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NCSRD-DS-5GDDoS: 5G Radio and Core metrics containing sporadic DDoS attacks
<p><strong>NCSRD-DS-5GDDos v3.0 Dataset</strong><br>===<br>NCSRD-DS-5GDDos is a comprehensive dataset recorded in a real-world 5G testbed that aligns with the 3GPP specifications. The dataset captures Distributed Denial of Service (DDoS) attacks initiated by malicious connected users (UEs). </p> <p>The setup comprises of 3 cells with a total of 9 UEs connected to the same core network. The 5G network is implemented by the Amarisoft Callbox Mini solution (cell 2), and we further employ a second cell using the Amarisoft Classic (cell 1 & 3), that also hosts the 5G core.</p> <p>The setup utilizes a broad set of UE devices comprising a set of smart phones (Huawei P40), microcomputers (Raspberry Pi 4 - Waveshare 5G Hat M2), industrial 5G routers (Industrial Waveshare 5G Router), a WiFi-6 mobile hotspot (DWR-2101 5G Wi-Fi 6 Mobile Hotspot) and a CPE box (Waveshare 5G CPE Box). All UEs are being operated by subsidiary hosts which are responsible for the traffic generation, occurring from scheduled communications times.</p> <p>All identifiers are artificially generated and do not represent or based on personal data. We identify each UE through its ‘imeisv’ ID, that corresponds to the device in use, due to vendor implementation, that uses the same IMSI for all UEs.</p> <p>This dataset captures attack data from a total of 5 malicious User Equipment (UE) devices that initiated various flooding attacks on a 5G network. Each record includes key identifiers such as the IMEISV (International Mobile Equipment Identity Software Version number) and IP address of the attacking UE, along with the device type. The file "summary_report.csv" summarizes this information. The traffic types used in the attacks include syn flooding, UDP flooding, ICMP flooding, DNS flooding, and GTP-U flooding. The benign users stream YouTube and Skype traffic.</p> <p>The dataset is recorded through the use of a data collector that interfaces with the 5G network and gathers data regarding UEs, gNBs and the Core Network. The data are recorded in an InfluxdB and pre-processed into three separate tabular .csv files for more efficient processing: “amari_ue_data.csv”, “enb_counters.csv” and “mme_counters.csv”. In this version, we use an Amarisoft Classic (cells 1 & 3, Core Network) and an Amarisoft Mini (cell 2) (more information on the products can be found in https://www.amarisoft.com/).</p> <p>The ”amari_ue_data.csv” provides information on the UEs regarding identification (“imeisv”, “5g_tmsi”, “rnti”), IP addressing, bearer information, cell information (“tac”, “ran_plmn”), and cell information (“ul_bitrate”, “dl_bitrate”, “cell_id”, retransmissions per user per cell “ul_retx” as well as aggregated bit rates for each cell).</p> <p>The ”enb_counters.csv” focuses on cell-level information, providing downlink and uplink bitrates, usage ratio per user, cpu load of the gNB.</p> <p>We provide separate files of ”amari_ue_data.csv” and ”enb_counters.csv” generated from each gNB (Amarisoft Classic and Mini).</p> <p>The “mme_counters.csv” provides information on the Non-Access Stratum (NAS) of the 5G Network and focuses on session status reports (e.g., number of PDU session establishments, paging, context setup. This part gives an overview of the connection management throughout the recording session, and provides information on features suggested by 3GPP for abnormal user behavior.</p> <p>We also provide a separate pre-processed dataset, that merges the two "amari_ue_data_*.csv" file, including labeling of the malicious/benign samples, and may be more flexible for interested data scientists.</p> <p>Please refer to README.txt for the features included in each file.</p> <p>If you use this dataset, please also cite the following papers:</p> <p>M. Christopoulou, A. Garos, A. Vekraki, D. Santorinaios, I. Koufos, S. Karamitsiani, G. Xilouris, M.-A. Kourtis, G. Gardikis, and P. Trakadas, “User Terminals as Attackers: An Open Dataset Analysis of DDoS Attacks in 5G Networks,” in Proc. 2024 IEEE Conf. Standards Commun. Netw. (CSCN), 2024, pp. 301–307, doi: 10.1109/CSCN63874.2024.10849694.</p> <p>G. Xylouris, A. Vekraki, M. Christopoulou, M. A. Kourtis, E. K. Markakis and P. Trakadas, "Advancing Predictive Security for Consumer Applications in Beyond 5G/6G Networks With Annotated Datasets," in IEEE Transactions on Consumer Electronics, doi: 10.1109/TCE.2025.3567151.</p>
Humidity and temperature influence on the self-cleaning performance of building materials containing the photocatalysts
