Skip to main content
Powered by ShareScore

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.

28

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

28 results for “Moca”

Learn how ShareScore rates datasets ↗
zenodo32/100

Moca: An efficient Memory trace collection system, preliminary experiments results analysis

<p>Every files required to replay the statistic analysis of the preliminary experiments for the artice: &quot;Moca: An efficient Memory trace collection system&quot; submitted at HPDC</p>

opencc-zeroJan 2016View details →
zenodo32/100

Moca: An efficient Memory trace collection system, experiments raw traces

<p>Raw traces generated for preliminary experiment of&nbsp; the article &quot;Moca: An efficient Memory trace collection system&quot; submitted at HPDC&#39;16.</p> <p>&nbsp;</p> <p>Download and extract the raw.tgz archive, then go to the hpdc directory, download and extract all the other archives inside it.</p> <p>&nbsp;</p> <p><strong>Warning:</strong> there are about 80 Gib of raw traces</p>

opencc-zeroJan 2016View details →
zenodo32/100

Moca: An efficient Memory trace collection system, experiments raw traces

<p>Raw traces generated for by the experiment of&nbsp; the article &quot;Moca: An efficient Memory trace collection system&quot; submitted at PMBS&#39;16.</p> <p>Download and extract the raw.tgz archive, then go to the created directory, download and extract all the other archives inside it.</p> <p><strong>Warning:</strong> there are about 90 Gib of raw traces</p>

opencc-zeroJan 2016View details →
zenodo32/100

Moca: An efficient Memory trace collection system, experiments results analysis

<p>Every files required to replay the statistic analysis of the experiments presented in the artice: &quot;Moca: An efficient Memory trace collection system&quot; submitted at PMBS&#39;16</p>

opencc-zeroFeb 2016View details →
zenodo32/100

MoCA causal model V1.0

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →
zenodo32/100

FIGURE 12 in Description of Moca austrasinensis sp. nov., with the first record of Imma lathidora Meyrick, 1914 from mainland China (Lepidoptera, Immidae)

FIGURE 12. Distribution map of Immidae species in the present study. Records of distribution are taken from Hampson (1891), Meyrick (1914), Diakonoff (1967) and results of this work.

opennotspecifiedSep 2019View details →
zenodo32/100

FIGURES 1–6 in Description of Moca austrasinensis sp. nov., with the first record of Imma lathidora Meyrick, 1914 from mainland China (Lepidoptera, Immidae)

FIGURES 1–6. Adults of Immidae: 1, Moca austrasinensis sp. nov., holotype, Shenzhen, Guangdong (SCAU); 2, Moca austrasinensis sp. nov., paratype, Shenzhen, Guangdong (SCAU); 3, Moca chrysocosma (Diakonoff), holotype, Luzon, Philippine, from Diakonoff (1967); 4, Moca purpurascens (Hampson), Nilgiris, India, from Hampson (1891); 5, Imma lathidora Meyrick, Huizhou, Guangdong (SCAU); 6, Imma lathidora Meyrick, holotype, Shuicheliao (Suisharyo), Taiwan, from Diakonoff (1967). Scale=1 cm

opennotspecifiedSep 2019View details →
zenodo32/100

FIGURES 10–11 in Description of Moca austrasinensis sp. nov., with the first record of Imma lathidora Meyrick, 1914 from mainland China (Lepidoptera, Immidae)

FIGURES 10–11. Male genitalia of Immidae: 10, Moca chrysocosma (Diakonoff), holotype, from Diakonoff (1967); 11, Imma lathidora Meyrick, holotype, from Diakonoff (1967).

opennotspecifiedSep 2019View details →
zenodo32/100

FIGURES 7–9 in Description of Moca austrasinensis sp. nov., with the first record of Imma lathidora Meyrick, 1914 from mainland China (Lepidoptera, Immidae)

FIGURES 7–9. Male genitalia of Immidae: 7, Moca austrasinensis sp. nov., holotype; 8 Moca austrasinensis sp. nov., paratype; 9, Imma lathidora Meyrick.

opennotspecifiedSep 2019View details →
ClinicalTrials.gov32/100

Swiss SOS MoCA - DCI Study

ClinicalTrials.gov study NCT03032471. IPD Sharing: Not stated. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov32/100

Validation of the Montreal Cognitive Assessment (MoCA) Version 8.x and MoCA-MIS in Greece.

