Find research datasets worth reusing

opencc-by-4.0Aug 2024View details →

Harmonization of experimental procedures to assess mitochondrial respiration in human permeabilized skeletal muscle fibers

DatLab files of the experiments included in the "Harmonization of experimental procedures to assess mitochondrial respiration in human permeabilized skeletal muscle fibers" manuscript (<a href="https://doi.org/10.1016/j.freeradbiomed.2024.07.039" target="_blank" rel="noopener">https://doi.org/10.1016/j.freeradbiomed.2024.07.039</a>).

opencc-by-4.0Aug 2024View details →

Spherical Harmonic Coefficients from the SVM by Tsunakawa

Spherical harmonic coefficients from the surface vector mapping (SVM) by Tsunakawa et al. (2015) in JGR-Planet

opencc-by-4.0Oct 2024View details →

TRY 6.0 - Species List from Taxonomic Harmonization – Matches with World Flora Online version 2023.12

Standardized names for TRY 6.0 are available from the TRY File Archive (TFA; see here: <a href="https://www.try-db.org/TryWeb/Data.php#100">https://www.try-db.org/TryWeb/Data.php#100</a>); these were created for the following publication: Schellenberger Costa, D., Boehnisch, G., Freiberg, M., Govaerts, R., Grenié, M., Hassler, M., Kattge, J., Muellner-Riehl, A.N., Rojas Andrés, B.M., Winter, M., Watson, M., Zizka, A. and Wirth, C. (2023), The big four of plant taxonomy – a comparison of global checklists of vascular plant names. New Phytol, 240: 1687-1702. <a href="https://doi.org/10.1111/nph.18961">https://doi.org/10.1111/nph.18961</a> Here matched records are provided with the taxonomic backbone of World Flora Online (WFO) version 2023.01, obtained from <a href="https://zenodo.org/records/10425161">https://zenodo.org/records/10425161</a>. Matches with WFO are given in the Zenodo archive in the fields for SID (=taxonID in WFO), scientificName (as in WFO) and scientificNameAuthorship (as in WFO). Fields of TRY_SpeciesID, TRY_AccSpeciesNameScientific and RecommendedScientificName were directly obtained from the TFA.   Matching was done via following steps: 1. Fungi matched in the TFA via the <a href="http://indexfungorum.org">http://indexfungorum.org</a>  were excluded (4,099 records). 2. The matching record in WFO was obtained by matching the TFA field of TPL_ID with the WFO field of tplID. Successful matches via this method are indicated in this Zenodo archive by the field of MATCH being set to TPL ID. 3. Where matches in WFO included a non-empty acceptedNameUsageID, the currently accepted name of the taxon was obtained via this ID. Successful matches via this method are indicated in this Zenodo archive by the field of MATCH being set to TPL ID and fields of synonymID, scientificName.synonym and scientificNameAuthorship.synonym showing details for the match with the synonym. 4. Taxa that were not matched in previous steps were matched for the TFA field of MatchedName. Matching was done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>). Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of MATCH being set to manual. Taxa at specific and infraspecific levels from the TFA where matches had only been achieved at generic levels for the MatchedName were excluded in this step. 5. Taxa that were not matched in previous steps were matched for the TFA field of TRY_AccSpeciesName. Matching was done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>). Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of MATCH being set to manual. 6. Taxa that were not matched in previous steps were matched for the TFA field of AlternativeName. Matching was done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>). Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of MATCH being set to manual. 7. Taxa that were not matched in previous steps were matched for the TFA field of MatchedName against <a href="https://sftp.kew.org/pub/data-repositories/WCVP/Archive/">version 11 of the World Checklist of Vascular Plants</a>. Matching was also done via the <a href="https://cran.r-project.org/package=WorldFlora">WorldFlora package</a> version 1.14-5 (<a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">Kindt 2020</a>), with similar scripts <a href="https://rpubs.com/Roeland-KINDT/1134151">as shown in this Rpub</a>. Matches expected to be acceptable after visual inspection are indicated in this Zenodo archive by the field of MATCH being set to manual and by the field of SID (and possibly synonymID) containing records where the WCVP ID is preceded by WCVP-. 