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Dataset results
60 results for “relational database”
Database of local seismicity registered on ocean bottom seismometers (OBS). Database related to Bornstein et al. (accepted in Earth and Space Science), PICKBLUE
<p>We assembled a database of Ocean Bottom Seismometer (OBS) waveforms and manual P and S picks from local seismicity, on which we trained PickBlue, a deep-learning picker, using the seismometer data and the hydrophone channel. The dataset belongs to Bornstein et al. (accepted 2023 in Earth and Space Science). The picker and database are available in the SeisBench platform, allowing easy and direct application to OBS traces and hydrophone records.</p><p>The complete database is also accessible with SEISBENCH: <br><a href="https://seisbench.readthedocs.io">https://seisbench.readthedocs.io</a><br>SEISBENCH on github:<br><a href="https://github.com/seisbench">https://github.com/seisbench</a></p><p>Related paper:</p><p>Bornstein, T., Lange, D., Münchmeyer, J., Woollam, J., Rietbrock., A., Barcheck, G., Grevemeyer, I., Tilmann, F. (accepted 2023 in Earth and Space Science). PickBlue: Seismic phase picking for ocean bottom seismometers with deep learning, Earth and Space Science. </p>
GEroNIMO project EP database related to KERs
<p>European Patents dataset performed using <a href="http://www.lens.org">www.lens.org</a> free database for the 7 Key Exploitable Results (KER) identified on the Grant Agreement and selected keywords for GEroNIMO projects. Set up parameters included.</p>
Dataset: A database of near-field head-related transfer functions based on measurements with a laser spark source
<p>This is a database of near-field head-related transfer functions (HRTFs) of an artificial head, measured at four distances (0.2, 0.3, 0.4 and 0.5 m), with 49 positions recorded at each distance, for a total of 196 measurement points. The HRTFs were recorded using an acoustic pulse created by a laser-induced breakdown of air (LIB), which realizes a close to ideal, massless, monopole sound source. The repository contains the original measurement data (raw_data.zip), the derived HRTFs both with (NF_LIB_HRTF_LFE.sofa) and without (NF_LIB_HRTF_measured.sofa) a low-frequency extension (LFE) applied, as well as the MATLAB code used to process the measurement data and to apply the LFE (LIB_HRTF_DB.zip). The database is made publicly available to support future research into nearby sound localization, and virtual/augmented reality applications.</p> <p>Please see the accompanying paper for further details: Marschall et al. (2023), <a href="https://doi.org/10.1016/j.apacoust.2022.109173">A database of near-field head-related transfer functions based on measurements with a laser spark source</a>, Applied Acoustics. </p>
A Free Database of Head-Related Impulse Response Measurements in the Horizontal Plane with Multiple Distances (MAT-Version)
<p>Head related impulse response measurements with the KEMAR dummy head performed in an anechoic chamber with a resolution of 1°. The impulse responses are provided for different distances and are accompanied by headphone compensation filters.</p> <p>This entry stores the measurements in the MAT format for use in Matlab/Octave. The measurements are identical to the once stored in the SOFA format available at <a href="https://doi.org/10.5281/zenodo.55418">https://doi.org/10.5281/zenodo.55418</a></p>
A Free Database of Head-Related Impulse Response Measurements in the Horizontal Plane with Multiple Distances
<p>Head related impulse response measurements with the KEMAR dummy head performed in an anechoic chamber with a resolution of 1°. The impulse responses are provided for different distances and are accompanied by headphone compensation filters.</p> <p>For details have a look at README.md.</p> <p>The same measurement can be downloaded as MAT files at <a href="https://doi.org/10.5281/zenodo.4459911">https://doi.org/10.5281/zenodo.4459911</a></p> <p>This dataset is further described in (see the PDF file)</p> <p>H. Wierstorf, M. Geier, A. Raake, S. Spors - A Free Database of Head-Related<br> Impulse Response Measurements in the Horizontal Plane with Multiple Distances.<br> In 130th AES Conv. 2011, eBrief 6.</p> <p> </p>
Database of Cross-Linguistic Norms, Ratings, and Relations for Words and Concepts as CLDF dataset
