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

97803 results
  • Data for "Selection of Shallow Crustal Earthquake Ground Motion Models for the West Nusa Tenggara Region, Indonesia"
    location and magnitude of considered earthquake in "Selection of Shallow Crustal Earthquake Ground Motion Models for the West Nusa Tenggara Region, Indonesia"
    • Dataset
  • CALCULO DEL TRL EN EL PROYECTO FACTORES DEL MODELO EFECTIVO DEL PROCESO DE INNOVACIÓN TECNOLÓGICA – METIP, PARA FOMENTAR LA INNOVACIÓN Y PROTECCIÓN DE LA PROPIEDAD INTELECTUAL EN EL DESARROLLO DE TECNOLOGÍAS EN DIVERSOS ÁMBITOS
    Para efectos del caculo del Nivel de Madurez Tecnologica de cada una de las tecnologias desarrolladas con la aplicacion del MEPIT, se utiliza la calculadora disponible en: https://vinculate.concytec.gob.pe/niveles-de-madurez/calculadora-nivel-madurez/
    • Dataset
  • Experiment of chocolate consumption
    This study investigates the unit size effect, a behaviorally-oriented nudge, on chocolate consumption. In particular, it examines how different unit sizes and the presence or absence of packaging influence the quantity of chocolate consumed and the perceived energy intake in grams and calories. The methodology involved an experiment with four focus groups, differentiated by health-consciousness, who were provided with chocolate in varying unit sizes and packaging conditions.
    • Dataset
  • Understanding biological carbon pump in the central Arabian Sea using phytoplankton biomarkers and diatom frustules from surface sediments.
    The Central Arabian Sea, a tropical ocean basin, is impacted by monsoon winds that lead to high biological productivity in surface waters and form an oxygen minimum zone (OMZ) at intermediate depth. The present study aimed to understand the pattern of biological carbon pump driven by different phytoplankton groups along the central Arabians Sea, an area strongly impacted by monsoon wind forcings. The surface sediment samples from 5 locations along the central Arabian Sea were collected from 21 ° N to 11 ° N (at 2 ° intervals) along 64 ° E. These sediments accumulate materials originating from surface waters and can be used to understand the surface processes including the contributions of various phytoplankton groups in sinking materials. Bulk sediment parameters (total organic carbon, inorganic carbon, total nitrogen) were analyzed along with plankton biomarkers (sterols and alkenone) and sea surface temperature (SST) proxy using alkenone. Additionally, the frustules of diatoms that are siliceous phytoplankton shells, were also measured from the same sediments. We noticed a north-south gradient in all parameters and the biological proxies showed more organic matter preservation from larger diatoms in the north. Whereas, lower organic matter contributed by smaller phytoplankton and zooplankton were found in the south. These trends were attributed to ocean-atmospheric processes and oxygen availability in the water column.
    • Dataset
  • Bank Affiliated Directors and Earnings management
    Source code for bank affiliated directors and earnings management
    • Dataset
  • Colour Emoji Dataset
    Reaction time and accuracy data for colour emoji categorisation task
    • Dataset
  • Data: Compliance and Familiarity with Fixed Assets’ Disclosure Requirements and Firm Value
    We examine the impact of compliance and familiarity with fixed assets’ disclosure requirements on firm value in Indonesia. Based on the IAS 16 disclosure instrument developed by Deloitte, data were manually tabulated from 1,672 financial statements of publicly listed firms during the period from 2013 to 2020. We calculated the compliance and familiarity index by dividing the total amount of “yeses” by the total amount of “yeses + nos.” We combine these data (indexes) with firm value data and data for control variables. We include SAS dataset and codes for the hypotheses testing. We find that both the compliance level and familiarity level gradually increase over time. The result shows that greater compliance with IFRS accounting standards is associated with greater firm value. Interestingly, we find a negative association between the familiarity sub-index and firm value, suggesting that unfamiliarity with more complex accounting standards can lead to lower firm value.
    • Dataset
  • The performance of the pattern search direct search method in solving load estimation problems
    Accurately estimating load is essential for effective electric distribution planning, assets management, precise power flow predictions, accurate power losses calculations, and efficient integration of distributed energy resources. To facilitate this, a dataset was generated using Matlab to produce various simulations in the Open Electric Power Distribution System Simulator (OpenDSS), a widely used software in the electric distribution industry. These simulations were conducted on three typical distribution feeders (IEEE 13-bus, 37-bus, and 123-bus) that support studies in distribution planning, assets management, power flow predictions, power losses calculations, and distributed resource integration. The dataset includes individual demand profiles of residential, commercial, and industrial consumers specified for the three distribution feeders, comprising at least 96 distinct scenarios. An optimization method was developed using the obtained dataset, which employs the pattern search technique to estimate loads by optimizing specified objective functions and constraints. The load estimation quality was assessed for all three feeders, utilizing estimation quality indices proposed by the authors. These indices evaluated both the initial and proposed load estimation methods across the developed scenarios. Furthermore, the data provided in this article can be utilized for comparison with future load estimation studies, particularly regarding the quality of the method's results.
    • Dataset
  • Multiclass Password Strength Classification (MPSC 2024) Dataset for password cracking detection and prevention
    We present a novel cutting-edge, large-scale multiclass dataset to improve the security of password protected systems cognition of suspicious password cracking attempts. The proposed newly generated dataset contains up-to-date samples and features available to the public to help reduce the effect of upcoming cyberattacks with machine learning methods. Specifically, 700,000 samples with more than 100 features are collected, processed through several stages including hashing, tokenization (NLP techniques), an others, and organized into three password classes: weak, moderate, and strong. For detailed info, Please refer to and cite our articles: Al-Haija, Q.A., Abu-Ghazaleh, R., Hafez, A., Mansour, S., Aljammal, Y. (2024). Password Security: Cracking Techniques and Countermeasures. Proceedings of Data Analytics and Management. ICDAM 2024. Lecture Notes in Networks and Systems, Springer, 2024. Al-Haija, Q.A., Abu-Ghazaleh, R., Hafez, A., Mansour, S., Aljammal, Y. (2024). PasswordProtectorPro: A Password Cracking Detection and Prevention Tool for Mission Critical Systems. 8th IET Smart Cities Symposium (SCS 2024), Hybrid Conference, Bahrain, 2024.
    • Dataset
  • LDHU3_14.1840
    GOLD domain-containing protein; Leishmania donovani (HU3 strain)
    • Dataset
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

Data Monitor provides visibility on an institution's entire research data output by harvesting research data from 2000+ generalist and domain-specific repositories, including everything in Mendeley Data.

Find out more