<p>Datasets for article Humidity and temperature influence on the self-cleaning performance of building materials containing the photocatalysts</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 1: Operational scenario with 6.0 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 1. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p> <p> </p> <p> </p> <p> </p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 2: Operational scenario with 4.5 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 2. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 8: Damaged scenario with 1.5 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 8. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 7: Damaged scenario with 3.0 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 7. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 5: Damaged scenario with 6.0 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 5. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 6: Damaged scenario with 4.5 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 6. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 4: Operational scenario with 1.5 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 4. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
Deliverable 1.1.1.1 BEL-Float project | Dataset containing the results of numerical simulations (motions, forces) of the operational performance analysis - Part 3: Operational scenario with 3.0 m significant wave height
<p>This dataset contains the results of OpenFAST simulations performed on the DeepCwind OC4 semi-submersible combined with the 5MW NREL turbine for various wind and wave conditions. The basis of the OpenFAST input files are taken from <a href="https://github.com/OpenFAST/r-test/tree/main/glue-codes/openfast/5MW_OC4Semi_WSt_WavesWN">OpenFAST r-test GitHub repository (5MW_OC4Semi_WSt_WavesWN)</a> and adapted to simulate various wind and wave conditions. The turbulent wind field as the input to the InflowWind module is generated using <a href="https://www.nrel.gov/wind/nwtc/turbsim.html">TurbSim</a>. The simulations are performed on a modified version of OpenFAST v3.5.3 to which adaptation to the code is made to extract additional Morison drag output up to 16 cylindrical members. This adapted code is <a href="https://github.com/abkpribadi/openfast/tree/Morison_additional_output">uploaded on GitHub as a branch from a forked OpenFAST repository</a>. In total there are 1152 simulation results consists of 768 irregular waves and 384 regular waves cases. The complete dataset is divided into 9 sub-datasets to which this is part number 3. A report describing this dataset is available on the BEL-Float project website: https://www.owi-lab.be/bel-float.</p>
A New Comprehensive Annotation of Leucine-Rich Repeat-Containing Receptors in Rice
<p>Datasets for preprint (https://doi.org/10.1101/2021.01.29.428842) entitled "<strong>A new comprehensive Annotation of Leucine-Rich Repeat-Containing Receptors in Rice</strong>".</p> <p>This paper describes an in-depth manual curation of LRR-CR annotations including genes containing nonsense mutations, tagged as 'non-canonical', by opposition to 'canonical', that have expected gene models.</p> <p> </p> <p>Contains 7 files for each rice cultivar:</p> <p>- domain annotation for each LRR-CR protein (xxx_LRR_domains_filtered.csv)</p> <p>- gff file containing LRR-CR gene model annotations</p> <p>- fasta file (1): the complete genes 'gene' (nucleotide sequence, exons and introns)</p> <p>- fasta file (2): the coding sequences 'CDS' (nucleotide sequence, exons, translatable). Note that for genes experiencing frameshift, the one or two bases that cause the frameshift are avoided in order to have nucleotide sequence that can be translated. Terminal and in frame stop codons are encoded by a '*'.</p> <p>- fasta file (3): protein sequences 'PEP' (amino acid sequence, exons, corresponding to translation of CDS (2) )</p> <p>- fasta file (4): 'cDNA' (nucleotide sequence, exons). Note that for genes experiencing frameshift, the translated protein sequence will not correspond to the one present in the file (3). For all other genes, the files "CDS" and "cDNA" retrieve the same nucleotide sequences.</p> <p>- fasta file (5): 'cDNA_wFrameshit' (nucleotide sequence, exons) : same sequences than in (4) except for genes experiencing frameshift whose sequences are completed with one or two "!" characters at the position of the frameshift in order to conserve the right reading frame (also used by V. Ranwez et al. for the MACSE programs <a href="https://dx.doi.org/10.1093/molbev/msy159">https://dx.doi.org/10.1093/molbev/msy159</a> ).</p> <p> </p>
How can software containers help your research?
