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2,371 results for “platform”
Fig. 12 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 12. System structure of Database of Korean National Species List. Grey rectangles represent systems related to the Database of National Species List of Korea and blue rectangles indicates systems using species information via Database of National Species List of Korea outside of NIBR. Black arrows indicate utilization of taxonomic information from the Database of National Species List of Korea and Grey arrows present communication with institutes outside of NIBR. Dotted grey arrow means commination channel will be established soon.
Fig. 1 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 1. Database structure of Database of Korean National Species List. (A) Presents relationship of major entities of the Database of Korean National Species List. Black thick lines are n:m relationship and blue arrows show detailed content types of each entity. (B) displays example of hierarchical relations of higher taxa originated from two different systems, KNSL and APG IV.
Fig. 6 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 6. Download page of Korean National Species List. This web page provides the download link of National Species List of Korea in the main page of the platform for biodiversity in Korea (http://www.kbr.go.kr/).
Fig. 3 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 3. Tree interface of taxon. (A) Shows interface to search by management groups, rank, and name. Yellow arrow indicates fold- er icon which open all higher nodes of the taxon up and grey arrow shows check icon which provides detailed information of the taxon. (B) displays tree interface for hierarchical structure of taxa. Plus icon indicated by blue arrow means open the lower taxa in the specific taxon, and each node (orange arrow) represents each taxon.
Fig. 11 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 11. Web interface of reporting tools in Database of Korean National Species List. (A) Presents the basket of report. Dotted box presents option of generating reports. (B) shows the list of tasks registered for generating report. (C) displays three different formats of report generated by the Database of National Species List of Korea.
WP7 platform_analysis
<p>Datasets from a scientific publication for the <a href="http://www.designfornext.org/">Design for Next conference</a> (and published in <a href="http://www.tandfonline.com/toc/rfdj20/20/sup1?nav=tocList">The Design Journal</a>) and a software library that try to answer to this research question: <em>how could the analysis of social interactions over time on such platforms improve the understanding of design-related collaborative processes? </em>The dataset includes social network analysis of three cases of Maker initiatives developed in GitHub repositories.</p> <p>See also <a href="http://make-it.io/open-data-api/">http://make-it.io/open-data-api/</a></p> <p> </p>
BRAIN Journal-Pros and Cons Gamification and Gaming in Classroom-Figure 3. Number of platform visits/week during first and second semester
<p>Figure 3 shows the number of course/activities accesses, per week, for the first and the second semester. Combining this with a lower rate of activities completion (not shown here) for the second semester, it is empirically proved that the introduction of the ranking block did not have the assumed motivational effect for students. A good explanation could be the fact that the top 4 students were at the end of semester far ahead from the others, which, most probably weakened the group motivation. </p>
BRAIN Journal-Pros and Cons Gamification and Gaming in Classroom-Figure 2. Course categories within UVAB University Moodle platform, (portal-eifr.ub.ro)
<p>A study was conducted aiming to assess the impact of introduction of ranking block plugin as a gamification element within Moodle learning management system (Ranking block Moodle, 2017). We mention that the Moodle platform, version 3.2 is dedicated to extramural and distance learning. It supports various gamification elements such as avatars, badges, leaderboard, levels, displaying quiz results or progress bars. The ranking block plugin was introduced and configured to be available for procedural programming course activities, at the beginning of the first semester of 2016, which starts in October. It displays a course leaderboard visible to all users as a way of obtaining recognition from other users. It is based on points instead of badges and it can monitor included activities based on accumulated points. The experiment involved first year bachelor students in computer science (32 students, extramural education) from UVAB University (www.ub.ro) who are using the Moodle platform in their tutorial based activities. The main page of UVAB Moodle platform is presented in Figure 2. </p>
Platform Specific Metamodel in Ecore for developing learning ecosystems
<p>The learning ecosystem metamodel is a M2-model instantiated from Ecore, a M3-model in the four-layer metamodel architecture of OMG. The main objective of this metamodel is to provide a Platform Specific Model (PSM) for describing learning ecosystems build from Open Source software components, human elements and information flows between components which are represented by web services.</p>
Structure and Function of the Nuclear Pore Complex Cytoplasmic mRNA Export Platform
<p>These scripts demonstrate the use of <a href="https://integrativemodeling.org/">IMP</a>, <a href="https://salilab.org/modeller">MODELLER</a>, and <a href="https://github.com/salilab/pmi">PMI</a> in the modeling of the Nup82 complex using DSS/EDC chemical cross-links and electron microscopy (EM) 2D class averages.</p> <p>First, <a href="https://salilab.org/modeller">MODELLER</a> is used to generate initial structures for the individual components in the Nup82 complex. Then, IMP is used to model these components using DSS/EDC crosslinks and the electron microscopy 2D class averages for the entire Nup82 complex.</p> <p>The modeling protocol will work with a default build of IMP, but for most effective sampling, IMP should be built with <a href="https://integrativemodeling.org/2.5.0/doc/ref/namespaceIMP_1_1mpi.html">MPI</a> so that replica exchange can be used.</p> <p><strong>For more information</strong> about how to reproduce this modeling, see the <a href="https://salilab.org/nup82/">Sali lab website</a> or the README file.</p>
