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8 results for “metadata quality”
The Red Queen in the Repository: metadata quality in an ever-changing environment (preprint of paper, presentation slides and dataset collection with validation schemas to IDCC2019 conference paper)
<p>This fileset contains a preprint version of the conference paper (.pdf), presentation slides (as .pptx) and the dataset(s) and validation schema(s) for the IDCC 2019 (Melbourne) conference paper: <em>The Red Queen in the Repository: metadata quality in an ever-changing environment. </em>Datasets and schemas are in .xml, .xsd , Excel (.xlsx) and .csv (two files representing two different sheets in the .xslx -file). The <em>validationSchemas.zip</em> holds the additional validation schemas (.xsd), that were not found in the schemaLocations of the metadata xml-files to be validated. The schemas must all be placed in the same folder, and are to be used for validating the Dataverse <em>dcterms</em> records (with <em>metadataDCT.xsd</em>) and the Zenodo <em>oai_datacite</em> feeds respectively (<em>schema.datacite.org_oai_oai-1.0_oai.xsd</em>). In the latter case, a simpler way of doing it might be to replace the incorrect URL "<em>http://schema.datacite.org/oai/oai-1.0/ oai_datacite.xsd</em>" in the <em>schemaLocation </em>of these xml-files by the CORRECT: <em>schemaLocation="http://schema.datacite.org/oai/oai-1.0/ http://schema.datacite.org/oai/oai-1.0/oai.xsd"</em> as has been done already in the sample files here. The sample file folders <em>testDVNcoll.zip </em>(Dataverse), <em>testFigColl.zip </em>(Figshare)<em> </em>and <em>testZenColl.zip </em>(Zenodo)<em> </em>contain all the metadata files tested and validated that are registered in the spreadsheet with objectIDs.<br> In the case of Zenodo, one original file feed,<br> <em>zen2018oai_datacite3orig-https%20_zenodo.org_oai2d%20verb=ListRecords%26metadata<br> Prefix=oai_datacite%26from=2018-11-29%26until=2018-11-30.xml</em> ,<br> is also supplied to show what was necessary to change in order to perform validation as indicated in the paper.</p> <p>For Dataverse, a corrected version of a file,<br> <em>dvn2014ddi-27595<strong>Corr</strong>_https%20_dataverse.harvard.edu_api_datasets_export%20<br> exporter=ddi%26persistentId=doi%253A10.7910_DVN_27595<strong>Corr</strong>.xml</em> ,<br> is also supplied in order to show the changes it would take to make the file validate without error.</p>
Description and quality metadata files for four spatial landmark datasets
<p>The files define the description and quality metadata of the spatial landmark datasets from camptocamp.org defined <a href="https://doi.org/10.5281/zenodo.6480985">here</a>.</p> <p>Two ISO standards ISO 19115-1:2014 and ISO 19157:2013, recommanded by the INSPIRE Directive for the dissemination of spatial data and the reporting of data quality are used.</p>
Coverage and quality of open metadata for Dutch research output - dataset
<p>Record level data underlying the figures and tables in the report:<strong><br><br>Coverage and quality of open metadata for Dutch research output - report<br></strong></p> <p><a href="https://doi.org/10.5281/zenodo.10629457" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10629457</a><br><br>The current dataset contains 3 csv files:</p> <ul> <li><em>rpo_nl_list_long_20240201.csv</em> - list of identifiers (ROR ID, OpenAlex ID, OpenAIRE ID) of Dutch research performing organisations. <p>Identifiers were collected for the following groups of Dutch RPOs (see Appendix A):</p> <ul> <li> <p>Universities, organised in Universities of the Netherlands (UNL, n=14);</p> </li> <li> <p>University Medical Centres, organised in the Dutch Federation of University Medical Centres (NFU, n=9); </p> </li> <li> <p>National research institutes under the umbrella organisation of the Foundation for Dutch Scientific Research Institutes (NWO-i, n= 9);</p> </li> <li> <p>Research institutes of the Royal Netherlands Academy of Arts and Sciences (KNAW, n=10);</p> </li> <li> <p>Universities of Applied Sciences affiliated to the Netherlands Association of Universities of Applied Sciences (Vereniging Hogescholen) (VH, n=35 of 37)<br><br></p> </li> </ul> </li> <li><em>openalex_works_20231223_rpo_nl_2022 </em>- record-level data of OpenAlex records retrieved for all Dutch RPOs in scope of the pilot (UNL/NFU, NWO-i, KNAW, VH) for publication year 2022<br><br></li> <li><em>openaire_products_20240116_rpo_nl_2022 - </em>record-level data of OpenAlex records retrieved for all Dutch RPOs in scope of the pilot (UNL/NFU, NWO-i, KNAW, VH) for publication year 2022</li> </ul>
Schools Weather and Air Quality (SWAQ) –Metadata – Urban Network, Sydney (NSW)
<p>Schools Weather and Air Quality (SWAQ) is a citizen science project funded by the Department of Industry, Innovation and Science as part of its Inspiring Australia - Citizen Engagement Program. SWAQ is equipping public schools across Sydney with research-grade meteorology and air quality sensors, enabling students to collect and analyse research quality data through curriculum-aligned classroom activities.</p> <p>The network includes twelve automatic weather stations and seven automatic air quality stations, stretched from -33.5995° to -34.0424° latitude and from 150.6918° to 151.2706° longitude. The average spacing is 10.2 km and the average installation height is 2.5 m above ground level. Six meteorological parameters (dry-bulb temperature, relative humidity, barometric pressure, rain, wind speed, and wind direction) and six air pollutants (SO2, NO2, CO, O3, PM2.5, and PM10) are recorded via Vaisala WXT 536 and Vaisala AQT 420 with a 20 minutes sampling frequency. </p> <p>SWAQ data provides urban canopy layer observations of the intra-urban heterogeneity and inter-parameter dependency of all major urban climate and air quality variables, valuable across diverse urban disciplines. SWAQ stations are located where there are gaps in existing government networks, and focus on Sydney’s western suburbs, where the highest urbanization rate is taking place, to better inform future urban planning. QC procedures are designed to ensure observations of extreme episodes are not excluded. Beyond research purposes, SWAQ is a citizen-centered network, conceived to promote valuable STEM (science, technology, engineering, mathematics) skills among citizens and students.