ClinicalTrials.gov study NCT07297121. IPD Sharing: NO. Countries: 1. Publications: 4.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

MOCA Versus RFA in the Treatment of Primary Great Saphenous Varicose Veins

ClinicalTrials.gov study NCT01936168. IPD Sharing: YES. Countries: 1. Publications: 6.

controlledIPD-YESFeb 2026View details →
dryad28/100

Data from: Early MoCA predicts long-term cognitive and functional outcome and mortality after stroke

Open the record for dataset details and reuse information.

publicAug 2019View details →
zenodo24/100

MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks

<p><strong>Description: </strong>This MOCAS is a multimodal dataset dedicated for human cognitive workload (CWL) assessment. In contrast to existing datasets based on virtual game stimuli, the data in MOCAS was collected from realistic closed-circuit television (CCTV) monitoring tasks, increasing its applicability for real-world scenarios. To build MOCAS, two off-the-shelf wearable sensors and one webcam were utilized to collect physiological signals and behavioral features from 21 human subjects. After each task, participants reported their CWL by completing the NASA-Task Load Index (NASA-TLX) and Instantaneous Self Assessment (ISA). Personal background (e.g., personality and prior experience) was surveyed using demographic and Big Five Factor personality questionnaires, and two domains of subjective emotion information (i.e., arousal and valence) were obtained from the Self-Assessment Manikin, which could serve as potential indicators for improving CWL recognition performance. Technical validation was conducted to demonstrate that target CWL levels were elicited during simultaneous CCTV monitoring tasks; its results support the high quality of the collected multimodal signals.</p> <p><strong>Data Access:</strong>&nbsp;In order to protect the sensitive data and privacy of human subjects (e.g., physiological signals and facial views), only authorized researchers who consent to the End User License Agreement (EULA) are allowed to download the MOCAS. The researchers who want to access the MOCAS should visit our website and download the ELUA document;<a href="https://drive.google.com/file/d/1XKbZIlKDYH9RG7QD_v2fB7mYF3pNeA9I/view?usp=sharing">&nbsp;https://drive.google.com/file/d/1XKbZIlKDYH9RG7QD_v2fB7mYF3pNeA9I/view?usp=sharing</a>&nbsp;After reviewing and filling the document up, they should email the signed ELUA document to&nbsp;<a href="mailto:info@smart-laboratory.org">info@smart-laboratory.org</a> and <a href="mailto:wonsu0513@gmail.com">wonsu0513@gmail.com </a>with Zenodo account and Reqeust Access via this repository (see the below file section). Then, our research group will review and grant their access to our Zenodo repository having the downsampled MOCAS dataset, subjective information, and supplementary codes used in this paper. For sharing the raw dataset, we will sequentially invite their email address used in the Zenodo and the EULA document to access raw dataset uploaded on an additional repository (Purdue BOX, https://purdue.box.com/v/mocas-dataset), due to huge size of the raw dataset.</p> <p><strong><a title="BibTeX">BibTeX </a>Citation:</strong></p> <div>Jo, W., Wang, R., Cha, G. E., Sun, S., Senthilkumaran, R. K., Foti, D., &amp; Min, B. C. (2024). MOCAS: A multimodal dataset for objective cognitive workload assessment on simultaneous tasks.&nbsp;<em>IEEE Transactions on Affective Computing</em>.</div> <pre>or<br><br>@ARTICLE{jo2024mocas, author={Jo, Wonse and Wang, Ruiqi and Cha, Go-Eum and Sun, Su and Senthilkumaran, Revanth Krishna and Foti, Daniel and Min, Byung-Cheol}, journal={IEEE Transactions on Affective Computing}, title={MOCAS: A Multimodal Dataset for Objective Cognitive Workload Assessment on Simultaneous Tasks}, year={2025}, volume={16}, number={1}, pages={116-132}, doi={10.1109/TAFFC.2024.3414330}}</pre>

restrictedcc-by-4.0Aug 2022View details →
ClinicalTrials.gov24/100

French Language Validation of the 5-minutes Montreal Cognitive Assessment (MoCA)

ClinicalTrials.gov study NCT03232697. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

MoCA vs. MMS: Which Tool to Detect Cognitive Disorders in Oncogeriatric?

ClinicalTrials.gov study NCT03299855. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

The MOCA I Study - Microvascular Obstruction with CoFI™ System Assessment

ClinicalTrials.gov study NCT03654573. IPD Sharing: NO. Countries: 3. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

MoCa Test for the Early Detection of Mild Cognitive Impairment During Annual Assessment of Young Adults With Diabetes and in a Control Group Without Diabetes

ClinicalTrials.gov study NCT02545062. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Validation Of The Flemish Montreal Cognitive Assessment (MoCA) For Persons With Hearing Impairment

ClinicalTrials.gov study NCT06400173. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

Molecular Markers in Cancers and Precancers (MOCA)

ClinicalTrials.gov study NCT05257707. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View 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