cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.abkyt3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-119.4893 34.93419, -119.4891 34.93387, -119.4888 34.93356, -119.4885 34.93326, -119.4882 34.93298, -119.4878 34.93272, -119.4875 34.93246, -119.4871 34.93223, -119.4867 34.93201, -119.4863 34.9318, -119.4859 34.93162, -119.4855 34.93145, -119.485 34.9313, -119.4846 34.93117, -119.4841 34.93106, -119.4837 34.93096, -119.4832 34.93089, -119.4828 34.93084, -119.4823 34.93081, -119.4796 34.93068, -119.4791 34.93067, -119.4786 34.93068, -119.4782 34.9307, -119.4777 34.93075, -119.4772 34.93082, -119.4768 34.9309, -119.4763 34.93101, -119.4759 34.93113, -119.4755 34.93127, -119.475 34.93143, -119.4746 34.93161, -119.4742 34.93181, -119.4739 34.93202, -119.4735 34.93225, -119.4731 34.93249, -119.4728 34.93275, -119.4725 34.93302, -119.4721 34.93331, -119.4719 34.93361, -119.4716 34.93392, -119.4713 34.93424, -119.4711 34.93457, -119.4709 34.93491, -119.4707 34.93526, -119.4706 34.93562, -119.4704 34.93598, -119.4703 34.93635, -119.4702 34.93672, -119.4701 34.9371, -119.4701 34.93748, -119.4701 34.93786, -119.4701 34.93824, -119.4701 34.93849, -119.4701 34.93887, -119.4701 34.93926, -119.4702 34.93963, -119.4703 34.94001, -119.4704 34.94038, -119.4706 34.94074, -119.4708 34.9411, -119.4709 34.94145, -119.4712 34.94179, -119.4714 34.94213, -119.4716 34.94245, -119.4719 34.94276, -119.4722 34.94306, -119.4725 34.94334, -119.4729 34.94361, -119.4732 34.94387, -119.4736 34.94411, -119.4739 34.94434, -119.4743 34.94455, -119.4747 34.94474, -119.4752 34.94492, -119.4756 34.94507, -119.476 34.94521, -119.4765 34.94533, -119.4794 34.94607, -119.4799 34.94617, -119.4803 34.94625, -119.4808 34.94632, -119.4813 34.94636, -119.4817 34.94638, -119.4822 34.94638, -119.4827 34.94637, -119.4831 34.94633, -119.4836 34.94628, -119.484 34.9462, -119.4845 34.94611, -119.4849 34.94599, -119.4854 34.94586, -119.4858 34.94571, -119.4862 34.94555, -119.4866 34.94536, -119.487 34.94516, -119.4874 34.94494, -119.4877 34.94471, -119.4881 34.94446, -119.4884 34.94419, -119.4887 34.94392, -119.489 34.94363, -119.4893 34.94332, -119.4896 34.94301, -119.4898 34.94268, -119.4901 34.94235, -119.4903 34.942, -119.4904 34.94165, -119.4906 34.94129, -119.4907 34.94093, -119.4908 34.94056, -119.4909 34.94019, -119.491 34.93981, -119.491 34.93943, -119.4911 34.93905, -119.4911 34.93866, -119.4911 34.93828, -119.491 34.9379, -119.491 34.93752, -119.4909 34.93714, -119.4908 34.93677, -119.4907 34.9364, -119.4905 34.93604, -119.4903 34.93569, -119.4901 34.93534, -119.4899 34.935, -119.4896 34.93452, -119.4893 34.93419))",
 "Year is greater than or equal to 2001",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021162-251120083545085/datasets/export for details.
DOI: 10.17026/ar/wka5pn
title: PAN-00173285 - composite shoe buckle

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173285&lt;/p&gt;
description: Modified: 2025-04-25T10:53:43+02:00
DOI: 10.6084/m9.figshare.30757604
title: Construction Labor Activity Observation Data: The Impact of Trade Congestion on Productivity (Phoenix, 2024-2025)

description: Data Summary Site Observations, documenting the Number of Trades Onsite during the Observations and the Average Work Percentages over the Seven Classifications of Work Categories.
DOI: 10.6084/m9.figshare.30757604.v1
title: Construction Labor Activity Observation Data: The Impact of Trade Congestion on Productivity (Phoenix, 2024-2025)

description: Data Summary Site Observations, documenting the Number of Trades Onsite during the Observations and the Average Work Percentages over the Seven Classifications of Work Categories.
DOI: 10.15468/dl.jc7ffc
title: Occurrence Download

description: A dataset containing 68378 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "TaxonKey is Apis mellifera"
 ]
}

