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93 results for “Dashboard”
Dashboard - Validação de Conceitos da Estrutura do Conhecimento sobre Administração em Enfermagem
<p>Trata-se de um painel de informações interativas sobre a epistemologia da Administração em Enfermagem, produzido no contexto da tese de doutorado do autor. O produto científico foi registrado sob o ISSN 2525-6602 (2022) e diagramado em formato de dashboard um único painel de informações interativas, cuja usabilidade pode facilitar o acesso da comunidade científica de Enfermagem aos achados mais relevantes sobre a epistemologia da Administração em Enfermagem.</p> <p>No canto superior esquerdo do dashboard, apresentam-se todas as unidades de conhecimento da taxonomia “Estrutura do Conhecimento sobre Administração em Enfermagem”. Ao clicar em qualquer um dos ícones com aspecto de mouse de uma determinada unidade de conhecimento, o painel traz automaticamente todas as informações bibliográficas e textuais da unidade de conhecimento que for selecionada. Se o usuário do painel desejar apreciar as informações de outra unidade de conhecimento, ele deve clicar no botão “RESTAURAR” e clicar novamente no ícone de mouse pertinente a outra unidade de conhecimento para ter a visão das informações sobre a nova unidade de conhecimento selecionada e, assim, sucessivamente para cada nova seleção.</p> <p>Logo abaixo aparecem informações sobre série histórica por décadas, titulação dos cientistas da enfermagem que produziram saber sobre a unidade de conhecimento selecionada e a perspectiva desse saber em comparação com o saber geral da Enfermagem brasileira. Ainda mais abaixo foi disponibilizada uma série e histórica anual para se ter uma ideia da frequência com que se produz ciência sobre a unidade de conhecimento selecionada.</p> <p>Na parte inferior esquerda, contém duas tabelas que apresentam o ranking dos dez cientistas da Enfermagem que mais se dedicaram em produzir conteúdo sobre a unidade de conhecimento selecionado e, o ranking das dez universidades onde o conteúdo da unidade de conhecimento selecionado foi gerado.</p> <p>Partindo agora para o canto superior direto, tem-se então, o nome e a definição conceitual da unidade de conhecimento selecionado, bem como, os valores de IVC e Kappa alcançados no processo de validação.<br> Se o usuário do painel clicar no ícone da definição, será apresentado um outro painel panorâmico contendo todas as informações de definição da taxonomia “Estrutura do Conhecimento sobre Administração em Enfermagem”. Se o usuário clicar no IVC, ele será direcionado para um outro painel contendo todas as informações, referências e expressões estatísticas empregadas na administração do IVC. O mesmo acontece se o usuário clicar no ícone Kappa. Se o usuário do painel clicar no termo “MÉTODO”, que está ao lado do IVC e Kappa, o usuário será direcionado para uma página contendo uma sítese das etapas metodológicas empregadas para alcançar os resultados apresentados.<br> Logo mais abaixo, apresenta-se um mapa geopolítico do Brasil, contendo a distribuição geográfica de origem do saber sobre Administração em Enfermagem petinente a cada unidade de conhecimento ora selecionada no canto superior esquerdo.</p> <p>Por fim, no canto inferior direito, pode-se apreciar a estrutura metodológica do que foi empregada na construção do saber sobre Administração em Enfermagem pertinente a qualquer uma das unidades de conhecimento selecionadas no canto superior esquer do dashboard.<br> O painel e o tutorial foram direcionados para o e-mail do coordenador de todos os cursos de enfermagem do Brasil registrados na plataforma Sucupira até fevereiro de 2022, solicitando que o material seja direcionado aos professores de Administração em Enfermagem. O mesmo material foi direcionado para o e-mail do coordenador de todos os grupos de pesquisas que contam com linha de pesquisa pertinente à Administração em Enfermagem disponível na base corrente do CNPq em fevereiro de 2022, solicitando que o material seja direcionado para os cientistas da Enfermagem que se ensinou ao estudo da Administração em Enfermagem. </p> <p>Por segurança, geralmente o Windows bloqueia a execução das macros quando é feito um download do arquivo e as interações podem ter mau funcionamento, você pode desbloquear as macros modificando as propriedades do arquivo da seguinte maneira:</p> <ol> <li> <p>Abra o Explorador de Arquivos do Windows e acesse a pasta onde você salvou o arquivo.</p> </li> <li> <p>Clique com o botão direito do mouse no arquivo e escolha <strong>Propriedades </strong>no menu de contexto.</p> </li> <li> <p>Na parte inferior da guia <strong>Geral</strong>, marque a caixa de seleção <strong>Desbloquear</strong> e selecione <strong>OK</strong>.</p> </li> </ol>
Dashboard Activated Services and Tele-Health for Heart Failure
ClinicalTrials.gov study NCT05001165. IPD Sharing: NO. Countries: 1. Publications: 2.
