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2,672 results for “services”
Quality evaluation criteria, best practices, and assessment systems for Institutional Publishing Service Providers (IPSPs): dataset
<p>The dataset contains tabular information on the elements of best practice in scholarly publishing found in a set of documents (high-level recommendations and principles, indexation criteria and specific assessment guidelines used on the national and institutional levels). The set of documents subject to analysis (58 items) were identified by the DIAMAS project team members (bibliographic metadata are provided in IPSP-best-practice-documents.xml and IPSP-best-practice-documents.ris).</p> <p>The dataset was compiled by the DIAMAS project team using an analysis matrix that included the general information about the documents (title, issuing entity, scope and purpose, etc.) and the the seven core components of scholarly publishing identified in the Diamond Open Access Action Plan (2022) and revised by the DIAMAS project team.</p> <p>More information about the data collection methodology can be found in the report D3.1 IPSP Best Practices Quality evaluation criteria, best practices, and assessment systems for Institutional Publishing Service Providers (IPSPs) (<a href="https://doi.org/10.5281/zenodo.7859172">https://doi.org/10.5281/zenodo.7859172</a>), which is based on this dataset.</p> <p> </p> <p><strong>****Dataset contents****</strong></p> <p>IPSPs_best-practices-overview.csv</p> <p>IPSPs_best-practices-overview.ods</p> <p>IPSP-best-practice-documents.xml</p> <p>IPSP-best-practice-documents.ris</p> <p>README.txt</p> <p> </p> <p><strong>****Column headers and field types***</strong></p> <p>Title (original) (text)</p> <p>Title (English) (text)</p> <p>Publication date (date, DD/MM/YY)</p> <p>Last accessed (date, DD/MM/YY)</p> <p>URL (text-web address)</p> <p>Scope (text, controlled)</p> <p>Type of document (text, controlled)</p> <p>Original language (text)</p> <p>Other languages (text)</p> <p>Entity issuing the document (text)</p> <p>Entity responsible for the assessment (text)</p> <p>Scope of the assessment (text, controlled)</p> <p>Scope of assessment: region or country (text)</p> <p>Disciplines’ coverage (text)</p> <p>Periodicity of the assessment (text)</p> <p>Reassessment frequency? If yes: periodicity (text)</p> <p>Benefits linked to the assessment (text)</p> <p>(1) Funding (text)</p> <p>(2) Ownership and governance (text)</p> <p>(3) Open science practices (text)</p> <p>(4) Editorial quality, editorial management and research integrity (text)</p> <p>(5) Technical service efficiency (text)</p> <p>(6) Visibility (including indexation), communication, marketing and impact (text)</p> <p>(7) Diversity, Equity and Inclusion (text)</p>
Assessing the Provision of a Multi-Ancillary Service Framework provided by PV-BES Systems (ProMiSe) - LAB Experiments
<p>This dataset comprises the results obtained during ProMiSe project. In particular, scope of ProMiSe is to test and validate a new unified control architecture used to overcome voltage violations and voltage unbalance issues by conducting real-time simulations and utilizing a power hardware-in-the-loop platform. The validation scheme reflects a range of different scenarios and realistic test cases of integration of the unified control strategy in modern distribution networks. In particular, three experiments are considered:</p> <p>- <strong>Experiment 1</strong>: The performance of the proposed unified strategy is evaluated in a low-voltage (LV) distribution network (DN). The LV DN, the detailed model of a three-phase, four-leg converter (3Ph4LC) and the deployed voltage regulation (VR) / voltage unbalance mitigation (VUM) algorithms are developed in the real time digital simulator (RTDS).