 The dataset includes 68378 records from 108 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021108-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ftfq6b
title: Occurrence Download

description: A dataset containing 2075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Fauna y flora asociada a 18 humedales del valle geográfico del río Cauca"
 ]
}

 The dataset includes 2075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021163-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gty5u8
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-119.4865 34.9529, -119.4868 34.95265, -119.4871 34.95237, -119.4875 34.95209, -119.4877 34.95179, -119.488 34.95148, -119.4883 34.95116, -119.4885 34.95083, -119.4887 34.95049, -119.4889 34.95014, -119.489 34.94978, -119.4892 34.94942, -119.4893 34.94905, -119.4894 34.94868, -119.4895 34.9483, -119.4895 34.94792, -119.4895 34.94754, -119.4895 34.94716, -119.4895 34.94678, -119.4895 34.9464, -119.4894 34.9457, -119.4893 34.94532, -119.4892 34.94495, -119.4891 34.94458, -119.4889 34.94422, -119.4888 34.94387, -119.4886 34.94352, -119.4884 34.94318, -119.4881 34.94285, -119.4879 34.94253, -119.4876 34.94222, -119.4873 34.94192, -119.487 34.94164, -119.4867 34.94137, -119.4863 34.94111, -119.486 34.94087, -119.4856 34.94064, -119.4852 34.94043, -119.4848 34.94024, -119.4844 34.94006, -119.484 34.9399, -119.4836 34.93976, -119.4831 34.93964, -119.4827 34.93953, -119.4824 34.93946, -119.4819 34.93938, -119.4815 34.93932, -119.481 34.93927, -119.4806 34.93924, -119.4801 34.93923, -119.4797 34.93924, -119.4792 34.93927, -119.4788 34.93931, -119.4782 34.93939, -119.4777 34.93945, -119.4773 34.93954, -119.4768 34.93965, -119.4764 34.93977, -119.4759 34.93991, -119.4755 34.94008, -119.4751 34.94026, -119.4747 34.94046, -119.4743 34.94067, -119.4739 34.9409, -119.4736 34.94115, -119.4732 34.94141, -119.4729 34.94169, -119.4726 34.94198, -119.4723 34.94228, -119.472 34.94259, -119.4718 34.94292, -119.4715 34.94326, -119.4713 34.9436, -119.4712 34.94396, -119.471 34.94432, -119.4709 34.94468, -119.4707 34.94506, -119.4707 34.94536, -119.4706 34.94571, -119.4705 34.94606, -119.4705 34.94641, -119.4704 34.94677, -119.4704 34.94712, -119.4705 34.94747, -119.4705 34.94775, -119.4705 34.94817, -119.4706 34.94858, -119.4707 34.94898, -119.4708 34.94938, -119.471 34.94977, -119.4711 34.9501, -119.4713 34.95045, -119.4715 34.9508, -119.4717 34.95114, -119.472 34.95146, -119.4722 34.95178, -119.4725 34.95209, -119.4728 34.95238, -119.4731 34.95267, -119.4734 34.95294, -119.4738 34.95319, -119.4741 34.95343, -119.4745 34.95365, -119.4749 34.95386, -119.4753 34.95405, -119.4757 34.95422, -119.4759 34.95427, -119.476 34.95433, -119.4764 34.95448, -119.4768 34.95462, -119.4773 34.95474, -119.4777 34.95484, -119.4781 34.95492, -119.4786 34.95499, -119.4787 34.955, -119.4792 34.95505, -119.4796 34.95508, -119.4801 34.95509, -119.4806 34.95508, -119.481 34.95505, -119.4815 34.955, -119.4819 34.95493, -119.4824 34.95484, -119.4828 34.95473, -119.4833 34.9546, -119.4837 34.95446, -119.4841 34.95429, -119.4845 34.95411, -119.4849 34.95391, -119.4853 34.9537, -119.4857 34.95347, -119.486 34.95322, -119.4862 34.95307, -119.4865 34.9529))",
 "Year is greater than or equal to 2001",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021164-251120083545085/datasets/export for details.
DOI: 10.18739/a2sb3x15x
title: Alaska River Ice Phenology from Landsat and ERA5: Observations, Models, and Trends (1979-2024)

