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7 results for “unified database”
A unified template for sediment source fingerprinting databases
<p>Over the last few years, the sediment source fingerprinting community has been engaged in promoting best practices to improve the design and the implementation of sediment fingerprinting techniques (<a href="https://doi.org/10.1007/s11368-022-03203-1">Evrard et al., 2022</a>). Data sharing is a key part of open science making research more reliable and accessible to the community. To move forward and improve data sharing, we propose these templates for databases and metadata.</p> <p>These templates include: common metadata for samples (soil, river flood deposit, sediment core...) description (name, IGSN, location, sampling date...), list and description of common properties (elemental geochemistry, organic matter, radionuclides…) used in sediment source fingerprinting studies. These templates are intended to evolve thanks to the participation of the community, as part of a collaborative project.</p> <p>In addition, the <strong>collectionneur </strong>R package was designed to help researchers and data managers maintain an up-to-date and well-organized database. is avalaible on <a href="https://github.com/tchalauxclergue/collectionneur"><strong>GitHub</strong> (https://github.com/tchalauxclergue/collectionneur)</a> and <a href="https://doi.org/10.5281/zenodo.15146958"><strong>Zenodo</strong> (https://doi.org/10.5281/zenodo.15146958)</a>. It facilitates the comparison and integration of new data entries into an existing database while keeping a detailed report of all modifications. All database formats are allowed, although it was initially designed for sediment source fingerprinting databases.</p> <p>Published databases following these templates are listed in the References section below. </p>
UNIFI IBIMET PRIN 2015 CLIMATIC DATABASE
<p>UNIFI PRIN 2015 CLIMATIC DATABASE</p> <p>Climatic and weather data related to investigated area </p> <p>PRIN italian ADAPTIVE DESIGN e INNOVAZIONI TECNOLOGICHE PER LA RIGERNARAZIONE RESILIENTE DEI DISTRETTI URBANI IN REGIME DI CAMBIAMENTO CLIMATICO</p> <p>DIDA Dipartimento di Architetttura Università di Firenze</p> <p>This database was created to perform investigations for climatic urban resilience.</p>
Worldwide Unified Wildland-Urban Interface (WUWUI) database
<p>This is the Worldwide Unified Wildland-Urban Interface (WUWUI) database developed by the study entitled "Global Expansion of Wildland-Urban Interface (WUI) and WUI fires: Insights from a Multiyear Worldwide Unified Database (WUWUI)" published on Environmental Research Letters (<strong>DOI</strong> 10.1088/1748-9326/ad31da).</p> <p>Please use the latest version.</p>
Towards a reproducible interactome: semantic-based detection of redundancies to unify protein-protein interaction databases
<p>Protein-protein interactions (PPIs) play an ubiquitous and fundamental role in all biological processes. Information on PPIs described in the literature is annotated and made available by several protein-interaction databases. Because most databases have their own curation rules and priorities, they often annotate overlapping sets of publications, which leads to redundancies. We developed a semantic-based approach which enables to accurately detect redundancies within PPI datasets from multiple databases. We applied this approach to assemble a "reproducible interactome", with PPIs supported by at least two methods or publications.</p>
APOSCRIPTA database. Unified Corpus of Papal Letters
<p>La base de données APOSCRIPTA est ainsi nommée d'après l'expression apostolica scripta, par laquelle les papes ont couramment désigné leurs lettres à partir du début du XIIe siècle. Il s'agit d'une ressource de recherche vouée à prendre, à brève échéance, les caractéristiques du type linked open data.</p> <p>Conçue en relation avec le goupe de recherches FULMEN, lancée en 2017 par le CIHAM (UMR 5648) – avec le soutien financier de l'Université de Lyon (Programme d'avenir Lyon Saint-Etienne), à l'initiative et sous la direction de Julien Théry, avec la collaboration d'Andrey Grunin et Laurent Vallière, et avec le soutien technique de l'ARCHE (UR 3400) et de l'IRHT (CNRS, UPR 841) –, APOSCRIPTA a pour objectif de rassembler les textes et métadonnées du plus grand nombre possible de documents (lettres principalement, mais aussi actes solennels ou canons et décrétales) émis par les pontifes romains depuis les origines jusqu'à l'âge moderne, quelles que soient leurs traditions manuscrites (privilèges ou expéditions conservés en original, copies de toute sorte). Voir la page Présentation pour plus de détails.</p> <p>Le corpus réuni par APOSCRIPTA, en augmentation permanente, est actuellement riche de plus de 25 000 lettres, décrétales ou privilèges.</p> <p>Pour plus de détails, voir: <a href="http://telma-chartes.irht.cnrs.fr/aposcripta/page/about-accueil">http://telma-chartes.irht.cnrs.fr/aposcripta/page/about-accueil</a></p>