</p> <p>- <strong>Experiment 2</strong>: The performance of the proposed unified strategy is evaluated in the LV DN of Experiment 1. The LV DN, the detailed model of a 3Ph4LC and the deployed VR/VUMalgorithms are developed in the RTDS. Compared to Experiment 1, in Experiment 2 the line <em>R/X</em> ratio is decreased, in order to demonstrate the impact of the <em>R/X</em> on the provided ancillary services. Here, it should be highlighted that grid voltage levels as well as the power levels of load nodes have been properly readjusted to achieve similar voltage levels to the point of the inter-connection (POI) of the 3Ph4LC with Experiment 1. </p> <p>- <strong>Experiment 3</strong>: The performance of the proposed unified strategy is evaluated in the LV DN of Experiment 1. The LV DN and the VR/VUM algorithms are developed in the RTDS. Compared to Experiment 1, in Experiment 3 the detailed model of the ProMiSe 3Ph4LC has been replaced with controllable current sources. Note that the filter has been remained in the analysis. Here, it should be highlighted that grid voltage levels have been properly readjusted to achieve similar voltage levels to POI with Experiment 1. In addition, due to a resonance problem observed during the test between the lab equipment and the virtual network in the software platform, the filter parameters are readjusted to overcome the problem.</p> <p>For each experiment, the obtained results are provided in csv format.</p> <p>For more Information regarding the ProMiSe project, the conducted simulations, as well as the files/variables expanation, please refer to ProMiSe-Info.pdf.</p>
Interagency Ecological Program and US Fish and Wildlife Service: Beach Seine Efficiency Study, collected by the Delta Juvenile Fish Monitoring Program, 2013-2018
Within the San Francisco Estuary, beach seining has been used since the 1970s by the U.S. Fish and Wildlife Service's Delta Juvenile Fish Monitoring Program (DJFMP) to monitor the relative abundance and distribution of juvenile Chinook salmon and other fishes of management concern occurring in near shore habitats. Over 2,000 seine samples are currently being collected throughout the San Francisco Estuary annually. Data from these surveys are used to make various water operation decisions and help inform managers on the status of fish populations within the San Francisco Estuary. By not accounting for the variability of species- and size-specific efficiency of beach seines across environmental gradients, the metrics developed by the DJFMP are likely underestimated and biased to an unknown extent. Consequently, the ability of the DJFMP to document the true occupancy of fishes for water operations and population vicissitude may be inhibited. Therefore, the first objective of this study is to estimate the species- and size-specific capture efficiency of DJFMP beach seines for fishes occurring in near shore habitats within the San Francisco Estuary. The second objective is to model the observed efficiency estimates using habitat variables to allow managers to account for incomplete detection when estimating fish abundance and occupancy from DJFMP beach seine data.
Interagency Ecological Program and US Fish and Wildlife Service: Enhanced Delta Smelt Monitoring Program Experimental Larval Survey Data 2018-2019
The United States Fish and Wildlife Service’s (USFWS) Experimental Larval Survey was designed and implemented by the Enhanced Delta Smelt Monitoring Program to assess alternative sampling methods for monitoring the larval life stages of the federally endangered Delta Smelt (Hypomesus transpacificus) within the San Francisco Estuary, California, USA. From 2018 to 2019, four different sampling methods (Beach Seine, Manta Trawl Net, 20-mm Surface Trawl Net, 20-mm Midwater Trawl Net) nested in time and space were used to estimate the occupancy rate, relative density, and size distribution of larval Delta Smelt across sampling methods and water depth strata within the San Francisco Estuary. For more information on the Lodi USFWS Office and the Enhanced Delta Smelt Monitoring Program: https://www.fws.gov/lodi/.
Data for Quantifying Ecosystem Services Under Various Oyster Reef Designs
This data provides the basis for comparison of the services provided by reef designs varying in elevation and width located adjacent to an intertidal marsh within a coastal bay of Virginia, USA. We quantified wave attenuation to determine potential coastal protection of the adjacent marsh, and changes to sediment composition and infaunal communities before and after reef construction for three years. After construction we also quantified oyster size and population density to compare high and low elevation reef designs. Data consists of 4 tables: 1) Depths and wave heights, adjacent to the bay and marsh sides of the reef 2) Abundance of organisms 3) Biomass of organisms 4) Sediment organic matter There is also a .zip file containing the original Excel files from which the consolidated tables were extracted.
