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11 results for “structural metadata”
Dataset and program scripts for the reproducibility of the hierarchical data structure file. Related to the manuscript entitled: Hierarchical Representation of Measurement Data, Metrological Uncertainty and Metadata for Calibrated Battery Tests
<p>We present an interoperable hierarchical data representation for battery tests, leading to improved scalability of data transmission and enhanced data accessibility and comprehensibility for both human interpretation and machine processing. The hierarchical data format includes the raw trace electrical measurement data, the metrological calibration and uncertainty data, the metadata such as experimental settings, instruments and software versions, as well as post-processed data such as electrochemical model fit parameters. This data representation allows repetition of the battery test under the exact same conditions such that identical results are achieved within defined error bounds. This is in line with the general F.A.I.R. data approach and provides repeatability and traceability in the battery value chain. As an application of the hierarchical data representation, we show the classification of cells as pass/fail being performed with quantitative confidence levels. We demonstrate the complete workflow of establishing the hierarchical data structure for electrochemical impedance spectroscopy (EIS), starting from metrological traceability of the calibration and uncertainty analysis towards the storage of the structured data as a single integrated file that preserves the hierarchical data format.</p>
Example Microscopy Metadata JSON files produced using Micro-Meta App to document the acquisition of example images using a custom-built TIRF Epifluorescence Structured Illumination Microscope
<p><strong>Example Microscopy Metadata JSON files produced using the <a href="https://wu-bimac.github.io/MicroMetaApp.github.io/">Micro-Meta App</a> documenting an example raw-image file acquired using the custom-built TIRF Epifluorescence Structured Illumination Microscope.</strong></p> <p>For this use case, which is presented in Figure 5 of <a href="http://doi: https://doi.org/10.1101/2021.05.31.446382">Rigano et al., 2021</a>, Micro-Meta App was utilized to document:</p> <p>1) The <strong>Hardware Specifications</strong> of the custom build TIRF Epifluorescence Structured light Microscope (TESM; <a href="https://www.pnas.org/content/109/8/E471.long">Navaroli et al., 2010</a>) developed, built on the basis of the based on Olympus IX71 microscope stand, and owned by the Biomedical Imaging Group (http://big.umassmed.edu/) at the Program in Molecular Medicine of the University of Massachusetts Medical School. Because TESM was custom-built the most appropriate documentation level is <strong>Tier 3</strong> (<em>Manufacturing/Technical Development/Full Documentation</em>) as specified by the <a href="https://doi.org/10.5281/zenodo.4710731">4DN-BINA-OME</a> Microscopy Metadata model (<a href="https://doi.org/10.1101/2021.04.25.441198">Hammer et al., 2021</a>).</p> <p>The TESM Hardware Specifications are stored in: <strong>Rigano et al._Figure 5_UseCase_Biomedical Imaging Group_TESM.JSON</strong></p> <p>2) The <strong>Image Acquisition Settings</strong> that were applied to the TESM microscope for the acquisition of an example image (FSWT-6hVirus-10minFIX-stk_4-EPI.tif.ome.tif) obtained by Nicholas Vecchietti and Caterina Strambio-De-Castillia. For this image, TZM-bl human cells were infected with HIV-1 retroviral three-part vector (FSWT+PAX2+pMD2.G). Six hours post-infection cells were fixed for 10 min with 1% formaldehyde in PBS, and permeabilized. Cells were stained with mouse anti-p24 primary antibody followed by DyLight488-anti-Mouse secondary antibody, to detect HIV-1 viral Capsid. In addition, cells were counterstained using rabbit anti-Lamin B1 primary antibody followed by DyLight649-anti-Rabbit secondary antibody, to visualize the nuclear envelope and with DAPI to visualize the nuclear chromosomal DNA.</p> <p>The Image Acquisition Settings used to acquire the FSWT-6hVirus-10minFIX-stk_4-EPI.tif.ome.tif image are stored in: <strong>Rigano et al._Figure 5_UseCase_AS_fswt-6hvirus-10minfix-stk_4-epi.tif.JSON</strong></p> <p><em><strong>Instructional video tutorials on how to use these example data files:</strong></em><br> Use these videos to get started with using Micro-Meta App after downloading the example data files available here.</p> <ul> <li><a href="https://vimeo.com/562022222">Part 1/2</a></li> <li><a href="https://vimeo.com/562022281">Part 2/2</a></li> </ul>
PDB70 Structural Library and Metadata
<p>Protein structural library developed from the PDB70 sequence database as well as associated metadata for each structure. The structures associated with each entry in the PDB70 structural library are provided in a tarball. When available, the metadata for a protein has been gathered from UniProtKB flat files. A focus is given to enzyme commission (EC) number metadata as this type of ontology is of main focus for identifying and classifying enzymes within a proteome. </p> <p>Changelog: </p> <p>v1.0.2 - Added list file for structures that have active EC numbers, accounting for defunct EC numbers in UniProtKB metadata being replaced with an active EC number when relevant.</p> <p>v1.0.1 - Small clean up of the provided .ipynb document. </p> <p>v1.0.0 - Original push of the PDB70 structural database and metadata.</p>