<p>Cite the source of the dataset as:</p> <blockquote> <p>Tjuka, Annika, Robert Forkel, and Johann-Mattis List. 2022. Linking Norms, Ratings, and Relations of Words and Concepts Across Multiple Language Varieties. Behavior Research Methods 54. 864–884. DOI: 10.3758/s13428-021-01650-1</p> </blockquote>
SemFi - Finnish Semantic Database with Syntactic Relations
<p>SemFi is a semantic database for Finnish in which the words are linked to each other by the syntactic relations and their frequency in a big corpus.</p> <p>SemFi is based on the syntactic bigrams of The Finnish Internet Parsebank provided by Turku University.</p> <p>The semfi.db file is an SQLite database and it is the one that should be used. The results_json.zip is mainly intended for those who are interested in working with SemUr which is a translated version of SemFi.</p> <p>The previous version of this dataset has successfully been used in the hard AI task of creating Finnish poetry automatically. That data still powers the computationally creative system,<a href="http://runokone.cs.helsinki.fi/"> Poem Machine</a>.</p> <p>More information and an online UI to browse the data is available on <a href="https://mikakalevi.com/semfi">https://mikakalevi.com/semfi/</a>.</p> <p><strong>Cite as</strong></p> <p>Hämäläinen, Mika. (2018). <a href="https://helda.helsinki.fi//bitstream/handle/10138/282733/paper9.pdf?sequence=1">Extracting a Semantic Database with Syntactic Relations for Finnish to Boost Resources for Endangered Uralic Languages</a>. In The Proceedings of Logic and Engineering of Natural Language Semantics 15 (LENLS15)</p>
A multiple model high-resolution head-related impulse response database for aided and unaided ears (HDF5 format)
<p>The Multiple-Model High Resolution HRTF database is a collection of HRTFs measured using four different Head-and-Torso Simulators at high spatial resolution (2 degree azimuth and elevation). The data here is stored in HDF5 files, the SOFA files are published in a separate dataset <a href="https://zenodo.org/record/2582553">doi:10.5281/zenodo.2582553</a>.</p>
TF-Marker: A comprehensive manually curated database for transcription factors and related markers in specific cell and tissue types in human.
<p>Here, we developed the TF-Marker database (TF-Marker, http://bio.liclab.net/TF-Marker/) which is committed to a comprehensive manual curation of TFs and related markers with experimental evidence in specific cell and tissue types in human. Currently, through reviewing <strong>2,091</strong> published literature, we have manually classified TFs and related markers into five types according to their functions: 1) <strong>TF</strong>: TFs, which regulate the expression of markers; 2) <strong>T Marker</strong>: markers, which are regulated by TFs (TF and T Marker pairs can identify cell types more specifically); 3) <strong>I Marker</strong>: markers, which influence the activity of TFs (I Markers can also influence the development of specific cells and tissues); 4) <strong>TFMarker</strong>: TFs, which play roles as markers (TFMarkers are cell/tissue-specific TFs used as cell markers in biology experiments); and 5) <strong>TF Pmarker</strong>: TFs, which play roles as potential markers. By curating thousands of published literature, <strong>5,905</strong> entries including <strong>1,316</strong> TFs, <strong>1,092</strong> T Markers, <strong>473</strong> I Markers, <strong>1,600</strong> TFMarkers and <strong>1,424</strong> TF Pmarkers, were annotated in <strong>383</strong> cell types and <strong>95</strong> tissue types in human. Moreover, TF-Marker divided markers into disease markers and tissue/cell-specific markers. TF-Marker is an elaborate database, which provides TFs and related markers supported by experimental evidence. We believe TF-Marker will provide strong support for research into cell/tissue-specific TFs and related markers.</p>
Chinese Engineers Relational Database (CERD) Bi-monthly Export
<p><strong>This is a bi-monthly export.</strong></p> <p>CERD is a database of engineers from the Chinese Republican period (1912–1949). Based on various digitised historical sources, it is a prosopographic catalogue of individuals, their education and their employment, and the institutions connected with it. Most biographical events have geographical information attached to them. The data can be used freely by researchers to answer individual research questions.</p> <p><strong>Citation recommendation:</strong></p> <p>Pelzer, Thorben, et al., eds. (2021–2023). Chinese Engineers Relational Database (CERD) (Version 1.7.0). Zenodo. http://doi.org/10.5281/zenodo.4075601.