Understanding the Influence of Parameter Value Uncertainty on Climate Model Output: Developing an Interactive Web Dashboard
Open the record for dataset details and reuse information.
TRAFAIR Air Quality Dashboard
<p>Videos that show the functionalities of the TRAFAIR Air Quality Dashboard: a web application that was active betweeen 2020 and the beginning of 2023. The dashboard was realized within the scope of the TRAFAIR Eurpean Project.</p>
COREQ checklist for WW Dashboard research
Open the record for dataset details and reuse information.
Be.CULTOUR Dashboard - Local Impact Indicators for Circular Cultural Tourism
<p>Dashboard of indicators for circular cultural tourism impacts assessment</p>
NA-POPS Results and Dashboard
<p>Results from the 8 June 2021 model runs for NA-POPS. This also includes a Shiny dashboard to visualize results.</p>
Tell me more: a deeper dive into the FARMER'S DASHBOARD
<p><strong>The following video describes the functions of the ROMI farmers dashboard and its potentials for farm management and analytics. Funded by EU Grant 773875.</strong></p> <p><em>Videos are available in:</em></p> <ul> <li>Hi-res (1080p Apple ProRes)</li> <li>Mid-res (1080p H265)</li> </ul> <p><strong>Video script:</strong></p> <p><strong>(HANAPPE) </strong>The farmer's dashboard is a tool, where it's still not in its final form as it is now. Right now it's tailored to the work we do in ROMI, where we collect the data from the cable bot and have like overview of what's growing in the field, extract you know, how individual plants are growing, how well they're growing, and in the longer term it becomes part of a bigger farm management system where we'll combine it with you know this the planning of what will be grown and when. And for these small farms they they do several harvest during the year they have weekly vegetable baskets, so they need some planning upon what they will seed when, when they will harvest some of the crops what will be the composition of the vegetable baskets that they'll be selling. And using these statistics that we get, we can try to help them adapt or predict a little bit more, the harvesting and then and what they can be, and what they'll be selling. </p> <p><strong>(BAORI) </strong>Now this is not something that you're going to have on a laptop that you'll be walking around the farm with. It's something that you're more going to use for analytics at the end of the day. So if you think about a situation perhaps where you will be doing daily scans say on your crop, or weekly depending on the size of the crop, and how many rovers you've got and all that kind of stuff. You're going to be taking pictures of a whole bed and then at the end of the day that information will get uploaded to a computer that will then run some analytics and some metrics on what you're growing so you can have a little look and see where the areas for example of your crop are most productive, whether least productive, do you have an infestation, do you have some kind of disease in your crop, or is it just that it's very cold or something in that kind of, that area. And the crops are not responding as well as the rest. So once you start to put in place the scans and this information you type back to the rover's dashboard. It's all presented in a really easy kind of understandable presentation view, where you know anybody without even technical skill is going to be able to have a look and say oh there's a problem here.</p> <p><strong>(MINCHIN) </strong>So this parcel each parcel has a number and a geo reference which corresponds to the farmer's dashboard. And that means that we know both in space but also in a computer system what is planted where. This really helps when we're working in the field and we just want to know what's been done and what should be done, and then logging that back into the system. So just having a reference number allows us to be able to work in more detail</p> <p><strong>(HANAPPE) </strong>It becomes also I think an interesting data for research, so this data of growth of plants combined with weather data and so on. We can share between farms we can improve statistics so we can have like a better idea of what varieties grows well in what sort of conditions and so on. It is still open open question because there's of course a lot of parameters, but trying to start from something very concrete, potentially optimising the planning a bit over time we may be able to get some ideas about what varieties are well adapted in what regions and so on, and fine-tune how long it takes between seeding and harvesting and so on. So i see the