8.  836 records where neither the TFA nor the previous steps managed to establish a match were removed. 9.  Taxa that could not be matched in previous steps are flagged by the field of MATCH being set to NONE - no species MatchedName (where TFA also did not achieve a match at the required specific or infraspecific level) or NONE (other records where no match was achieved).   The Zenodo archive contains 406,208 records with matches via the TPL, 96,040 records with manual matches, 1,822 records where the TFA also not achieve matches at required (infra-)specific levels and 361 records where no match was achieved (among this latter category were 202 records flagged in TFA as ‘not found in WFO’ and 140 records flagged in TFA as ‘found only here’).   Version 2024.10b was created with added fields from TFA of TRY_SpeciesName and BackboneDatabase. This was done especially to explain different matches for records with the same RecommendedScientificName but with different matches to WFO, as for example for Acacia adunca A.Cunn. & G.Don and Acacia aestivalis E.Pritz.   References <ul> <li>Kattge J. 2023. TRY 6.0 - Species List from Taxonomic Harmonization. <a href="https://www.try-db.org/TryWeb/Data.php#100">https://www.try-db.org/TryWeb/Data.php#100</a></li> <li>Schellenberger Costa, D., Boehnisch, G., Freiberg, M., Govaerts, R., Grenié, M., Hassler, M., Kattge, J., Muellner-Riehl, A.N., Rojas Andrés, B.M., Winter, M., Watson, M., Zizka, A. and Wirth, C. (2023), The big four of plant taxonomy – a comparison of global checklists of vascular plant names. New Phytol, 240: 1687-1702. <a href="https://doi.org/10.1111/nph.18961">https://doi.org/10.1111/nph.18961</a></li> <li>The World Flora Online Consortium, Alan Elliott, Roger Hyam, William Ulate, Mark Watson, Gregory Anderson, Giovani carlos Andrella, et al. “World Flora Online Plant List December 2023”. Zenodo, December 22, 2023. <a href="https://doi.org/10.5281/zenodo.10425161" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10425161</a>.</li> <li>Kindt R (2020). “WorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone data.” Applications in Plant Sciences, 8(9), e11388. <a href="https://doi.org/10.1002/aps3.11388">https://doi.org/10.1002/aps3.11388</a></li> <li>Borsch, T., Berendsohn, W., Dalcin, E., Delmas, M., Demissew, S., Elliott, A., Fritsch, P., Fuchs, A., Geltman, D., Güner, A., Haevermans, T., Knapp, S., le Roux, M.M., Loizeau, P.-A., Miller, C., Miller, J., Miller, J.T., Palese, R., Paton, A., Parnell, J., Pendry, C., Qin, H.-N., Sosa, V., Sosef, M., von Raab-Straube, E., Ranwashe, F., Raz, L., Salimov, R., Smets, E., Thiers, B., Thomas, W., Tulig, M., Ulate, W., Ung, V., Watson, M., Jackson, P.W. and Zamora, N. (2020), World Flora Online: Placing taxonomists at the heart of a definitive and comprehensive global resource on the world's plants. TAXON, 69: 1311-1341. <a href="https://doi.org/10.1002/tax.12373">https://doi.org/10.1002/tax.12373</a></li> <li>Govaerts, R., Nic Lughadha, E., Black, N. et al. The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. Sci Data 8, 215 (2021). <a href="https://doi.org/10.1038/s41597-021-00997-6">https://doi.org/10.1038/s41597-021-00997-6</a></li> </ul>   The development of this archive supported by the Darwin Initiative to project DAREX001 of Developing a Global Biodiversity Standard certification for tree-planting and restoration, by Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the Provision of Adequate Tree Seed Portfolio project in Ethiopia, by the Green Climate Fund through the IUCN-led Transforming the Eastern Province of Rwanda through Adaptation project and through the Readiness proposal on Climate Appropriate Portfolios of Tree Diversity for Burkina Faso, by the Bezos Earth Fund to the Bezos Quality Tree Seed for Africa in Kenya and Rwanda project and by the German International Climate Initiative (IKI) to the regional tree seed programme on The Right Tree for the Right Place for the Right Purpose in Africa.

opencc-by-4.0Jul 2021View details →

DDISH-GI: Dynamic Distributed Spherical Harmonics Global Illumination - Supplementary Video

A supplementary video for the upcoming publication "DDISH-GI: Dynamic Distributed Spherical Harmonics Global Illumination". The video includes a comparison to a state-of-the-art method and also to the path traced ground truth. Limitations of the proposed method are also shown.