</p> <p><strong>Changelog:</strong></p> <p>1.7.0 (February 2023): Approx. 17,600 individuals, two additional sources<br> 1.6.0 (August 2022): Approx. 17,400 entries, completed sources, minor corrections, mergers, translations<br> 1.5.0 (June 2022): Approx. 17,300 entries, added additional memberships<br> 1.4.0 (April 2022): Approx. 16,800 entries, added additional sources, schooling<br> 1.3.0 (February 2022): Approx. 16,500 entries, added documentation, additional memberships<br> 1.2.0 (December 2021): Approx. 16,300 entries, added frequent CSV exports, source annotations, 5 missing <em>minglu</em> pages, additional association memberships<br> 1.1.0 (October 2021): Approx. 15,700 entries, added selected association memberships<br> 1.0.0 (August 2021): Approx. 15,400 entries [complete <em>gongchengren minglu</em> dataset milestone]<br> 0.5.0 (June 2021): Approx. 13,000 entries<br> 0.4.0 (April 2021): Approx. 10,500 entries<br> 0.3.0 (February 2021): Approx. 7,500 entries, as well as various corrections, mergers, translations<br> 0.2.0 (December 2020): Approx. 5,000 entries, as well as various corrections, mergers, translations<br> 0.1.0 (October 2020): Early version with approx. 3,000 entries</p> <p><strong>Online Access:</strong></p> <p>Via Heurist: <a href="https://home.uni-leipzig.de/cerd/">https://home.uni-leipzig.de/cerd/</a></p>
A multiple model high-resolution head-related impulse response database for aided and unaided ears (SOFA format)
<p>The Multiple-Model High Resolution HRTF database is a collection of HRTFs measured using four different Head-and-Torso Simulators at high spatial resolution (2 degree azimuth and elevation). The data here is stored in SOFA format, with the data identical to the HDF5 files in <a href="https://zenodo.org/record/1226873">doi:10.5281/zenodo.1226873</a>.</p>
Image database to supplement "Paulus, F.M. et al. Pain empathy but not surprise in response to unexpected action explains arousal related pupil dilation." (VIPER database)
<p>This folder contains the 282 images of the "VIPER" database (visually-induced pain empathy repository) along with ratings of 24 independent raters. Details are described in the following publication:</p> <p>Paulus, F.M., Müller-Pinzler, L., Walper, D., Marx, S., Hamschmidt, L., Rademacher, L., Krach, S., Einhäuser, W. Pain empathy but not surprise in response to unexpected action explains arousal related pupil dilation.</p> <p>The material can be used for scientific purposes, provided this reference is appropriately cited. Please check the download site to get the up-to-date reference at the time of your publication.</p> <p> </p> <p>Conditions are identified by the filename of the image, which consists of the number of the scenario (1-83) and the condition identifier:<br> pain<br> neut(ral)<br> mism(atch)<br> tool<br> Note that the tool and the mismatch condition do not exist for all scenarios.</p> <p>The file ratings_viper.csv contains the ratings. Each image corresponds to a line, the columns are as follows:<br> Column 1: Filename of the image<br> Column 2: Scenario number<br> Column 3: condition<br> Columns 4 through 27: ratings of the 24 individuals (between 0 and 4, NaN if there was no rating recorded)</p> <p>The file thumbnail_viper.jpg provides an overview over all images in the database.</p> <p>For ease of download, the images are available as tar-archive (allImages_viper.tar) and as inidivual files.</p> <p> </p>
Databases related to molecular biophysics 09-2022
<p>A survey and comparative analysis of the technical provision of existing databases that provide for archival of data from molecular biophysics experiments and closely related areas has been carried out. The analysis demonstrates that for many methods provided by MOSBRI there is no specialist provision for data archival such as would adequately satisfy FAIR principles. In particular only a small number of databases containing molecular biophysics derived data use standard data formats with sufficiently rich metadata that enables interoperable data reuse. Where relevant molecular biophysics databases do exist, and in the closely related area of structural biology, there is a clear trend toward complete deposition of the experiment life cycle (i.e., primary experimental data, analysis procedure and interpretation), which will need to be incorporated into plans for the future MOSBRI data repository. The survey also highlights many resources that would have to be linked with any future MOSBRI data repository, to ensure findability and interoperability. </p>