FoldingDiff generated structures (n=780, main results) and associated metadata
<p>Backbone structures generated by FoldingDiff spanning lengths [50, 128). Each length has 10 randomly sampled structures for a total of 780 backbone structures. These were used to derive all results in our manuscript's main results section. In addition to structures in .pse format, we provide an excel table with the following sheets:</p><ul><li>Table containing metadata for each of the aforementioned generated structures. Metadata includes scTM designability scores using ProteinMPNN + OmegaFold and using ProteinMPNN + AlphaFold2, maximum training set TM score (similarity), structure length, and number of sheets/helices present as annotated by P-SEA.</li><li>Table containing Gauss integral embeddings for each of the 780 backbones generated by FoldingDiff</li><li>Table containing Gauss integral embeddings for select test set structures between 50 and 128 residues in length. These were used to compare and contextualize structures/embeddings from FoldingDiff.</li></ul>
Supplement - Structure from Motion Metadata and Outcomes
<p>Ground control points used to ensure Structure from Motion (SfM) terrain models were georectified (Westoby et al. 2012; Wolf 2021) using Emlid R2 RTK (real-time kinematic) GNSS (global navigation satellite system) system consisting of a base station set up over an established known point (established with Canadian Geodetic Survey of Natural Resources Canada (NRCAN) service Canadian Spatial Reference System Precise Point Positioning (CSRS- PPP)) and a rover. </p> <p>Once the ground control points were surveyed, aerial drone images were acquired. We created flight polygons in Drone Deploy. Pictures were captured with a DJI Mavic II drone with minimum 80 % overlap of photos. Drone Deploy was chosen because it has an option to account for the doming error commonly found in models created from drone imagery and structure from motion (SfM). The doming effect is a systematic error that impacts the DEMs vertical component and can provide errors larger than the usual centimeter level (Sanz-Ablanedo et al. 2020). Generally, each site was flown once in fall of 2020 and once in spring of 2021. </p> <p>We created orthorectified images and digital terrain models using Agisoft Metashape, a photogrammetric processing software application that uses SfM. We followed the workflow outlined in Bywater-Reyes and Pratt-Sitaula (2022). Once processed, orthorectified imagery and Digital Elevation Models (DEMs) were exported to ArcGIS Pro for additional analysis. Data collection metadata and postprocessing outcomes can be found in this Zenodo repository.</p>
Standard Sample Description V1 Structural Metadata
<p>Standard Sample Description V1 is a specification aimed at harmonising the collection of analytical measurement data for the presence of harmful or beneficial chemical substances in food, feed and water. The specification is a list of standardised data elements (items describing characteristics of samples or analytical results such as country of origin, product, analytical method, limit of detection, result, etc.), linked to controlled terminologies. This file has been prepared to support the publication of data and interoperability. This file indicates which data elements from the specification will not be published to ensure full protection of confidential/sensitive information, for example personal data in accordance with Regulation (EC) No 45/2001 and to protect commercial interests, including intellectual property as specified in Article 4(2), first indent, of Regulation (EC) No 1049/2001.</p> <p>The Excel table contains information about the structural metadata elements of the data collection and their fact tables.<br> <br> The column <em>name</em> shows the name of the element (e.g. localOrg).<br> The column <em>description</em> describes how the content has to be interpreted.<br> The column <em>code</em> expresses the corresponding code of the structural metadata element.<br> The column <em>optional</em> says whether the structural metadata element is optional or not (then it is mandatory).<br> The column <em>dataType</em> contains the type which can be used to fill the structural metadata element and the possible maximal length of the field. The possible types are: text or number. <br> The column <em>catalogue</em> contains the name of the catalogue where the content of the structural metadata element has to be picked from (e.g. COUNTRY).<br> The column <em>data</em> <em>protection</em> contains whether the structural metadata element will be published or not (yes = will not be published, no = will be published).</p>
Standard Sample Description V2 Structural Metadata
