and road damage images for training the detection model. However, there is a great challenge in using classic classification methods with crowdsourced vibration data containing high level of noises, as vehicle vibrations are greatly affected by the types and conditions of the vehicles, as well the varying driving behaviors of drivers. The study thus employed the recent developments in Deep Learning methods, including a Self-Taught Learning (STL) algorithm and Sparse Coding to tackle with the low-quality issues of collected data. A total of 310 miles of road-induced vehicle vibration data was collected in Texas and Louisiana, and the road damage detection model was trained on Texas A&M University (TAMU) supercomputing server. The results show that the features generated from Sparse Coding greatly contribute to enhancing detection performances, by addressing low-quality data issues."</p>
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.