</p> <p>This collection includes the metadata files for all SWAQ stations, in pdf. Metadata describe the site (type, geographic coordinates, elevation, orographic setting, representativeness, local climatic zone, dominant land use, percent land cover, mean tree and building heights, proximity to water/heat and pollutants sources/sinks, estimation of Davenport Roughness, traffic density, sky view factor), and the instrumentation (variables, models, manufacturers, calibration and installation dates). Site characteristics are described at three radial scales: 20 km, 500 m, and 50 m. Graphical representations include: satellite images, street-view maps, cardinal direction photographs, panoramic photos, and close-up photos of sensors, solar panels, and connections. Optimum site allocation was determined by undertaking a multi-criteria weighted overlay analysis to ensure data representativeness and quality. All SWAQ sensors are installed:</p> <ul> <li>in homogenous urban regions, without sections of anomalous variation in the regional urban makeup and aspect-ratio, and without large, concentrated heat/pollution sources or sinks;</li> <li>in areas falling into the WMO Class 4 with no electromagnetic sources that could have distorted the transmission;</li> <li>at a constant height of 2 - 3.5 m above ground level.</li> </ul> <p>The actual data is available from the Australian Terrestrial Ecosystem Research Network (TERN) <a href="https://https://portal.tern.org.au/schools-weather-air-sydney-nsw/22077">data portal</a> and is regularly updated. The data available from TERN has undergone a rigorous quality check routine before upload.</p> <ul> <li>Calibration: Sensors and gateways are calibrated and tested by Vaisalain controlled conditions </li> <li>Quality Assurance: Annual maintenance log</li> <li>Quality control: continuity tests, fixed range tests (on both physical and instrumental limits), dynamic range and step tests (both performed on a monthly basis), internal consistency tests (on known atmospheric relations) and persistence tests. </li> </ul> <p>The files are in csv format. On the <a href="https://www.swaq.org.au">SWAQ website</a> a non quality controlled subset is available for educational purposes only.</p> <p>This project was funded by an Australian Government Department of Industry, Innovation and Science, Inspiring Australia – Science Engagement Program: Citizen Science Grants (CSG56028).</p> <p>It was also part of the Centre of Excellence for Climate Extremes research project "Attribution & Risk".</p> <p>More information is available in the readme file, in particular a full list of the variables and a legend for the quality flags used.</p>
Metadata Quality Assessment Results of data.europa.eu in November 2023
<h2>Description</h2> <p>Metadata Quality Assessment Results of data.europa.eu in November 2023 to evaluate the quality of the datasets harvested by the European portal in terms of FAIR principles</p> <h2>Paper</h2> <ul> <li>Paper: <a href="https://arxiv.org/abs/2402.06693">Fostering the integration of European Open Data into Data Spaces through High-Quality Metadata</a></li> <li>Cite:</li> </ul> <p><code>@misc{conde2024fostering,</code><br><code> title={Fostering the integration of European Open Data into Data Spaces through High-Quality Metadata}, </code><br><code> author={Javier Conde and Alejandro Pozo and Andrés Munoz-Arcentales and Johnny Choque and Álvaro Alonso},</code><br><code> year={2024},</code><br><code> eprint={2402.06693},</code><br><code> archivePrefix={arXiv},</code><br><code> primaryClass={cs.DB}</code><br><code>}</code></p> <p> </p>
Quality Evolution of DCAT Metadata in data.europa.eu between 2021 and 2022
<p>This datasets consists the evolution of the quality of the DCAT metadata in data.europa.eu between January 2022 and March 2023.</p> <p>It is used in the EGOV 2023 research paper "An Extensive Methodology and Framework for Quality Assessment of DCAT-AP Datasets".</p> <p>The data was retrieved with via the official API: <a href="https://data.europa.eu/api/mqa/cache/">https://data.europa.eu/api/mqa/cache/</a><br> The script.py was used to generate the tabular data.</p> <p> </p>
Training Data for "Creating Quality FAIR assessment reports and draft of Data Papers from EML metadata with MetaShRIMPS"
<p>Training Data for "Training Data for "Creating Quality FAIR assessment reports and draft of Data Papers from EML metadata with MetaShRIMPS""</p>
Data and metadata of crop yield and quality derived from H2020 Diverfarming project
<p>Data and metadata of crop yield and quality from different cases studies and long terms from WP3 "Crop production and quality", derived from H2020 Diverfarming project. This workpackage provides robust and sound data about how diversified cropping systems with low-input practices and efficient use of resources have positive effects on crop production and quality, and so, farm yields and economic revenues for farmers is increased. This can increase trading productivity with high quality outputs, so improving the competitiveness of European agriculture in the global market. http://www.diverfarming.eu.</p>
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OpenNeuro
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