Skip to main content

Share your research data

Mendeley Data is a free and secure cloud-based communal repository where you can store your data, ensuring it is easy to share, access and cite, wherever you are.

Create a Dataset

Find out more about our institutional offering, Digital Commons Data

Search the repository

Recently published

128980 results
  • Framing Bias in a Large Language Model: A Diagnostic Accuracy Study of Prompt Effects on ChatGPT’s Melanoma Classification
    - Mendeley Supplemental Figure 1. Representative examples of the test. Each image was presented six times under different instructions: a neutral baseline prompt, and five framed prompts. - Mendeley Supplemental File 1. Detailed Materials and methods (Study design, Model Access and Interaction, Dataset Details, Prompting Procedure, Outcome Measures and Statistical Analysis) of the study
  • Resilience Pathways to Drought: An analysis of Agro-pastoral Household in Buroa, Somaliland
    This dataset supports the findings of the preprint research article “Resilience Pathways to drought: An analysis of Agro-pastoral households in Buroa, Somaliland”. The study dataset package includes: Codebook, Survey raw data, README.tex and Methods description doc.
  • Late Bronze Age Transdanubian Arrowhead Database
    This database was compiled for the paper titled "Late Bronze Age Bronze Arrowheads from Transdanubia and Beyond" (DissArch 2025). It provides a detailed list of Late Bronze Age Transdanubian analogue finds, along with supplementary information such as site names, archaeological context, dating, quantity, citations, and notes. The database is based on the works of Gedl (2014), Říhovský (1996), Eckhardt (1996), Clausing (2005), Reinhold (2007), Sicherl (2004), Vasić (2015), and Inselmann et al. (2024), as well as numerous individual studies referenced in the document "Transdanubian Arrowhead Database (Bibliography)." This database also revises the most recent work by Inselmann et al. (2024) and broadens the geographic scope of analogous finds beyond Central Europe. It includes information on the following Eckhardt variants: 1A, 1C, 3A, 4A, 4C, 4E, and 5A. We intend to regularly update and expand the database. Should you identify any errors—such as missing citations, incorrect site names, or typological misidentifications—please contact me so appropriate corrections can be made. Version 1 was made in July, 2025 and updated to Version 2 in October 6, 2025. Version 4 was made in October 11, 2025.
  • Dataset for 'Effects of Topographic Complexity on Space-Use by a Key Intertidal Grazer in Artificial Environments'
    These datasets contain the data used in the analysis and presentation of results for the manuscript 'Effects of Topographic Complexity on Space-Use by a Key Intertidal Grazer in Artificial Environments' (Clubley et al.). The file 'Clubley_etal_gross_limpet_movement.csv' contains limpet movement data from laboratory experiments, where movement distance (cm) of each limpet is shown for each individual time step (5-minute). The file 'Clubley_etal_net_limpet_movement.csv' contains the net distance (distance between original and final position) moved by each limpet during the laboratory experiments (24-hour).
  • NUTS2 Level Land Use and Land Cover Quantifications under the Shared Socio-Economic Pathways, 2020-2050
    This dataset provides consistent projections of land use and land cover (LULC) for European NUTS2 regions under the five Shared Socio-Economic Pathways (SSPs) from 2020 to 2050. The projections are generated with G-RDEM [1], a recursive-dynamic global Computable General Equilibrium (CGE) model implemented in the open-source platform CGEBox [2]. Designed to capture long-term structural change, G-RDEM simulates economic and land use dynamics directly at the NUTS2 level, avoiding the need for post-model downscaling. European Union (EU) member states follow the 2016 NUTS2 classification [3], while European Free Trade Association (EFTA) countries and EU accession candidates follow the 2008 NUTS2 classification [4]. The dataset includes: • Scenarios: - SSP1 - SSP2 - SSP3 - SSP4 - SSP5 • Regions: - NUTS2 regions for EU member states, EU accession candidates, and EFTA countries - Country level results for Morocco, Algeria, Tunisia, Egypt, the rest of North Africa, Russia, Belarus, and Ukraine - Continental aggregates for the rest of the world • Land cover and corresponding land uses: - Built-up land * No economic land uses - Cropland * Apples * Bananas/ plantains * Barley * Citrus fruits * Cocoa beans * Coffee beans * Grapes * Leguminosae * Maize * Nuts * Oats * Olives * Other cereals * Other crops * Other fruits * Other oilseeds * Other roots/ tubers * Other vegetables * Paddy rice * Palm oil fruit * Plant-based fibres * Potatoes * Rape seed * Rye * Sorghum * Soy bean * Sugar cane/ beet * Teas * Tomatoes * Wheat * All cropland uses are further differentiated between irrigated and rainfed variants - Managed forest * Forestry - Other land (rock, ice, desert) * No economic land uses - Pastureland * Cattle for meat * Raw milk * Ruminants for meat * Wool - Savannah/ grassland * No economic land uses - Shrubland * No economic land uses - Unmanaged forest * No economic land uses • Units: mio ha • Temporal coverage: 2020–2050, 2- and 5-year intervals • Format: CSV and XLSX The dataset is suitable for applications in climate impact research, ecosystem service assessment, water and biodiversity modelling, land use and land cover planning, and other policy scenario analysis.
  • Magnetic susceptibility, radiocarbon and Polarella glacialis data for core KH21-234-34GC
    Here we present a magnetic susceptibility dataset from marine sediment core KH21-234-34GC , for its age model. Core KH21-234-34GC was retrieved from the Yermak Plateu (81.2199280 ˚N, 2.3710955˚E ) with a gravity corer at 1011m water depth during cruise KH21-234 . We measured the magnetic susceptibility at 1 cm resolution using a Bartington MS2C loop sensor (Ø 125mm) with a Geotek Multi-Sensor Core Logger (MSCL-S). Gene copies of the sympagic dinoflagellate Polarella glacialis were determined by droplet digital PCR on samples from marine sediment core KH21-234-34GC collected from the Yermak Plateu (81.2199280 ˚N, 2.3710955˚E ) with a gravity corer at 1011m water depth during cruise KH21-234. DNA from gravity core sediments was extracted in the NORCE ancient DNA laboratory using the DNeasy PowerMax Soil Kit (Qiagen). Primers targeting the ITS1 region of P. glacialis were used in ddPCR reactions to determine gene copies per g of sediment. Radiocarbon dates were determined by picking shells of Neogloboquadrina pachyderma at four depths from marine sediment core KH21-234-34GC collected from the Yermak Plateu (81.2199280 ˚N, 2.3710955˚E ) with a gravity corer at 1011m water depth during cruise KH21-234. Accelerator mass spectrometry (AMS) 14C dates from the radiocarbon lab at ETH Zurich, and calibrated ages were calculated used the functions BchronCalibrate:sampleAges and Bchronology:PredictAges from the statistical package BChron (version 4.7.7). We trace P. glacialis quantitatively using droplet digital PCR (ddPCR), alongside biomarkers of sea-ice-associated and open-water phytoplankton. We utilise these proxies in combination to reconstruct past sea ice conditions in a sediment core from the Yermak Plateau (Arctic Ocean) dating back to MIS 3 (ca. 50,000 years ago). Our results indicate perennial and extensive sea ice coverage from MIS 3 until the end of the Last Glacial Maximum. We show that first-year sea ice, and seasonal sea ice were very variable during the Bølling-Allerød and Younger Dryas periods, including periods of open ocean during the Bølling-Allerød and permanent sea ice during the Younger Dryas. Within the Holocene we observe an increasing trend of P. glacialis DNA from the warm early Holocene to the cool late Holocene, suggesting an increase in first-year sea ice extent.
  • Beyond Diagnosis: Caregiver and Service Provider Experiences with Autism Support in the Philippines
    ABSTRACT Purpose: Access to autism services in low- and middle-income countries remains underexamined. This study explored the lived experiences of caregivers and service providers as they navigate the challenges and supports within the autism service landscape in the Philippines. Guided by Bronfenbrenner’s Ecological Systems Theory, the research examined how sociocultural norms, systemic barriers, and institutional constraints interact to shape engagement with autism care. Methods: Using a qualitative design, six purposely selected caregivers, teachers, and therapists participated in structure interviews. Thematic analysis generated fourteen themes reflecting motivations for service engagement, sociocultural barriers, collaborative supports, systemic limitations, and aspirations for equitable services. Results: Findings demonstrated that while personal commitment drives engagements, entrenched cultural beliefs, socioeconomic disparities, professional underevaluation, and fragmented systems impede consistent care. Participants emphasized the need for decentralized services, standardized professional regulation, stronger government involvement, and sustained public education. Conclusion: Overall, the study underscores the importance of the whole-system reform and culturally grounded approaches to autism services in the Philippines. The study contributes empirical evidence to the growing literature on autism service disparities and underscores the importance of socioculturally informed models of care in underresourced settings.