The SMaRP database: Sulfate, Methane and Related Parameters in marine sediments
<p>Global dataset on sulfate, methane and related parameters in marine sediments</p>
CatVolc: A new database of geochemical and geochronological data of volcanic-related materials from the Catalan Volcanic Zone (Spain)
<p>The Catalan Volcanic Zone (CVZ) (NE Spain) consists of an intraplate alkaline volcanic zone associated with the opening of the Western Mediterranean and the development of the European Rift System. Volcanic activity in the CVZ started in the L’Empordà area (ca. > 12 - 8 Ma), extended to La Selva (7.9 - 1.7 Ma), and finally migrated to the Garrotxa Volcanic Field (< 0.7 - 0.01Ma). Despite the scientific interest in the CVZ since the early 19th century, certain aspects remain poorly constrained. These include a full understanding of the spatial and temporal evolution of the magma plumbing system and ascent mechanisms, as well as the chronology of volcanism across the CVZ. Addressing these unresolved questions requires geochemical, petrological, and geochronological data, which, in the case of the CVZ, are scattered and have never been integrated or analyzed within a unified framework. Here, we present the CatVolc (Catalan Volcanism) database, which compiles available geochemical and geochronological data of volcanic-related materials of the CVZ. For each sample, the CatVolc database lists general information about the sampling site, sample lithology, whole-rock analyses (including major and trace elements), isotopic ratios, mineral chemistry, and radiometric/thermoluminescence dating information, if available. A preliminary analysis of the information contained in the CatVolc database highlights the critical limitations of the current state of knowledge and allows suggesting potential future directions for volcanic-driven investigations in the CVZ. Additionally, the results obtained validate the CatVolc database as a key tool for comprehending the spatial and temporal evolution of the magmatic system(s) and volcanic activity in the CVZ, particularly in the Garrotxa Volcanic Field. This aspect is critical for advancing in the assessment of the volcanic hazards in the region and for gaining a comprehensive understanding of future volcanic activity.</p> <p>The current database version consists of three MS Excel files dedicated to primary magmatic rocks (<em>CatVolc_magmatic_rocks.xlsx</em>), xenoliths (<em>CatVolc_xenoliths.xlsx</em>) and radiometric/thermoluminescence dating information (<em>CatVolc_dating.xlsx</em>). Each MS Excel file is structured around a main table (<em>Samples_general_info</em>) containing general information (e.g., location, age, sampling site) of the listed samples, and a certain number of secondary tables. Secondary tables included in the MS Excel files for magmatic rocks and xenoliths report: (i) whole-rock geochemistry (<em>Major_elements</em> and <em>Trace_elements</em>); (ii) isotopic relations data (<em>Isotopic_relations</em>); and (iii) mineral and volcanic glass chemistry (<em>Amphibole</em><strong>, </strong><em>Feldspar</em><strong>, </strong><em>Felspathoid</em><strong>, </strong><em>Glass</em><strong>, </strong><em>Mica</em><strong>, </strong><em>Olivine</em><strong>, </strong><em>Pyroxene</em><strong>, </strong><em>Oxides</em><strong>, </strong><em>Serpentines</em><strong> </strong>and<strong> </strong><em>Sulphides</em><em>)</em>. In addition to the <em>Samples_general_info </em>table, the <em>CatVolc_dating.xlsx </em>also includes radiometric/thermoluminescence dating information (<em>Dating</em>). Finally, in all three Excel files, we have incorporated a table with consulted references (<em>References</em><em>) </em>and a glossary of the acronyms used for the parameters included in the main and secondary tables (<em>Codes</em>). </p> <p> </p>
Database of geochemical analyses of soils and rocks related to the Bosumtwi impact crater
<p>This excel file contains geochemical analyses of soils and rocks related to the Bosumtwi impact crater and its surroudings geological units - all data included in this database have been extracted from peer-reviewed literature.</p>
Dataset related to aticle "Additive Fabrication of a Vascular 3D Phantom for Stereotactic Radiosurgery of Arteriovenous Malformations"The database contains 3D models in STL file format of a patient-specific brain arteriovenous malformation phantom reconstructed from computed tomography scans.
