Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
13,276
datasets available to search
ShareScore release 0.9.0
Dataset results
13,276 results for “IT management”
Fig. 1 in Do managed bees drive parasite spread and emergence in wild bees?
Fig. 1. The key factors that may drive disease emergence within and between populations of managed and wild bees. Adapted from Daszak et al. (2000).
Fig. 9 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 9. Web page of management of common names in Database of Korean National Species List. This web page displays the list of common names registered in the database.
Fig. 8 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 8. Web pages of management function of special list of species defined by law. (A) Presents the web interface of searching taxon with five functions. (B) shows the list of registered species defined by law with Korean name.
Fig. 10 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 10. Web pages of management of references in Database of Korean National Species List. (A) Shows the list of references with function to assign references to taxa. (B) Web interface of function assigning reference to taxa.
Fig. 7 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 7. Web page of list of special list of species defined by law. This web page provides management function of special list of species defined by law.
Fig. 5 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 5. Introduction page of Korean National Species List. Introduction page of National Species List of Korea in the platform for biodiversity in Korea (http://www.kbr.go.kr/content/view.do?menuKey = 446&contentKey = 14).
Fig. 4 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 4. Web interface of list of taxa with search options. (A) Displays complex interface for searching taxon. (B) is the list view of taxa searched. (C) shows the example of brief information of taxon which will be appeared by clicking KTSN number in the list view.
Fig. 2 in Database of National Species List of Korea: the taxonomical systematics platform for managing scientific names of Korean native species
Fig. 2. Web interface of taxon in Database of Korean National Species List. (A) Provides hierarchical structure of taxon with the tree interface. (B) shows basic information of taxon including KTSN, species properties, representative common names, and status of KTSN. (C) displays ranks, names, common names, identifiers, origins and etc. (D) displays information higher taxa based on hierarchical systems. (E) shows the list of synonyms. (F) is the list of references related to this taxon. (G) is the list of all common names except representative name.
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.
Figure 2 in Generalist ground-nesting bees dominate diversity survey in intensively managed agricultural land
Figure 2. Species richness compared between sampling periods. Dark grey bars: species from the genus Andrena Fabricius (Andrenidae); light grey bars: species from the genera: Halictus Latreille, Lasioglossum Curtis (Halictidae), Osmia Panzer (Megachilidae), and Nomada Scopoli (Apidae); black bars: species from the genus Bombus Latreille (Apidae). Different letters above the dark grey bars indicate a significant statistical difference between sampling periods in total species richness of all sampled genera (F (3, 42) = 20.01, p<0.001).
Figure 1 in Generalist ground-nesting bees dominate diversity survey in intensively managed agricultural land
Figure 1. Total number of bees sampled in this study at the four different sampling periods. Dark grey bars: individuals from the genus Andrena Fabricius (Andrenidae); light grey bars: individuals from the genera: Halictus Latreille, Lasioglossum Curtis (Halictidae), Osmia Panzer (Megachilidae), and Nomada Scopoli (Apidae); black bars: individuals from the genus Bombus Latreille (Apidae). Different letters above the dark grey bars indicate a significant statistical difference between sampling periods in activity-density of individuals from all sampled genera (F (3, 42) = 18.89, p<0.001).
Figure 3. Traditional Approach and Process Management System Approach – Effort Percentage Comparison-Business Process Management – A Traditional Approach versus a Knowledge Based Approach
<p>Comparing the results obtained in using the two approaches (Figure 3), it is possible to note<br> a significant reduction in terms of both effort and working hours in correspondence of design and<br> development phases.</p>
Figure 1. Azure management portal and VM with two Delphi desktop apps-Early Warning of Heat/Cold Waves as a Smart City Subsystem: A Retrospective Case Study of Non-anticipative Analog Methodology
<p><br> Nowadays, only D-Wave Systems Company produces commercially the 2nd generation<br> adiabatic quantum computer with up to 512 flux qubits (project code name ″Vesuvius″). They are<br> microscopic loops of niobium metal that are capable of quantum behavior at low temperatures.<br> Hence, electrical currents in the loops can flow in clockwise (+1) or counterclockwise (-1)<br> direction, or both, when in quantum superposition. Qubits are connected to neighbors according to<br> the topology of quantum processor. The hardware is controlled by a framework of Josephson<br> junctions that allow individual qubit values to be stored and read, and to influence the states of<br> neighboring qubits.</p>
Database of Pines from the Forests paper: "Intraspecific Variation in Pines from the Trans-Mexican Volcanic Belt Grown Under Two Watering Regimes: Implications for Management of Genetic Resources"