  • Biochar alters soil aggregate organic carbon component distribution and stability under nitrogen fertilization
    Raw data from general test and supplementary material.
  • Bots or Humans? The Role of AI and eWOM in Travel Decisions Amid Crisis
    Guided by Theory of Planned Behavior (TPB) and Source Credibility Theory (SCT), the study addressed RQ1: How does crisis communication source (CCS: AI chatbot vs. eWOM) affect visit intentions (VI) to paradox destinations (risky yet attractive places, e.g., politically unstable with cultural appeal) via perceived source credibility (PSC) and attitudes toward the destination (ATD), moderated by perceived coping efficacy (PCE)? RQ2 examined differences between conditions. Hypotheses: H1: CCS influences PSC (AI > eWOM). H2: PSC positively affects ATD. H3: ATD positively affects VI. H4: Serial mediation (CCS → PSC → ATD → VI). H5a–c: PCE moderates paths (stronger at high PCE). H6a–b: Paths stronger in AI vs. eWOM condition. Data Description and Gathering Quantitative experimental survey data from 352 Chinese adults (63.6% female, mostly 25–34 years old, bachelor's degree holders, occasional travelers). Collected via Credamo.cc in 2025 using convenience sampling. Participants randomly assigned to eWOM (n=179) or AI chatbot (n=173) conditions, viewing simulated crisis info for fictional destination "Solara" (political instability + attractions). Measures: PSC (5 items), ATD (3), VI (3), PCE (4) on 7-point Likert scales; demographics as covariates. Cross-sectional; suitable for causal tests but limited generalizability. Interpret: Higher scores = stronger perceptions; use means/SDs for descriptives, β/p-values for paths. Usage: Replicate in SPSS/AMOS for mediation/moderation; apply to tourism strategies. Notable Findings Analyzed via SPSS/AMOS (ANCOVA, PROCESS Model 6, CFA, MGA). Reliability α >.89; model fit good (CFI=.96, RMSEA=.04). AI more credible than eWOM (p=.008; H1 supported). PSC → ATD (p<.001; H2) and ATD → VI (p<.001; H3) positive. Serial mediation significant (b=0.1572, CI [0.0354, 0.2986]; H4 supported). PCE moderated PSC → ATD (p=.010) and ATD → VI (stronger for low-PCE; H5b–c supported, H5a not). MGA: Paths stronger in AI condition (e.g., PSC → ATD: β=.90 vs. .79; p=.01; H6 supported). Data Interpretation Data shows AI chatbots enhance credibility over eWOM in paradox contexts, driving attitudes and intentions via mediation. Low-PCE tourists more influenced by credible sources for risk mitigation; high-PCE more resilient. Limitations: Fictional scenario, Chinese sample, self-reports. Implications: Use AI for factual crisis comms, eWOM for emotional ties; hybrid approaches for recovery in unstable destinations.
  • The Global 30m Forest Age Map (Natural vs. Planted)
    Due to memory constraints, all data is stored at https://code.earthengine.google.com/?asset=projects/ee-wangyan00forestage/assets/127nf and https://code.earthengine.google.com/?asset=projects/ee-wangyan00forestage/assets/254pf
1
View more
GREI

The Generalist Repository Ecosystem Initiative

Elsevier's Mendeley Data repository is a participating member of the National Institutes of Health (NIH) Office of Data Science Strategy (ODSS) GREI project. The GREI includes seven established generalist repositories funded by the NIH to work together to establish consistent metadata, develop use cases for data sharing, train and educate researchers on FAIR data and the importance of data sharing, and more.

Find out more

Why use Mendeley Data?

Make your research data citable
Unique DOIs and easy-to-use citation tools make it easy to refer to your research data.
Share data privately or publicly
Securely share your data with colleagues and co-authors before publication.
Ensure long-term data storage
Your data is archived for as long as you need it by Data Archiving & Networked Services.
Keep access to all versions
Mendeley Data supports versioning, making longitudinal studies easier.

The Mendeley Data communal data repository is powered by Digital Commons Data.

Digital Commons Data provides everything that your institution will need to launch and maintain a successful Research Data Management program at scale.

Find out more