Cloud management platform evaluation data generated by CMP²
<p>This repository contains exemplary results from using the CMP² (Comparing Cloud Management Platforms) testbed on CloudcheckR, ManageIQ, MistIO, Boto and Libcloud. The results give insight into the performance of multi-cloud middleware. All experiments were conducted as research in education linked to the Cloud Accounting and Billing research initiative at Service Prototyping Lab, Zurich University of Applied Sciences, Switzerland. Apart from the raw data in JSON format, generated graphs are also included.</p> <p> </p>
Research data supporting "A robust liposomal platform for direct colorimetric detection of sphingomyelinase enzyme and inhibitors"
<p>Raw research data supporting the publication: Holme, M. N. et al., ACS Nano, 2018, DOI: 10.1021/acsnano.8b03308.</p>
Illustrative Darwin core archive to input data on a citizen science platform from a collection management system
<p>Illustrative DwC archive to send data from a collection management system to a citizen sciences platform. This illustrative archive displays the specimens used for the trans-institutional and trans-platform pilot project held in the frame of ICEDIG.</p> <p>Further description of its content in the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a collection management system to a citizen science platform, multi-imaged case
<p>Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Multi-imaged vertebrate specimen case : http://coldb.mnhn.fr/catalognumber/mnhn/zo/2013-152</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a collection management system to a citizen science platform, simple case
<p>Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Simple case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p03558024</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Companion for Visual Performance Analysis of Memory Behavior in a Task-Based Runtime on Hybrid Platforms
<p>This is the companion data for the CCGRID2019 submission paper entitled: Visual Performance Analysis of Memory Behavior in a Task-Based Runtime on Hybrid Platforms by Lucas Leandro Nesi, Samuel Thibault, Luka Stanisic and Lucas Mello Schnorr. All the data, source code, and images generation scripts used in the paper are presented here.</p>
Summary for policymakers of the assessment report on land degradation and restoration of the Intergovernmental SciencePolicy Platform on Biodiversity and Ecosystem Services: Figure SPM.1
<p>The purpose of Figure SPM.1 is to support the statement that land degradation occurs just about everywhere in the world (i.e. it is ‘pervasive’), takes many forms, and that examples of successful restoration are also widespread. The figure consists of a backdrop map of the world from a multiple land degradation perspective, showing the level of uncertainty between studies, overlaid with dots representing all the places specifically mentioned in the eight chapters of the main Assessment Report on Land Degradation and Restoration, including case studies of both degradation and restoration. Around the map are brief notes regarding the main forms of degradation encountered.</p>
Video Game Platform Mapping
<p>The diggr platform mapping provides a mapping, reference and grouping for platform strings of various video game databases. It is meant to ease mapping and matching of releases, local releases or games in general which are to be found in these databases.</p> <p>This is meant as a first step towards unification of platform identification.</p> <p> </p>
Draft genome assemblies of killifish from the Fundulus genus with ONT and Illumina sequencing platforms
<p>Four species from the genus Fundulus were selected for genome sequencing to study the physiological and genetic mechanisms that diverge between euryhaline and stenohaline freshwater species within this cyprinodontiform order of ray-finned fishes.</p>
SELIS platform for pan-European logistics applications datasets
<p>This publication comes as a result of the SELIS H2020 project (<a href="http://www.selisproject.eu">http://www.selisproject.eu</a>). The provided datasets are anonymized samples of the real data which describe some of the use cases we have encountered.</p> <p>In the interest of the Open Research Data Pilot, this publication (<a href="https://github.com/selisproject/selis-node-connectors">https://github.com/selisproject/selis-node-connectors</a>) provides a basic implementation of connectors used in real world applications for supply chain participants to connect and funnel their data to the SELIS Community Node (SCN). The prototype of the SELIS big data analytics and machine learning infrastructure is also openly available (<a href="https://github.com/selisproject/bda">https://github.com/selisproject/bda</a>).</p> <p>Along with the connectors, obfuscated/test data is also provided for each solution. The connectors all follow the same approach, which is parsing the data provided, transforming them into a SCN-compatible data exchange model and publishing them to the SCN under a specific configuration. The samples provided cover two use cases:</p> <p><strong>Adria Kombi Data set: </strong>This anonymized data set which includes 24 csv files describes a use case developed for the SELIS project. It involves the (as accurate as possible) estimation of time of arrival (ETA) for individual freight trains using historical data and live feeds.</p> <p><strong>SONAE Data set: </strong>This anonymized data set which includes 2 csv files describes a different use case developed for the same project. This specific use case involves the automatic generation of suggested order forecasts for a retailer (SONAE) given stock level data from different warehouses and information such as lead time (minimum time required from order till delivery) per product and supplier, delivery days etc.</p> <p> </p> <p><em>For a more detailed description of the data please refer to the README.md files included in the downloadable zipped directories.</em></p> <p> </p> <p> </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.