<p>This video explains software containers to a research audience. It is an introduction to why containers are beneficial for research. These benefits are standardisation, portability, reliability and reproducibility. </p> <p>Software Containers in research are a solution that addresses the challenge of a replicable computational environment and supports reproducibility of research results. Understanding the concept of software containers enables researchers to better communicate their research needs with their colleagues and other researchers using and developing containers.</p> <p><strong>Watch the video here: <a href="https://www.youtube.com/watch?v=HelrQnm3v4g">https://www.youtube.com/watch?v=HelrQnm3v4g</a></strong></p> <p>If you want to share this video please use this:</p> <p>Australian Research Data Commons, 2021. <em>How can software containers help your research?</em>. [video] Available at: <a href="https://www.youtube.com/watch?v=HelrQnm3v4g">https://www.youtube.com/watch?v=HelrQnm3v4g</a> DOI: <a href="http://doi.org/10.5281/zenodo.5091260">http://doi.org/10.5281/zenodo.5091260</a> [Accessed dd Month YYYY].</p>
Diverse arsenic-containing lipids in the surface ocean
<p>Arsenic is present at nanomolar levels throughout the ocean, and microbes assimilate this potentially toxic element due to its similarity to inorganic phosphorus. Although dissolved arsenic has been a focus of several oceanographic studies, the size and chemical character of the particulate arsenic pool is poorly understood. We measured particulate arsenic in five samples from the open ocean and determined the contribution of arsenic-containing lipids to this pool. Here we show that the accumulation of arsenic into lipids is a widespread phenomenon in the surface ocean. Particulate arsenic concentrations were 15 to 42 pmol L<sup><span>−</span>1</sup> with 7–20% of the particulate arsenic pool within arsenolipids. We found that arsenosugar phospholipids dominated the arsenolipid pools in our samples with a minor component of arsenohydrocarbons and other unidentified lipids. A significant portion of the arsenosugar phospholipids (up to 35%) were present as previously undescribed mixed acyl ether lipids, suggesting a bacterial source.</p>
FIG. 8. — Left mandible containing p in Pliocene suids from Musaitu and Dermenji, Moldova: implications for understanding the origin of African Kolpochoerus Van Hoepen & Van Hoepen, 1932
FIG. 8. — Left mandible containing p/2-m/2, from Perpignan, France (CCECL Pp 195), lectotype of "Sus" minor (Depéret, 1890) (Azzaroli 1954): A, stereo triplet of the occlusal view (note the thickness of the mandible despite the juvenile status of the jaw; B, buccal view; C, lingual view. Scale bar: 10 mm.
FIG. 7. — Right mandible containing d in Pliocene suids from Musaitu and Dermenji, Moldova: implications for understanding the origin of African Kolpochoerus Van Hoepen & Van Hoepen, 1932
FIG. 7. — Right mandible containing d/2-m/1 of Dasychoerus arvernensis (Croizet & Jobert, 1828) from Les Étouaires, part of the holotype (http://coldb.mnhn. fr/CatalogNumber/MNHN/F/PET2005, specimen labelled "Étouaires"): A, lingual view; B, stereo triplet of the occlusal view; C, buccal view. Scale bar: 10 mm
FIG. 2. — Left maxilla containing D2 in Pliocene suids from Musaitu and Dermenji, Moldova: implications for understanding the origin of African Kolpochoerus Van Hoepen & Van Hoepen, 1932
FIG. 2. — Left maxilla containing D2/-D4/ and M1/, part of the holotype of Dasychoerus arvernensis (Croizet & Jobert, 1828), from Les Étouaires, Perrier, France (MNHN.F.PET2005, specimen labelled "Étouaires"): A, stereo triplet of the occlusal view; B, lingual view; C, buccal view. Scale bar: 10 mm.