opencc-by-4.0Aug 2020View details →

RHARM (Radiosounding HARMonization) dataset - subset

In the context of the Copernicus Climate Change Service (C3S), a novel approach, named RHARM (Radiosounding HARMonization), has been developed to provide a harmonized dataset of temperature, humidity and wind profiles along with an estimation of the measurement uncertainties for about 650 radiosounding stations globally.  The RHARM method is applied to the Integrated Global Radiosonde Archive (IGRA) Version 2 which is the most comprehensive collection of historical and near-real-time radiosonde and pilot balloon observations from around the globe, maintained and distributed by the National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI). The daily (0000 and 1200 UTC) radiosonde data holdings on 16 standard pressure levels (from 1000 to 10 hPa) from 1978 to present are post-processed or statistically homogenized using the RHARM approach. The applied adjustments are interpolated to all reported significant levels to retain information content contained within each individual ascent profile.  The RHARM algorithm is the first to provide homogenized time series of temperature, relative humidity and wind profiles alongside an estimation of the observational uncertainty for each single observation at each pressure level.  A copy of the RHARM dataset is stored in the Copernicus Climate Data Store (CDS) although not publicly available yet. For review purposes only, a subset has been made available here.

opencc-by-4.0Oct 2021View details →

A Spherical Harmonic model of Earth's lithospheric magnetic field up to degree 1050

This model describes the Earth's vector lithospheric (or crustal ) magnetic field to about 40-km spatial resolution. It is provided in the form of Spherical Harmonic (SH) Gauss coefficients using the norm commonly used in geomagnetism (the Schmidt normalization). The file is in (zipped) ascii with 4 columns: the SH degree, the SH order, the Gnm and the Hnm parameters. The model was obtain after selecting and processing magnetic field measurements from the German CHAMP and ESA Swarm satellites that were merged with worldwide near-surface scalar anomaly data compiled over decades. A description of the scientific procedure and the model assessments are described in a paper under publication at Geophysical Research Letters. Please consider citing the GRL paper: Thébault E., Hulot G., Langlais B., and Vigneron P., A Spherical Harmonic model of Earth’s lithospheric magnetic field up to degree 1050, Geophys. Res. Lett., 2021

opencc-by-4.0Aug 2022View details →

Dataset for the publication "Evaluation of Voltage Transformers' Accuracy in Harmonic and Interharmonic Measurement"

This is dataset for paper published: G. Crotti, G. D’Avanzo, C. Landi, P. S. Letizia and M. Luiso, "Evaluation of Voltage Transformers’ Accuracy in Harmonic and Interharmonic Measurement," in IEEE Open Journal of Instrumentation and Measurement, vol. 1, pp. 1-10, 2022, Art no. 9000310, doi: 10.1109/OJIM.2022.3198473.

opencc-by-4.0Aug 2022View details →

Dataset: Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System

The dataset provided here is intended for publication - Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System. Direct use of our provided datasets is available from Zenodo, and the source code to generate the datasets is published in <a href="https://gitlab.com/dlr-ve/esy/open-brazilian-energy-data">Gitlab</a>. We describe the data collection process in detail and open source the code for data processing and analysis in our publication. The assembled dataset includes the following subcategories, as detailed in the methods section of our publication: i) geospatial data for Brazil, ii) aggregated grid network topology, iii) vRES potentials --- profile and installable generation capacity, iv) geographically installable capacity of biomass thermal plants, v) hydropower plants inflow, vi) existing and planned power generators with their capacity, vii) electricity load profile, viii) scenarios of sectoral energy demand and ix) cross-border electricity exchanges. This dataset is resolved geographically by Brazilian federal states, and time series data are resolved by hours, spanning 2012-2020. The dataset can be used as input to popular open energy system models such as PyPSA and any other modelling framework. We encourage you to contribute to improving the datasets.

opencc-zeroJan 2023View details →

Solid-state-like high harmonic generation from cluster molecules with rotational periodicities

High harmonic generation (HHG) from solid-state crystals in strong laser fields has been understood by the band structure of the solids, which is based on the periodic boundary condition (PBC) due to translational invariance. For the systems with PBC due to rotational invariance, an analogous Bloch theorem can be applied. Considering a ring-type cluster of cyclo[18]carbon as an example, we develop a quasi-band model and predict the solid state-like HHG in this system. Under the irradiation of linearly polarized laser field, cyclo[18]carbon exhibits solid-state-like HHG originated from intra-band oscillations and inter-band transitions, which in turn is promising to optically detect the symmetry and geometry of controversial structures. Our results based on the Liouville-von-Neumann equations are well reproduced by the time-dependent density functional theory calculations and are foundational in providing a connection linking the HHG physics of gases and solids.

opencc-by-sa-4.0Dec 2022View details →

WorldCereal open global harmonized reference data repository (CC-BY-SA licensed data sets)

Within the ESA funded WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets. This publication includes those harmonized data sets of which the original data set was published under the CC-BY-SA license or a license similar to CC-BY-SA. See document "_In-situ-data-World-Cereal - license - CC-BY-SA.pdf" for an overview of the original data sets.

