scholarly journals Meteo Browser South Tyrol: A Shiny App to download the meteorological time series from the Open Data Catalogue of the Province of Bolzano/Bozen - Italy

2019 ◽  
Vol 5 ◽  
Author(s):  
Giulio Genova ◽  
Mattia Rossi ◽  
Georg Niedrist ◽  
Stefano Della Chiesa

Meteo Browser South Tyrol is a user-friendly web-based application that helps to visualize and download the hydro-meteorological time series freely available in South Tyrol, Italy. It is designed for a wide range of users, from common citizens to students as well as researchers, private companies and the public administration. Meteo Browser South Tyrol is a Shiny App inside an R package and can be used on a local machine or accessed on-line. Drop down menus allow the user to select hydro-meteorological station and measurements. A simple map shows where the monitoring stations are, the latest measurements available, and lets the user subset the selected stations geographically by drawing a polygon.

2021 ◽  
Vol 7 ◽  
Author(s):  
Martin Palma ◽  
Alessandro Zandonai ◽  
Luca Cattani ◽  
Johannes Klotz ◽  
Giulio Genova ◽  
...  

Easily accessible data is an essential requirement for scientific data analysis. The Data Browser Matsch | Mazia was designed to provide a fast and comprehensible solution to access, visualize and download the microclimatic measurements of the IT 25 LT(S)ER Match | Mazia research site in South Tyrol, Northern Italy, with the overall aim to provide straightforward data accessibility and enhance dissemination. Data Browser Matsch | Mazia is a user-friendly web-based application to visualize and download micrometeorological and biophysical time series of the Long-Term Socio-Ecological Research site Matsch | Mazia in South Tyrol, Italy. It is designed both for the general public and researchers. The Data Browser Matsch | Mazia drop-down menus allow the user to query the InfluxDB database in the backend by selecting the measurements, time range, land use and elevation. Interactive Grafana dashboards show dynamic graphs of the time series.


2021 ◽  
Vol 22 (S6) ◽  
Author(s):  
Yasmine Mansour ◽  
Annie Chateau ◽  
Anna-Sophie Fiston-Lavier

Abstract Background Meiotic recombination is a vital biological process playing an essential role in genome's structural and functional dynamics. Genomes exhibit highly various recombination profiles along chromosomes associated with several chromatin states. However, eu-heterochromatin boundaries are not available nor easily provided for non-model organisms, especially for newly sequenced ones. Hence, we miss accurate local recombination rates necessary to address evolutionary questions. Results Here, we propose an automated computational tool, based on the Marey maps method, allowing to identify heterochromatin boundaries along chromosomes and estimating local recombination rates. Our method, called BREC (heterochromatin Boundaries and RECombination rate estimates) is non-genome-specific, running even on non-model genomes as long as genetic and physical maps are available. BREC is based on pure statistics and is data-driven, implying that good input data quality remains a strong requirement. Therefore, a data pre-processing module (data quality control and cleaning) is provided. Experiments show that BREC handles different markers' density and distribution issues. Conclusions BREC's heterochromatin boundaries have been validated with cytological equivalents experimentally generated on the fruit fly Drosophila melanogaster genome, for which BREC returns congruent corresponding values. Also, BREC's recombination rates have been compared with previously reported estimates. Based on the promising results, we believe our tool has the potential to help bring data science into the service of genome biology and evolution. We introduce BREC within an R-package and a Shiny web-based user-friendly application yielding a fast, easy-to-use, and broadly accessible resource. The BREC R-package is available at the GitHub repository https://github.com/GenomeStructureOrganization.


2021 ◽  
Author(s):  
Neal R Haddaway ◽  
Matthew J Page ◽  
Christopher C Pritchard ◽  
Luke A McGuinness