<p>Standard Sample Description V2 is a specification aimed at harmonising the collection of analytical measurement data for the presence of harmful or beneficial chemical substances in food, feed and water. The specification is a list of standardised data elements (items describing characteristics of samples or analytical results such as country of origin, product, analytical method, limit of detection, result, etc.), linked to controlled terminologies. This specification uses EFSA FoodEx2 to describe sampled foods.</p> <p>This file has been prepared to support the publication of data and interoperability. This file indicates which data elements from the specification will not be published to ensure full protection of confidential/sensitive information, for example personal data in accordance with Regulation (EC) No 45/2001 and to protect commercial interests, including intellectual property as specified in Article 4(2), first indent, of Regulation (EC) No 1049/2001.</p> <p>The Excel table contains information about the structural metadata elements of the data collection and their fact tables.<br> <br> The column <em>name</em> shows the name of the element (e.g. localOrg).<br> The column <em>description</em> describes how the content has to be interpreted.<br> The column <em>code</em> expresses the corresponding code of the structural metadata element.<br> The column <em>optional</em> says whether the structural metadata element is optional or not (then it is mandatory).<br> The column <em>dataType</em> contains the type which can be used to fill the structural metadata element and the possible maximal length of the field. The possible types are: text or number. <br> The column <em>catalogue</em> contains the name of the catalogue where the content of the structural metadata element has to be picked from (e.g. COUNTRY).<br> The column <em>data</em> <em>protection</em> contains whether the structural metadata element will be published or not (yes = will not be published, no = will be published).</p>
EU MENU Structural Metadata
<p>The availability of detailed, harmonised and high-quality food consumption data for use in dietary exposure assessments is a long-term objective of EFSA. In 2009, the EFSA guidance on “General principles for the collection of national food consumption data in the view of a pan-European dietary survey” was published, and a pan-European food consumption survey, also known as the “EU Menu”, was launched. This structural metadata supports reporting of harmonised food consumption data for use in dietary exposure assessments of food-borne hazards and nutrient intake estimations. It was developed for 24-hour dietary recall studies. The reported foods should be described in accordance with the EFSA FoodEx2 food classification system.</p> <p>This file indicates which data elements from the EU MENU will not be published to ensure full protection of confidential/sensitive information, for example personal data in accordance with Regulation (EC) No 45/2001 and to protect commercial interests, including intellectual property as specified in Article 4(2), first indent, of Regulation (EC) No 1049/2001.</p> <p>The Excel tables contain information about the structural metadata elements of the data collection and their fact tables.<br> <br> The column <em>name</em> shows the name of the element (e.g. localOrg).<br> The column <em>description</em> describes how the content has to be interpreted.<br> The column <em>code</em> expresses the corresponding code of the structural metadata element.<br> The column <em>optional</em> says whether the structural metadata element is optional or not (then it is mandatory).<br> The column <em>dataType</em> contains the type which can be used to fill the structural metadata element and the possible maximal length of the field. The possible types are: text or number.<br> The column <em>catalogue</em> contains the name of the catalogue where the content of the structural metadata element has to be picked from (e.g. COUNTRY).<br> The column <em>data</em> <em>protection</em> contains whether the structural metadata element will be published or not (yes = will not be published, no = will be published).</p> <p>The structural metadata is available for the three EU Menu fact tables: Consumption, Food list and Subjects. </p>
Metadata from: Rhizosphere bacteria and fungi are differentially structured by host plants, soil mineralogy and ectomycorrhizal communities in the Alaskan tundra
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Structuring of Data and Metadata in Bioimaging: Concepts and technical Solutions in the Context of Linked Data
<p>guided walkthrough of poster at <a href="https://doi.org/10.5281/zenodo.6821815">https://doi.org/10.5281/zenodo.6821815</a></p> <p>which provides an overview of contexts, frameworks, and models from the world of bioimage data as well as metadata and the techniques for structuring this data as Linked Data.</p> <p>You can also watch the video in the browser on the <a href="https://gerbi-gmb.de/i3dbio/i3dbio-resources/metadata-guide/">I3D:bio website</a>.</p>
Data and metadata of soil microbial community structure, enzyme activities, functional genes and earthworms derived from H2020 Diverfarming project
<p>Soil data and metadata of soil microbial community structure, enzyme activities (dehydrogenase, β-glucosidase, leucine-aminopeptidase, alkaline phosphatase and arylsusfatase activities), N functional genes and earthworms from the different cases studies and long terms from WP4 "Impact of crop diversification on biodiversity", derived from H2020 Diverfarming project. The main objective of workpackage is to provide a scientific understanding of the link between diversified cropping systems, above- and belowground biodiversity, and the resulting ecosystem services provided by soil microorganisms, soil invertebrates and vegetation in agro-ecosystems. Soil organisms contribute to all biogeochemical cycles, Soil organic matter mineralization and stabilization, shape soil structure and have associations with plant species promoting growth and development. http://www.diverfarming.eu.</p>
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