<p><em>The database contains 3D models in STL file format of a patient-specific brain arteriovenous malformation phantom reconstructed from computed tomography scans.</em></p>
Database on Projects, Programmes, and Institutions (PPIs) related to agroecology
<p>This database holds the list of projects, funding programmes, and institutions (PPIs) dealing with agroecology research in Europe identified in the mapping activities carried out in the Task 1.3 of AE4EU project (https://www.ae4eu.eu/). The final version of the database was released as annex of the project Deliverable D 1.3 “Report on agroecological research development”. In this public version all sensitive data (eg., email contacts) were removed from the file.</p> <p>The database is composed by the following different sheets including:</p> <ul> <li><strong>European projects</strong> with the list of the identified research projects related to agroecology funded by the European Union under the Horizon 2020 framework programme from 2014 onwards</li> <li><strong>Transnational projects</strong> with research projects funded by programmes co-framed and co-funded by Member States and European Union (i.e., ERA-NETs in the past Horizon framework and European Partnerships of Horizon Europe)</li> <li><strong>National projects</strong> on agroecology funded by national funding programmes in the different European countries from 2014 onwards</li> <li><strong>European programmes</strong>. This list reports the topics and calls from which the selected European projects were funded. The list was also enriched including topics and calls from the new working programme 2021-2022 (Horizon Europe Programme);</li> <li><strong>Transnational programmes</strong> which financed the identified transnational research projects</li> <li><strong>National programmes</strong>. Here the information on the national agroecology programmes provided by relevant key informants (i.e., national funding agencies and bodies, AE4EU partners) were included,</li> <li><strong>Participants</strong> with the list of public or private research institutions, organizations, and enterprises involved as partners of the identified European, Transnational and National research projects</li> </ul>
Pharmacokinetic Relation Extraction Database (PRED)
<p>Annotated data to perform Relation Extraction and extract pharmacokinetic (PK) parameter estimates from scientific text. </p> <p>Training, development and test files are released in <a href="https://jsonlines.org/">JSONL format</a> and store the annoated data for training and evaluating end-to-end relation extraction models. </p> <p>Each line in the JSONL files corresponds to an annotated sentence with the following information: </p> <ul> <li><strong>text</strong>: Raw sentence</li> <li><strong>relations: </strong>List or relations each containing: <ul> <li><strong>head_span </strong>: Head entity of the relation as a dictionary containing start character, end character and entity type label</li> <li><strong>child_span: </strong>Child entity of the relation </li> <li><strong>label</strong>: relation type label (i.e. either C_VAL, D_VAL or RELATED)</li> </ul> </li> <li><strong>spans</strong>: List of entities mentioned in the sentence, specifying: (1) the character-level boundaries and (2) the entity type label of each annotation (i.e. either PK, VALUE, UNITS, RANGE or COMPARE). This field is not strictly required to train the model since all spans are defined within the relations.</li> <li><strong>sentence_hash</strong>: Unique sentence ID</li> <li><strong>metadata</strong>: Metadata with unique article, paragraph and sentence identifiers and the article section from which the sentence was extracted</li> </ul> <p> </p>
SchemaPile: A Large Collection of Relational Database Schemas
<p>Access to fine-grained schema information is crucial for understanding how relational databases are designed and used in practice, and for building systems that help users interact with them. Furthermore, such information is required as training data to leverage the potential of large language models (LLMs) for improving data preparation, data integration and natural language querying.<br><br>Existing single-table corpora such as GitTables provide insights into how tables are structured in-the-wild, but lack detailed schema information about how tables relate to each other, as well as metadata like data types or integrity constraints. On the other hand, existing multi-table (or database schema) datasets are rather small and attribute-poor, leaving it unclear to what extent they actually represent typical real-world database schemas. </p> <p>In order to address these challenges, we present SchemaPile, a corpus of 221,171 database schemas, extracted from SQL files on GitHub. It contains 1.7 million tables with 10 million column definitions, 700 thousand foreign key relationships, seven million integrity constraints, and data content for more than 340 thousand tables. We conduct an in-depth analysis on the millions of schema metadata properties in our corpus, as well as its highly diverse language and topic distribution. In addition, we showcase the potential of SchemaPile to improve a variety of data management applications, e.g., fine-tuning LLMs for schema-only foreign key detection, improving CSV header detection and evaluating multi-dialect SQL parsers. We publish the code and data for recreating SchemaPile and a permissively licensed subset SchemaPile-Perm. </p> <p><a href="http://schemapile.github.io">http://schemapile.github.io</a></p>
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.