Copernicus Global Land Service: Land Cover 100m: epoch 2018: Africa demo (deprecated)
<p><strong><em>This demo dataset over Africa is deprecated. Please see <a href="https://doi.org/10.5281/zenodo.3518037">this global dataset</a> instead.</em></strong></p> <p>Demonstration land cover maps over Africa at 100m resolution for epoch year 2018, from the global component of the Copernicus Land Service and derived from PROBA-V satellite observations.</p> <p>The maps include the main discrete classification (23 classes aligned with UN-FAO's LCCS), a set of cover fractions (%) for the 10 main classes and additional quality layers (e.g. density of input data).</p> <p>For the near-real time (nrt) epoch 2018, the classifier and regression models of base year 2015 are used, and the time window of the classified metrics covers one full year prior (2017) and three months pastor (Jan-March 2019) data. The nrt map can then be supplied in the fourth month after the most recent completed calendar year, and is updated (consolidated) afterwards by using a full year of paster data (when epoch 2019-nrt is produced, epoch 2018 is consolidated).</p> <p>The layers with the probability of the discrete classification and the standard deviation of the cover fractions are only provided for the base year (epoch 2015). The Change Consistency Layer that checks consistency between classifier and break detection, is only available for this near-real time epoch</p> <p> </p> <p><a href="https://africa.lcviewer.vito.be/2018">View the maps and area statistics</a></p> <p><a href="https://land.copernicus.eu/global/documents/lcc100/all/pum">Product User Manual</a></p> <p><a href="https://land.copernicus.eu/global/products/lc">More land cover change product information and documentation</a></p>
Copernicus Global Land Service: Land Cover 100m: epoch 2017: Africa demo (deprecated)
<p><strong><em>This demo dataset over Africa is deprecated. Please see <a href="https://doi.org/10.5281/zenodo.3518035">this global dataset</a> instead.</em></strong></p> <p>emonstration land cover maps over Africa at 100m resolution for epoch year 2017, from the global component of the Copernicus Land Service and derived from PROBA-V satellite observations.</p> <p>The maps include the main discrete classification (23 classes aligned with UN-FAO's LCCS), a set of cover fractions (%) for the 10 main classes and additional quality layers (e.g. density of input data).</p> <p>For the consolidated epoch 2017, the classifier and regression models of base year 2015 are used, and the time window of the classified metrics covers one full year prior (2016) and pastor (2018) data. The layers with the probability of the discrete classification and the standard deviation of the cover fractions are only provided for the base year (epoch 2015). The Change Consistency Layer that checks consistency between classifier and break detection, is only available for the most recent (near-real time) year (epoch 2018).</p> <p> </p> <p><a href="https://africa.lcviewer.vito.be/2017">View the maps and area statistics</a></p> <p><a href="https://land.copernicus.eu/global/documents/lcc100/all/pum">Product User Manual</a></p> <p><a href="https://land.copernicus.eu/global/products/lc">More land cover change product information and documentation</a></p> <p> </p>
Copernicus Global Land Service: Land Cover 100m: epoch 2015: Africa demo (deprecated)
<p><strong><em>This demo dataset over Africa is deprecated. Please see <a href="https://doi.org/10.5281/zenodo.3243508">this global dataset</a> instead.</em></strong></p> <p>Demonstration land cover maps over Africa at 100m resolution for epoch year 2015, from the global component of the Copernicus Land Service and derived from PROBA-V satellite observations.</p> <p>The maps include the main discrete classification (23 classes aligned with UN-FAO's LCCS), a set of cover fractions (%) for the 10 main classes and additional quality layers (e.g. density of input data).</p> <p>As a base year, the classification and regression models for 2015 are saved for re-use in subsequent consolidated (with full year prior and pastor observations) and near-real time years (with full year prior and 3 months pastor data). The layers with the probability of the discrete classification and the standard deviation of the cover fractions are only provided for this base epoch. The Change Consistency Layer that checks consistency between classifier and break detection, is only available for the most recent (near-real time) epoch (2018).</p> <p> </p> <p><a href="https://africa.lcviewer.vito.be/2015">View the maps and area statistics</a></p> <p><a href="https://land.copernicus.eu/global/documents/lcc100/all/pum">Product User Manual</a></p> <p><a href="https://land.copernicus.eu/global/products/lc">More land cover change product information and documentation</a></p> <p> </p>
InterFlex WP3 data set_ SGAM diagrams_interface data base_service identification