Text-fig. 5. Fossil mammals from the Oligocene of Djebel Bou Gobrine, Tunisia, stored in the ONM Museum, El Charguia, Tunis. a–b) (?)Phiomia sp. maxilla containing parts of two upper molars (probably M1/ and M2/) (a – occlusal view, b – buccal view); c–d) anthracothere distal tibia in coarse sand matrix (c – plantar view, d – distal view) (all in scale). in Arsinoitherium (Embrithopoda) And Other Large Mammals And Plants From The Oligocene Of Tunisia
Text-fig. 5. Fossil mammals from the Oligocene of Djebel Bou Gobrine, Tunisia, stored in the ONM Museum, El Charguia, Tunis. a–b) (?)Phiomia sp. maxilla containing parts of two upper molars (probably M1/ and M2/) (a – occlusal view, b – buccal view); c–d) anthracothere distal tibia in coarse sand matrix (c – plantar view, d – distal view) (all in scale).
Text-fig. 2. Generalised stratigraphy of the area including the fossil site in Orta-Şabanözü (Sengüler 2007). The coloured formation is Hüyükköy Formation, aged as late Miocene and containing fossil woods. in The First Glyptostroboxylon And Taxodioxylon Descriptions From The Late Miocene Of Turkey And Palaeoclimatological Evaluation
Text-fig. 2. Generalised stratigraphy of the area including the fossil site in Orta-Şabanözü (Sengüler 2007). The coloured formation is Hüyükköy Formation, aged as late Miocene and containing fossil woods.
Text-fig. 53. Scanning electron microscope (SEM) images of tricolpate pollen of Nicholsia brevicolpites gen. et sp. nov. from a coprolite containing several kinds of pollen; Torres Vedras locality, Portugal. a) Detail of the coprolite that yielded the tricolpate pollen in this Text-figure showing several different kinds of pollen grains; b–d) Tricolpate pollen grains in polar (b) and equatorial (c, d) views showing colpi, coarsely granular aperture membrane and foveolate tectum. Specimen, TV44-S137906-03 (holotype; a–d). Scale bars 30 Μm (a), 6 Μm (b–d). in The Early Cretaceous Mesofossil Flora Of Torres Vedras (Ne Of Forte Da Forca), Portugal: A Palaeofloristic Analysis Of An Early Angiosperm Community
Text-fig. 53. Scanning electron microscope (SEM) images of tricolpate pollen of Nicholsia brevicolpites gen. et sp. nov. from a coprolite containing several kinds of pollen; Torres Vedras locality, Portugal. a) Detail of the coprolite that yielded the tricolpate pollen in this Text-figure showing several different kinds of pollen grains; b–d) Tricolpate pollen grains in polar (b) and equatorial (c, d) views showing colpi, coarsely granular aperture membrane and foveolate tectum. Specimen, TV44-S137906-03 (holotype; a–d). Scale bars 30 Μm (a), 6 Μm (b–d).
Text-fig. 3. a–g, i, j: Quinquala obovata gen. et sp. nov., fruits from Wyoming and Oregon. a, b: Kisinger Lakes flora, Wyoming. a: Enlarged lateral view of split wing displaying venation along outer edge. Note the seed present in the locular area (arrow). UF 19376-60023b. b: Enlarged lateral view of split wing containing seeds within the locular area (arrow). UF 19376-60023c. c: Lateral view of fruit from White Cliffs, Oregon. UF 262-17690. d: Lateral view of fruit from West Branch Creek, Oregon. UF 229-53091. in Winged Fruits Of Rutaceous Affinity From The Eocene Of Western North America
Text-fig. 3. a–g, i, j: Quinquala obovata gen. et sp. nov., fruits from Wyoming and Oregon. a, b: Kisinger Lakes flora, Wyoming. a: Enlarged lateral view of split wing displaying venation along outer edge. Note the seed present in the locular area (arrow). UF 19376-60023b. b: Enlarged lateral view of split wing containing seeds within the locular area (arrow). UF 19376-60023c. c: Lateral view of fruit from White Cliffs, Oregon. UF 262-17690. d: Lateral view of fruit from West Branch Creek, Oregon. UF 229-53091.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research 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.
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.
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.
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.
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.