description: This dataset provides spatial and temporal information on the seasonal formation and loss of river ice cover (ice phenology) across Alaska from water years (WY) 1979 to 2023 at the river reach level, integrating remote sensing observations from the Landsat satellite archive with climate reanalysis data from ERA5. It includes both observed indicators derived directly from satellite imagery and modeled estimates of ice-cover status generated from logistic regression using air temperature metrics. The dataset characterizes freeze-up and break-up timing, duration of ice cover, and changes in river ice phenology.
 The primary purpose of this dataset is to support assessments of how river ice has responded to changing climate conditions over recent decades. These data are intended to inform decision-making related to transportation, access to resources, and climate adaptation—particularly for rural Alaskan communities, many of which depend on rivers as year-round transportation corridors and require stable ice cover for safe winter travel. The dataset is associated with a manuscript by Brown et al. (in prep). It is structured to support both exploratory visualization and reproducible analysis, with accompanying code for data processing, model fitting, and summarization of results.
 Key products include:
 - Observed surface water and inferred ice cover extent from Landsat for 30 rivers (WY 1982–2023);
 - Predicted annual ice phenology metrics (e.g., first and last days of full ice-cover, ice cover duration) derived from logistic regression models trained on observed ice cover and ERA5 30-day prior mean air temperatures (WY 1979-2023);
 - Median ice phenology for WY 2000-2023 from both observed and modeled datasets;
 - Analysis of change from both observed and modeled datasets, including trend estimates and decadal comparisons.
DOI: 10.17026/ar/arxbuj
title: PAN-00173223 - Roman one-piece iron spring shears

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173223&lt;/p&gt;
description: Modified: 2025-04-30T12:51:50+02:00
DOI: 10.15468/dl.c8dfwj
title: Occurrence Download

description: A dataset containing 4125 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is North America",
 "Country is Canada",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Month is May",
 "StateProvince is New Brunswick",
 "Year 2025-2025"
 ]
}

 The dataset includes 4125 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021165-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17782106
title: Table 3. Summary of total translation time, pauses and revisions by participant group in the Translog-II experiment
DOI: 10.5281/zenodo.17782107
title: Table 3. Summary of total translation time, pauses and revisions by participant group in the Translog-II experiment
DOI: 10.15468/dl.63carp
title: Occurrence Download

description: A dataset listing the 20 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is USA.29.4_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Carnivora"
 ]
}

 The dataset's 20 records were derived from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021157-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.khq89f
title: Occurrence Download

description: A dataset containing 88 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Heterocoma albida, Proteopsis insculpta, Proteopsis sellowii)"
 ]
}

 The dataset includes 88 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021170-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eajuuc
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Parvindela cursitans"
 ]
}

 The dataset includes 57 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021173-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/ddn0js
title: PAN-00173067 - devotional pendant Modern period