<p>This data set contains the InterFlex demonstration use case descriptions in the form of SGAM diagrams as well as the interface data base which was used for different deliverables and the repective results within work package 3 "Impact and deployment analysis of the innovative solutions". There has also been one publication in this regard ( <a href="https://doi.org/10.1109/INDIN.2018.8472053">10.1109/INDIN.2018.8472053</a>)</p> <p>Furthermore, it includes the service mappings for the InterFlex (under GA 731289) demonstrators as an input for different WP3 3.1 subtasks, deliverbale (D3.2) as well as a scientific publication (ICRERA 2019, ID 239, online ISSN: 2572-6013)</p>
Data and R Code from "A novel approach to sustainability assessment of food supply chains using networks of ecosystem services"
<p>Data and R code from this paper applying network analysis (iGraph) to two case studies pre and post agroecological transitions in Central America and Tanzania, Africa from the IPES-Food report. Further descriptions of this data and code can be found within the extended manuscript. R Code relies on the data from the scenarios (e.g., Nodes and Relations CSVs) and creates the output network metrics (e.g., Node Metric CSVs). </p>
Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2018: Globe
<p>Consolidated epoch 2018 from the Collection 3 of annual, global 100m land cover maps.</p> <p>Other available epochs: <a href="https://doi.org/10.5281/zenodo.3939038">2015</a> <a href="https://doi.org/10.5281/zenodo.3518026">2016</a> <a href="https://doi.org/10.5281/zenodo.3518036">2017</a> <a href="https://doi.org/10.5281/zenodo.3939050">2019</a></p> <p>Produced by the global component of the Copernicus Land Service, derived from PROBA-V satellite observations and ancillary datasets.</p> <p>The maps include </p> <ul> <li>a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System,</li> <li>a set of versatile cover fractions: percentage (%) of ground cover for the 10 main classes</li> <li>a forest type layer</li> <li>quality layers on input data density and on the confidence of the detected land cover change</li> </ul> <p><a href="https://land.copernicus.eu/global/lcviewer">Click here to view the maps</a></p> <p><a href="https://land.copernicus.eu/global/lcviewer">More information about the land cover maps</a></p> <p><a href="https://doi.org/10.5281/zenodo.3606295">Product User Manual</a></p>
Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2017: Globe
<p>Consolidated epoch 2017 from the Collection 3 of annual, global 100m land cover maps.</p> <p>Other available epochs: <a href="https://doi.org/10.5281/zenodo.3939038">2015</a> <a href="https://doi.org/10.5281/zenodo.3518026">2016</a> <a href="https://doi.org/10.5281/zenodo.3518038">2018</a> <a href="https://doi.org/10.5281/zenodo.3939050">2019</a></p> <p>Produced by the global component of the Copernicus Land Service, derived from PROBA-V satellite observations and ancillary datasets.</p> <p>The maps include</p> <ul> <li>a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System,</li> <li>a set of versatile cover fractions: percentage (%) of ground cover for the 10 main classes</li> <li>a forest type layer</li> <li>quality layers on input data density and on the confidence of the detected land cover change</li> </ul> <p><a href="https://land.copernicus.eu/global/lcviewer">Click here to view the maps</a></p> <p><a href="https://land.copernicus.eu/global/lcviewer">More information about the land cover maps</a></p> <p><a href="https://doi.org/10.5281/zenodo.3606295">Product User Manual</a></p>
Copernicus Global Land Service: Land Cover 100m: collection 3: epoch 2019: Globe
<p>Near real time epoch 2019 from the Collection 3 of annual, global 100m land cover maps.</p> <p>Other available epochs: <a href="https://doi.org/10.5281/zenodo.3939038">2015</a> <a href="https://doi.org/10.5281/zenodo.3518026">2016</a> <a href="https://doi.org/10.5281/zenodo.3518036">2017</a> <a href="https://doi.org/10.5281/zenodo.3518038">2018</a></p> <p>Produced by the global component of the Copernicus Land Service, derived from PROBA-V satellite observations and ancillary datasets.</p> <p>The maps include</p> <ul> <li>a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System,</li> <li>a set of versatile cover fractions: percentage (%) of ground cover for the 10 main classes</li> <li>a forest type layer</li> <li>quality layers on input data density and on the confidence of the detected land cover change</li> </ul> <p><a href="https://land.copernicus.eu/global/lcviewer">Click here to view the maps</a></p> <p><a href="https://land.copernicus.eu/global/lcviewer">More information about the land cover maps</a></p> <p><a href="https://doi.org/10.5281/zenodo.3606295">Product User Manual</a></p>
Network properties data and code used in "Ecological plasticity governs ecosystem services in multilayer networks".