opencc-by-4.0Dec 2022View details →

WorldCereal open global harmonized reference data repository (CC-BY licensed data sets)

Within the ESA funded WorldCereal project we have built an open harmonized reference data repository at global extent for model training or product validation in support of land cover and crop type mapping. Data from 2017 onwards were collected from many different sources and then harmonized, annotated and evaluated. These steps are explained in the harmonization protocol (10.5281/zenodo.7584463). This protocol also clarifies the naming convention of the shape files and the WorldCereal attributes (LC, CT, IRR, valtime and sampleID) that were added to the original data sets. This publication includes those harmonized data sets of which the original data set was published under the CC-BY license or a license similar to CC-BY. See document "_In-situ-data-World-Cereal - license - CC-BY.pdf" for an overview of the original data sets.

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Dataset related to article "Harmonization of sensorimotor deficit assessment in a registered multicentre pre-clinical randomized controlled trial using two models of ischemic stroke"

https://figshare.com/search?q=10.6084%2Fm9.figshare.21346731

opencc-by-4.0Dec 2022View details →

FIGURE 2 in Harmonizing taxon names in biodiversity data: A review of tools, databases and best practices

FIGURE 2 Taxonomy as a unifying key for ecological datasets. The two sides represent two exemplary datasets, with a containing conservation status of taxa (here species) and B their traits (colours show different traits). The datasets are indexed by taxon names 'Sp1' to 'Sp6'. The rounded rectangle in the middle depicts the taxonomic harmonization process: (a) the names are extracted from each dataset, respectively in the orange and purple rectangles; (b) both lists are then compared to a taxonomic database which harmonizes all names. Here the names 'Sp1' and 'Sp6' refer to the same taxon in the taxonomic database (as indicated by the dashed lines). Without taxonomic harmonization, the exact match of names would have resulted in the loss of Sp5 and Sp6 when merging both datasets. LC, NT, VU, and CR are abbreviations of Red List statuses, meaning least concern, not threatened, vulnerable, and critically endangered, respectively

FIGURE 1 in Harmonizing taxon names in biodiversity data: A review of tools, databases and best practices

FIGURE 1 Typology of taxonomic databases according to their taxonomic breadth and their spatial scale. The x-axis represents increasing taxonomic breadth from a single taxonomic group to no clear taxonomic restriction (e.g. considering all biota or all Eukaryota). The y-axis represents spatial scale from regional to global. Each box represents a specific type of taxonomic database, with examples. LCVP, Leipzig Catalogue of Vascular Plants; WorldFlora, World Flora Online; POWO, Plants of the World Online; GermanSL, German Simple List; Vascan, Database of Vascular Plants of Canada; WoRMS, World Register of Marine Species; CASD, Chinese Animal Scientific Database; COL, Catalogue of Life; GBIF, Global Biodiversity Information Facility; TAXREF, French Taxonomic Referential; FinBIF, Finnish Biodiversity Information Facility

FIGURE 4 in Harmonizing taxon names in biodiversity data: A review of tools, databases and best practices

FIGURE 4 Diagram of different taxonomic harmonization workflows. The workflows differ in the number of steps they consider and the databases they leverage on. Rounded rectangles are lists of taxon names while diamonds represent taxonomic databases against which the names are matched. The different colours used at step 2 represent different taxonomic groups

FIGURE 3 in Harmonizing taxon names in biodiversity data: A review of tools, databases and best practices

FIGURE 3 Screenshot showing the network view of taxharmonizexplorer. The left section shows a table of each of the nodes in the network to let the user select manually nodes of interest, the top part presents a summary of the information on the selected node in the network. The right section displays the relationships between packages (which depends on which other), between databases (how one populates another one) and between packages and databases (which packages access which databases)

openother-openJun 2023View details →

Harmory: the Harmonic Memory

The first release of Harmory contains ~26K harmonic segments from 1800 harmonic (~10% of ChoCo, corresponding to all the audio partitions). Out of all segments: 13667 (16%) correspond to the same pattern families, 66175 (53%) are pattern-friendly (they share non-trivial similarities with other segments), whereas 8176 (32%) are inherently unique (they are found in other songs).

publicJan 2023View details →

Solid-state-like high harmonic generation from cluster molecules with rotational periodicities

Open the record for dataset details and reuse information.

publicJan 2022View details →

Transient analysis of power loss density with time-harmonic electromagnetic waves in Debye media

Open the record for dataset details and reuse information.