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00173067&lt;/p&gt;
description: Modified: 2025-04-26T11:50:55+02:00
DOI: 10.15468/dl.wpqak4
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mammalia",
 "HasCoordinate is true",
 "Geometry POLYGON ((-119.8856 35.03841, -119.8852 35.03853, -119.8847 35.03868, -119.8843 35.03884, -119.8839 35.03902, -119.8835 35.03922, -119.8831 35.03944, -119.8827 35.03968, -119.8823 35.03993, -119.882 35.0402, -119.8816 35.04048, -119.8813 35.04077, -119.881 35.04108, -119.8808 35.0414, -119.8805 35.04174, -119.8803 35.04208, -119.8801 35.04243, -119.8797 35.04314, -119.8795 35.0435, -119.8794 35.04387, -119.8792 35.04424, -119.8791 35.04462, -119.879 35.04501, -119.879 35.0454, -119.8789 35.04579, -119.8789 35.04618, -119.8789 35.04657, -119.879 35.04696, -119.879 35.04734, -119.8791 35.04773, -119.8792 35.04811, -119.8794 35.04848, -119.8795 35.04885, -119.8797 35.04921, -119.8799 35.04956, -119.8802 35.0499, -119.8804 35.05023, -119.8807 35.05055, -119.881 35.05086, -119.8813 35.05115, -119.8816 35.05143, -119.882 35.05169, -119.8824 35.05194, -119.8827 35.05217, -119.8831 35.05239, -119.8836 35.05259, -119.884 35.05277, -119.8844 35.05293, -119.8857 35.05337, -119.8861 35.05351, -119.8866 35.05363, -119.887 35.05373, -119.8875 35.05381, -119.888 35.05387, -119.8885 35.05392, -119.8889 35.05394, -119.8894 35.05394, -119.8899 35.05392, -119.8903 35.05388, -119.8908 35.05381, -119.8913 35.05373, -119.8917 35.05363, -119.8922 35.05351, -119.8926 35.05337, -119.8931 35.05321, -119.8935 35.05303, -119.8939 35.05284, -119.8944 35.05259, -119.8948 35.05239, -119.8951 35.05218, -119.8955 35.05195, -119.8958 35.0517, -119.8961 35.05145, -119.8963 35.05125, -119.8967 35.05096, -119.897 35.05065, -119.8973 35.05033, -119.8975 35.05, -119.8978 35.04966, -119.898 35.0493, -119.8982 35.04894, -119.8984 35.04857, -119.8985 35.04819, -119.8987 35.04782, -119.8988 35.04744, -119.8989 35.04706, -119.899 35.04667, -119.8991 35.04595, -119.8991 35.04557, -119.8991 35.04518, -119.8991 35.0448, -119.8991 35.04441, -119.899 35.04403, -119.899 35.04365, -119.8989 35.04328, -119.8987 35.0429, -119.8986 35.04254, -119.8984 35.04218, -119.8982 35.04183, -119.898 35.04149, -119.8978 35.04116, -119.8975 35.04084, -119.8972 35.04053, -119.8969 35.04023, -119.8966 35.03995, -119.8963 35.03968, -119.8959 35.03942, -119.8955 35.03918, -119.8952 35.03896, -119.8948 35.03875, -119.8944 35.03856, -119.8939 35.03839, -119.8935 35.03824, -119.8931 35.0381, -119.8926 35.03799, -119.8922 35.03789, -119.8917 35.03781, -119.8912 35.03776, -119.8908 35.03772, -119.8903 35.0377, -119.8898 35.03771, -119.8894 35.03773, -119.8889 35.03777, -119.8884 35.03784, -119.888 35.03792, -119.8861 35.0383, -119.8856 35.03841))",
 "Year is greater than or equal to 2001",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 19 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021171-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kz6w8g
title: Occurrence Download

description: A dataset containing 1714 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Brazil",
 "TaxonKey is Ameiva ameiva"
 ]
}

 The dataset includes 1714 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021175-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3xfdnr
title: Occurrence Download

description: A dataset containing 1694 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Compilación de fonoteca de referencia de murciélagos insectívoros de México: Fase I",
 "Geometry POLYGON((-132.06491 11.47918,-71.93509 11.47918,-71.93509 35.52082,-132.06491 35.52082,-132.06491 11.47918))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1694 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0021174-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.16961281
title: Online Data: Black-hole mass estimation through accretion disk spectral fitting for high-redshift blazars

description: # High-z Blazar SED Fitting Results

This package contains archival data, MCMC fitting results, and Python scripts for modeling the spectral energy distributions (SEDs) of high-redshift blazars. It is designed to allow reproduction of the analysis and generation of plots for individual sources.

---

## 📂 Contents of the ZIP folder

- **DLAcoeff.txt**, **LAFcoeff.txt**    Coefficients used in the analytical model of Inoue et al. (2014), MNRAS, 442 for the effective opacity to neutral hydrogen in the IGM (https://ui.adsabs.harvard.edu/abs/2014ascl.soft02019I)    - **sources.txt**   List of sources in the sample (columns: `id`, `name`, `redshift`, `model` [1 = single-component, 2 = two-component]).

- **1.txt – 23.txt**  Archival observations (photometric data) for each source in the sample.

- **\*.h5**    MCMC fitting results stored with `emcee.backends.HDFBackend`.

- **functions.py**    Helper functions used by script.py    - **script.py**  Main plotting script. Run with:  ```bash  python script.py [you will be prompted to enter the source id you wish]  ⚙️ Requirements

This code depends on the following Python packages:

    numpy

    pandas

    matplotlib

    scipy

    emcee

    corner

    astropy

    (Python ≥ 3.8 recommended)    ▶️ Usage

    Select a source of interest from sources.txt (using the id column).

    Run the plotting script with the source ID:    python script.py    You will be prompted to enter the ID of a source.        You will be prompted to enter a number (1-4) for the plot you wish to create (Type 1: chain plot, Type 2: corner plot, Type 3: SED plot, Type 4: All).    Output plots are saved in the current directory (or in a plots/ folder, if present).

📊 Outputs

    Corner plots of posterior distributions (from MCMC fits).        SED plots with archival photometry and model results.    The code also applies IGM attenuation using the supplied LAFcoeff.txt and DLAcoeff.txt.