<p>Raw data from the Forests paper: "Intraspecific Variation in Pines from the Trans-Mexican Volcanic Belt Grown under Two Watering Regimes: Implications for Management of Genetic Resources" Forests <strong>2018</strong> <em>9</em>(2), 71. doi:<a href="http://dx.doi.org/10.3390/f9020071">10.3390/f9020071. </a></p> <p>The database correspond to seedlings of four Mexican pines: <em>P. oocarpa, P. patula</em> and <em>P. pseudostrobus</em>, that were submitted to two watering treatments: Field Capacity (FC) and Drought-Stress (DS), during 90 days. Growth and biomass, survival and ontogenetic score were measured.</p>
Dataset for: Developing research data management services and support for researchers: a mixed methods study
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manuscript: <br> Perrier L, Barnes L. Developing research data management services and support for researchers: a mixed methods study. Partnership. 2018;13(1). doi: doi.org/10.21083/partnership.v13i1.4115.</p> <p>Full-text available at: <a href="https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202">https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202</a></p> <p><strong>Data and Documentation Files</strong></p> <p>Five files make up the dataset: </p> <ol> <li>Coding Scheme: RDMServicesSupport_Codes.txt</li> <li>Transcript, Focus Group 01 (anonymized): RDMServicesSupport_FocusGroup01.pdf</li> <li>Transcript, Focus Group 02 (anonymized): RDMServicesSupport_FocusGroup02.pdf</li> <li>Transcript, Focus Group 03 (anonymized): RDMServicesSupport_FocusGroup03.pdf</li> <li>Transcript, Focus Group 04 (anonymized): RDMServicesSupport_FocusGroup04.pdf</li> </ol> <p>Contact: Laure Perrier: <a href="https://journal.lib.uoguelph.ca/index.php/perj/article/view/4115/4202">orcid.org/0000-0001-9941-7129</a></p>
RAGE pilot data from 1st evaluation of the Sports Team Manager game on soft skills for employability
<p><strong>General description: </strong>The dataset includes data from the first evaluation pilot which tested the Sports team manager game developed by PlayGen for the Okkam use case.</p> <p><strong>Topic</strong><br> ACM CSS 2012: Human Computer Interaction (HCI) design and evaluation methods<br> PsycINFO Classification: 3620 Personnel Management & Selection & Training; 2228 Occupational & Employment Testing</p> <p><strong>Name entitites</strong><br> Organizational information: OKKAM, in collaboration with University of Trento<br> Geographical information: Italy<br> Time information: May-June 2017</p> <p><strong>Types</strong>: Excel</p> <p><strong>RAGCS target group:</strong> end users: other user groups</p> <p><strong>Evaluation dimensions</strong><br> Evaluation object: Sports Team Manager game<br> Methodology/design: within subjects design<br> Evaluation variables: usability, user experience, learning</p> <p><strong>Instruments:</strong> 1. Questionnaire on Usability Game User Experience Satisfaction Scale (GUESS; Phan, Keebler, & Chaparro, 2016) – Usability subscale; 2. questionnaire on User Experience including 3 subscales: Enjoyment (GUESS -Enjoyment subscale); Usefulness (Intrinsic Motivation Questionnaire, IMI; Ryan, 1982) - Subscale Value/Usefulness; Flow (Flow Short Scale, FSS, Rheinberg et al., 2003; Vollmeyer & Rheinberg, 2006); 3. Pre-post questionnaire on learning; 4. Focus interview</p> <p><strong>Knowledge/skill elements</strong><br> RAGCS skills: cognitive skills: evaluating, analysing; affective skills: interpersonal skills<br> ESCO skills: social interaction (<a href="http://data.europa.eu/esco/skill/8f18f987-33e2-4228-9efb-65de25d03330">http://data.europa.eu/esco/skill/8f18f987-33e2-4228-9efb-65de25d03330)</a>; accept constructive criticism (<a href="http://data.europa.eu/esco/skill/a311ab20-75df-4aff-8016-3142c5659d30">http://data.europa.eu/esco/skill/a311ab20-75df-4aff-8016-3142c5659d30</a>); work in teams (<a href="http://data.europa.eu/esco/skill/60c78287-22eb-4103-9c8c-28deaa460da0">http://data.europa.eu/esco/skill/60c78287-22eb-4103-9c8c-28deaa460da0</a>); negotiate compromise <a href="http://data.europa.eu/esco/skill/7954861c-86d4-4529-afbb-2c23dab9ac74">(http://data.europa.eu/esco/skill/7954861c-86d4-4529-afbb-2c23dab9ac74)</a>; lead others (<a href="http://data.europa.eu/esco/skill/75d8e5d9-bef3-418b-9011-01bff9f27207">http://data.europa.eu/esco/skill/75d8e5d9-bef3-418b-9011-01bff9f27207</a>); motivate others <a href="http://data.europa.eu/esco/skill/e2d44a9b-f28c-489e-9861-b654b5ded507">(http://data.europa.eu/esco/skill/e2d44a9b-f28c-489e-9861-b654b5ded507</a>); support colleagues (<a href="http://data.europa.eu/esco/skill/95a41cf5-4037-4c96-91a8-c34b41637224">http://data.europa.eu/esco/skill/95a41cf5-4037-4c96-91a8-c34b41637224</a>); manage time <a href="http://data.europa.eu/esco/skill/d9013e0e-e937-43d5-ab71-0e917ee882b8">(http://data.europa.eu/esco/skill/d9013e0e-e937-43d5-ab71-0e917ee882b8</a>); make decisions (<a href="http://data.europa.eu/esco/skill/d62d2b4c-a6f8-439e-8a1b-4f29ab5f2c47">http://data.europa.eu/esco/skill/d62d2b4c-a6f8-439e-8a1b-4f29ab5f2c47</a>); develop strategies to solve problems (<a href="http://data.europa.eu/esco/skill/7a8fb784-67fa-41e9-a75c-6b491d91f800">http://data.europa.eu/esco/skill/7a8fb784-67fa-41e9-a75c-6b491d91f800</a>); evaluate information (<a href="http://data.europa.eu/esco/skill/7dd94ad3-13d6-43fe-8b94-51fcbf67ced9">http://data.europa.eu/esco/skill/7dd94ad3-13d6-43fe-8b94-51fcbf67ced9)</a><br> <br> <strong>Relationships</strong>: D8.3 First RAGE Evaluation Report<br> Related dataset: <a href="https://doi.org/10.5281/zenodo.2564742">10.5281/zenodo.2564742</a></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.