farm bots evolve in that sense as a farm management system that combines data from the field like the data we get from the cable bot. That combines a planning that the farmer makes in the beginning of the year and potentially some modelling about how plants grow using these statistics that we've collected over the years. </p> <p><strong>(COLLIAUX) </strong>For the farmers dashboard we have plenty of pair of images where the images correspond, too close by position of the camera of a cable bot. And we want to know how what is the displacement of the camera between the two images so that we can adjust the images to stitch them together. And we do this for many images along the path of the cable bot, and you see here we can generate a map of the of a culture bed. And then we can generate many maps every day of the culture bed. And we can see the radishes and actually the weeds here grow along the week and then we detect each of the plants and we mat match them along days, so that we can grow the growth curve of each plant and gather statistics about their growth. So you see here occurs with the statistics for the growth of plants and we hope, as I said before, that this kind of information is useful for farmers to predict their harvest in the coming weeks and also to design and manage their field.</p>
Dashboard "Communication technologies used and parameters measured in Food Supply Chains in the scientific literature"
<p>This dashboard collects information about the communication technologies used and parameters measured in several scientific papers. Data can be filtered according to different criteria:</p> <ol> <li>Year of publication of the paper.</li> <li>Main topic in which the objetive of the paper is framed within.</li> <li>Stage of the food supply chain where the study is developed.</li> <li>Product group according to the Classification of Products by Activity (CPA) of the European Union.</li> </ol> <p>This dashboard was created by Manuel Amador Cervera for the University of Deusto in the context of the Horizon 2020 project "FOODRUS". The information contained in it refers to the scientific publications outlined in the table that can be found in the "References" sheet.<br> This project has received funding from the European Union’s Horizon 2020 Research & Innovation programme under Grant Agreement no. 101000617. This dashboard is the sole responsibility of the University of Deusto, and the European Union or any user is not liable for any use that may be made of the information contained therein.</p>
Rwanda Digital Dashboard Hybrid Type 3 Implementation Study
ClinicalTrials.gov study NCT06941831. IPD Sharing: YES. Countries: 1. Publications: 10.
Improving Engagement With a Process Measure Dashboard Through Precision Feedback
ClinicalTrials.gov study NCT06465667. IPD Sharing: NO. Countries: 1. Publications: 2.
An RCT Evaluation of a Diabetes Dashboard Team Model in Primary Care
ClinicalTrials.gov study NCT02156037. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Study of Remote Asthma Management Using an Integrated Artificial Intelligence-assisted EHR Dashboard and Mobile Device Compared With Usual Asthma Care to Treat 6-17 Year Old Patients
ClinicalTrials.gov study NCT06062433. IPD Sharing: NO. Countries: 1. Publications: 1.
PRISM: The PRimary Care Individual Social Norms MSK Data Dashboard: a Feasibility Trial
ClinicalTrials.gov study NCT07112508. IPD Sharing: NO. Countries: 0. Publications: 10.
Effect of a CKD Dashboard on Patient Activation and Shared Decision Making
ClinicalTrials.gov study NCT05931978. IPD Sharing: NO. Countries: 1. Publications: 10.
Precision IFX: Using a Dashboard to Individualize Infliximab Dosage
ClinicalTrials.gov study NCT02624037. IPD Sharing: Not stated. Countries: 1. Publications: 15.
Proactive Infliximab Optimization Using a Pharmacokinetic Dashboard Versus Standard of Care in Patients With Inflammatory Bowel Disease: The OPTIMIZE Trial
ClinicalTrials.gov study NCT04835506. IPD Sharing: YES. Countries: 2. Publications: 1.
Evaluating the Impact of an Equity Focused Dashboard and Clinical Support
ClinicalTrials.gov study NCT05278806. IPD Sharing: NO. Countries: 1. Publications: 1.
Evaluation of a Dashboard for Diabetes Care Integrated With the Electronic Health Record
ClinicalTrials.gov study NCT03826290. IPD Sharing: NO. Countries: 1. Publications: 3.
i-Dashboard for Multi-disciplinary Rounds in SICU
ClinicalTrials.gov study NCT04845698. IPD Sharing: NO. Countries: 1. Publications: 4.
ScienceDex guides
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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.