🆕 **What’s new in Version 2**

    🔭 Updated source list.      ⚙️ Improved jet/disk model implementation.      📈 MCMC fitting results recalculated using longer chains.  

📚 Citation

If you use this material in your work, please cite:Kyriopoulos et al. arxiv (submitted)
DOI: 10.5281/zenodo.17781963
title: Online Data: Black-hole mass estimation through accretion disk spectral fitting for high-redshift blazars

description: # High-z Blazar SED Fitting Results

This package contains archival data, MCMC fitting results, and Python scripts for modeling the spectral energy distributions (SEDs) of high-redshift blazars. It is designed to allow reproduction of the analysis and generation of plots for individual sources.

---

## 📂 Contents of the ZIP folder

- **DLAcoeff.txt**, **LAFcoeff.txt**    Coefficients used in the analytical model of Inoue et al. (2014), MNRAS, 442 for the effective opacity to neutral hydrogen in the IGM (https://ui.adsabs.harvard.edu/abs/2014ascl.soft02019I)    - **sources.txt**   List of sources in the sample (columns: `id`, `name`, `redshift`, `model` [1 = single-component, 2 = two-component]).

- **1.txt – 23.txt**  Archival observations (photometric data) for each source in the sample.

- **\*.h5**    MCMC fitting results stored with `emcee.backends.HDFBackend`.

- **functions.py**    Helper functions used by script.py    - **script.py**  Main plotting script. Run with:  ```bash  python script.py [you will be prompted to enter the source id you wish]  ⚙️ Requirements

This code depends on the following Python packages:

    numpy

    pandas

    matplotlib

    scipy

    emcee

    corner

    astropy

    (Python ≥ 3.8 recommended)    ▶️ Usage

    Select a source of interest from sources.txt (using the id column).

    Run the plotting script with the source ID:    python script.py    You will be prompted to enter the ID of a source.        You will be prompted to enter a number (1-4) for the plot you wish to create (Type 1: chain plot, Type 2: corner plot, Type 3: SED plot, Type 4: All).    Output plots are saved in the current directory (or in a plots/ folder, if present).

📊 Outputs

    Corner plots of posterior distributions (from MCMC fits).        SED plots with archival photometry and model results.    The code also applies IGM attenuation using the supplied LAFcoeff.txt and DLAcoeff.txt.

🆕 **What’s new in Version 2**

    🔭 Updated source list.      ⚙️ Improved jet/disk model implementation.      📈 MCMC fitting results recalculated using longer chains.  

📚 Citation

If you use this material in your work, please cite:Kyriopoulos et al. arxiv (submitted)
DOI: 10.17026/ar/byl7rh
title: PAN-00167281 - crowbar

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00167281&lt;/p&gt;
description: Modified: 2025-04-30T15:54:40+02:00
DOI: 10.5683/sp3/zfcfjh
title: Research strategies on non-invasive brain stimulation on gait and corticospinal plasticity in children and adolescents with brain injury / Stratégies de recherche sur la stimulation cérébrale non invasive sur la démarche et la plasticité corticospinale chez les enfants et les adolescents atteints de lésions cérébrales

description: This dataset contains search strategies for MEDLINE All (Ovid), Embase (Ovid), Cochrane Central (Ovid), Cochrane DSR (Ovid), CINAHL Complete (EBSCOhost), SportDiscus with Full Text (EBSCOhost), and Web of Science Core Collection (Clarivate). When run in their respective databases, these strategies retrieve articles on the concepts of non-invasive brain stimulation (NIBS), cerebral palsy (CP) or acquired brain injury, gait, and pediatric population. The number of results and search strategies for each database are indicated in the rtf file(s). The searches were conducted on on February 8, 2025. / Ce jeu de données contient les stratégies de recherche pour MEDLINE All (Ovid), Embase (Ovid), Cochrane Central (Ovid), Cochrane DSR (Ovid), CINAHL Complete (EBSCOhost), SportDiscus with Full Text (EBSCOhost), and Web of Science Core Collection (Clarivate). Quand on les exécute dans leurs bases de données respectives, ces stratégies repèrent les articles sur les concepts de stimulation cérébrale non invasive (NIBS), paralysie cérébrale (PC) ou lésion cérébrale acquise, la démarche et population pédiatrique. Le nombre de résultats et les stratégies de recherche pour chaque base de données sont indiqués dans le.s fichier.s rtf. Les recherches ont été effectuées le 8 février 2025.