<p>Code and network properties data used in the analyses presented in "Ecological plasticity governs ecosystem services in multilayer networks". Further information can be requested of the author David A. Bohan (David.Bohan@inrae.fr).</p>
Collected recommendations and requirements for FAIR-enabling services
<p>Within FAIRsFAIR task 2.4, we carried out a structured literature review to extract requirements, recommendations and other desiderata for FAIR-enabling services. This document contains the full list of excerpts, structured and annotated. This work has been used as input for the basic framework on FAIRness of services developed by FAIRsFAIR task 2.4 (see https://doi.org/10.5281/zenodo.4292599).</p>
Analysed data from interviews on FAIR-enabling services
<p>Within FAIRsFAIR task 2.4, we carried out five semi-structured interviews with data service owners to understand how services currently support the FAIR principles, what are transferable insights and recommendations, and what are common challenges and pitfalls. This document collects the insights captured from the interviews. This work has been used as input for the basic framework on FAIRness of services developed by FAIRsFAIR task 2.4 (see https://doi.org/10.5281/zenodo.4292599).</p> <p> </p>
Land cover, landscape metrics and typology of European cities for Urban Forest Ecosystem Services (UFES) evaluation
<p>The data refers to the paper "<em>Urban Forests as Regulating Ecosystems: Types and Ranking of European Cities</em>"</p> <p>The datasets provide a typology for 689 European urban areas, the land cover metrics and landscape metrics used to create the typology and the Urban Forest Ecosystem Services (UFES) indexes created from them.</p> <p>The typology of Urban Forest Ecosystem Services (UFES) presents 10 clusters of cities aggregated into 4 groups: Forest cities, Anthropogenic cities, Herbaceous cities and Standard European cities. The data can be used to support urban planning policies at local and regional scales; in urban forestry, urban form and ecosystem services work related at different spatial scales. The metrics used capture the spatial integration of different layers of natural, semi-natural and artificial land within functional urban areas.</p> <p> </p> <p>The datasets are a csv file (<code>Metrics.csv</code>) and a shapefile (<code>UFES.shp</code>) of polygons with attributes.</p> <ul> <li> <p><code>UFES.shp</code> attributes' are the following: FUA codes, country name, main city name, clusters and groups of FUAs resulting from the hierarchical cluster analysis (HCA), the R color codes used in the article, the five UFES budget indexes as well as an aggregated global UFES index for each FUA.</p> </li> <li> <p><code>Metrics.csv</code> contains the FUA codes, the land cover and landscape metrics used in the HCA.</p> </li> </ul> <p> </p>
2020 Stakeholder Survey of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) - Quantitative Dataset
<p>This dataset is the outcome of a survey of IPBES stakeholders that was conducted in May-June 2020. The aim of this survey is to better understand stakeholder engagement with IPBES, to improve implementation of the IPBES stakeholder engagement strategy (decision IPBES-3/4 presented in document IPBES/3/18), and to further increase the inclusivity and effectiveness of the IPBES work programme. Results will help, among others, to better align communication and outreach, and to strengthen collaborative processes within the IPBES work programme.</p> <p><br> This dataset presents only the quantitative data of the complete dataset of responses. It has been anonymised and all personal comments in response to open questions have been removed. For information, the full anonymised dataset has been published on Zenodo, with restricted access (see DOI: <a href="http://doi.org/10.5281/zenodo.4121916">10.5281/zenodo.4121916</a>).</p> <p>This dataset is under restricted access and embargoed until after the eighth session of IPBES Plenary. For any inquiry, please contact IPBES Head of Communications (stakeholders@ipbes.net). </p>
Example Instantiations of the e-Infrastructure Catalogue of Services
<p>This document contains example instantiations of the e-Infrastructure Catalogue of Services. This supports a published framework for creating a Catalogue of Services (CoS), primarily intended for e-Infrastructure services, which describes services at a high level and makes them discoverable.</p>
Sentinel-1 InSAR Browse Service Image of the October 2016 Central Italian Earthquakes
<p>The surface deformation caused by the central Italian earthquakes which occured in October 2016 is captured in this terrain corrected interferogram produced by the Sentinel-1 InSAR Browse Service for the Geohazards Exploitation Platform.</p> <p>Two earthquakes occured on 26<sup>th</sup> October and one on 30<sup>th</sup> October. The Sentinel-1 datasets were acquired on 26-10-2016 for the master and 01-11-2016 for the slave from a descending pass so that the line of sight deformation is viewed from the east.</p> <p>Contains modified Copernicus Sentinel data (2016), processed by DLR/ESA/Terradue.</p>
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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.