Database used in : Analysis of intermunicipal journeys for cardiac surgery in Brazilian Unified Health System (SUS): an approach based on network theory
<p>Data and scripts referring to the results generated in the article entitled: <strong>Analysis of intermunicipal journeys for cardiac surgery in Brazilian Unified Health System (SUS): an approach based on network theory.</strong></p> <p> </p> <p>To obtain the results of the work the following sequence of database treatment was performed:</p> <p> </p> <p>DATASUS --> BASE_PER_YEAR --> EDGES_BASE --> EDGES_VC_BASE</p> <p>The bases were downloaded from the DATASUS site (link: https://datasus.saude.gov.br/transferencia-de-arquivos/#) in .dbc format separated by month and year; using Tabwin we joined the bases generating a base for each year in csv format. The reformatted bases are gathered together in the file PER_YEAR_BASE.ZIP; from the bases for each year we manually built the files in csv format with the list of the edges with the following fields: "Source", "Target", "Type", "Id", "Label" and "Weight". The "Source" column was filled with data from MUNIC_RES and the "Target" column with data from MUNIC_MOV. The "ID" and "Weight" fields were filled in automatically using Gephi, where the "Weight" column represents the sum of the edge, defined by the pair of Source and Target columns, were repeated throughout the year. This generated the bases containing the list of edges that are grouped in the file EDGES_BASE.ZIP. Each base was filtered to contain only edges related to the city "Vitória da Conquista" and grouped in the file EDGES_VC_BASE.zip</p> <p>INDE BASE --> NODES_BASE</p> <p>To build the list of nodes containing the list of municipalities with their respective geographical locations (in UTM), we used the database of the INDE (available on the link: https://visualizador.inde.gov.br/). The file in shape format was treated in the ArqGis program and the database with the network nodes was created (file NODES_BASE.csv).</p> <p>EDGES_VC_BASE and NODES_BASE --> NETWORK</p> <p>Using the program Gephi we joined the bases referring to the edges (EDGES_VC_BASE) and those referring to the nodes of the network (NODES_BASE) and built the networks for each year studied for the city of "Vitória da Conquista". All networks are in gephi format and compressed in the NETWORKS.zip file.</p> <p>EDGES_VC_BASE and NODES_BASE --> INDICES</p> <p>Using the R script "distance.R" and using as input the files of edges (EDGES_VC_BASE) and nodes (NODES_BASE) we generate files in csv format with the columns: dist_med_in , dist_med_out, Flow_in and flow_out. The indexes dist_med_in and dist_med_out represent the average distance traveled in meters to enter and leave the municipality, respectively; the indexes flow_in and flow_out estimate the quantity of people that entered and left the municipality. All index files are grouped in the compressed file INDICES.zip.</p> <p>The last two digits at the end of all file names represent the year of analysis. </p>
Eastern Canada's Unified Heritage Building Database (EC-UHBD)
<p>This database merges details on heritage-listed buildings from multiple Eastern Canadian registers. A focus on structural characteristics available were able to be harmonized in this database including: construction date, number of stories, building materials, location, use type and links to the orginal building.</p> <p><strong>Data are still preliminary and in review.</strong></p> <p>The building registers are listed here: </p> <ul> <li>Parks Canada Federal Database of Historic Buildings (Parks Canada, 2018)</li> <li>Historic Places (<em>Parks Canada</em>, 2001)</li> <li>Répertoire du patrimoine du Québec (Québec, 2013.</li> <li>Grande Répertoire du patrimoine bâti de Montréal (<em>Montreal.ca</em>, 2021a)</li> <li>L’inventaire des propriétés municipales d’intérêt patrimonial (<em>Montreal.ca</em>, 2021b)</li> <li>Le patrimoine du Vieux-Montréal en détail (<em>Montreal.ca</em>, 2021c)</li> <li>Répertoire du patrimoine bâti (<em>Ville de Québec</em>, 2023)</li> <li>Ontario Trust Database (<em>Ontario Heritage Trust</em>, 2023)</li> <li>Lieux de culte du Québec (Conseil du patrimoine religieux du Québec, 2011)</li> </ul>
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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.