Background Reporting standards, such as PRISMA aim to ensure that the methods and results of systematic reviews are described in sufficient detail to allow full transparency. Flow diagrams in evidence syntheses allow the reader to rapidly understand the core procedures used in a review and examine the attrition of irrelevant records throughout the review process. Recent research suggests that use of flow diagrams in systematic reviews is poor and of low quality and called for standardised templates to facilitate better reporting in flow diagrams. The increasing options for interactivity provided by the Internet gives us an opportunity to support easy-to-use evidence synthesis tools, and here we report on the development of tools for the production of PRISMA 2020-compliant systematic review flow diagrams. Methods and Findings We developed a free-to-use, Open Source R package and web-based Shiny app to allow users to design PRISMA flow diagrams for their own systematic reviews. Our tools allow users to produce standardised visualisations that transparently document the methods and results of a systematic review process in a variety of formats. In addition, we provide the opportunity to produce interactive, web-based flow diagrams (exported as HTML files), that allow readers to click on boxes of the diagram and navigate to further details on methods, results or data files. We provide an interactive example here; https://driscoll.ntu.ac.uk/prisma/. Conclusions We have developed a user-friendly suite of tools for producing PRISMA 2020-compliant flow diagrams for users with coding experience and, importantly, for users without prior experience in coding by making use of Shiny. These free-to-use tools will make it easier to produce clear and PRISMA 2020-compliant systematic review flow diagrams. Significantly, users can also produce interactive flow diagrams for the first time, allowing readers of their reviews to smoothly and swiftly explore and navigate to further details of the methods and results of a review. We believe these tools will increase use of PRISMA flow diagrams, improve the compliance and quality of flow diagrams, and facilitate strong science communication of the methods and results of systematic reviews by making use of interactivity. We encourage the systematic review community to make use of these tools, and provide feedback to streamline and improve their usability and efficiency.


2015 ◽  
pp. 1586-1618
Author(s):  
Paula Díaz ◽  
Joan Masó

Users are playing an increasingly relevant role in geospatial data production. The traditional procedure for creating cartography, mainly by experts in official mapping agencies, has evolved into a more participative process for generating data: neogeography. Technology and the Internet are now user-friendly for a wide range of people who have become active users of global networks, such as GEOSS, INSPIRE, Eye On Earth, and EarthCube, and official producers need to adapt to the new era of openness, collaboration, and hybrid maps by adopting open standards. Although the creation of geospatial information is notably growing worldwide, and is enhanced by user-generated content, we may wonder whether this is a feasible alternative to official cartography. This chapter reviews the main geospatial networks based on both bottom-up and top-down data creation approaches, as well as the potentialities and limitations of user-generated content in the scientific field and in decision-making organisms.


Author(s):  
Naveen K. Bansal ◽  
Mehdi Maadooliat ◽  
Steven J. Schrodi

Abstract We consider a multiple hypotheses problem with directional alternatives in a decision theoretic framework. We obtain an empirical Bayes rule subject to a constraint on mixed directional false discovery rate (mdFDR≤α) under the semiparametric setting where the distribution of the test statistic is parametric, but the prior distribution is nonparametric. We proposed separate priors for the left tail and right tail alternatives as it may be required for many applications. The proposed Bayes rule is compared through simulation against rules proposed by Benjamini and Yekutieli and Efron. We illustrate the proposed methodology for two sets of data from biological experiments: HIV-transfected cell-line mRNA expression data, and a quantitative trait genome-wide SNP data set. We have developed a user-friendly web-based shiny App for the proposed method which is available through URL https://npseb.shinyapps.io/npseb/. The HIV and SNP data can be directly accessed, and the results presented in this paper can be executed.


2019 ◽  
Author(s):  
Birgit Möller ◽  
Hongmei Chen ◽  
Tino Schmidt ◽  
Axel Zieschank ◽  
Roman Patzak ◽  
...  

AbstractBackground and aimsMinirhizotrons are commonly used to study root turnover which is essential for understanding ecosystem carbon and nutrient cycling. Yet, extracting data from minirhizotron images requires intensive annotation effort. Existing annotation tools often lack flexibility and provide only a subset of the required functionality. To facilitate efficient root annotation in minirhizotrons, we present the user-friendly open source tool rhizoTrak.Methods and resultsrhizoTrak builds on TrakEM2 and is publically available as Fiji plugin. It uses treelines to represent branching structures in roots and assigns customizable status labels per root segment. rhizoTrak offers configuration options for visualization and various functions for root annotation mostly accessible via keyboard shortcuts. rhizoTrak allows time-series data import and particularly supports easy handling and annotation of time series images. This is facilitated via explicit temporal links (connectors) between roots which are automatically generated when copying annotations from one image to the next. rhizoTrak includes automatic consistency checks and guided procedures for resolving conflicts. It facilitates easy data exchange with other software by supporting open data formats.ConclusionsrhizoTrak covers the full range of functions required for user-friendly and efficient annotation of time-series images. Its flexibility and open source nature will foster efficient data acquisition procedures in root studies using minirhizotrons.


2020 ◽  
Author(s):  
Yasmine Mansour ◽  
Annie Chateau ◽  
Anna-Sophie Fiston-Lavier

AbstractMotivationMeiotic recombination is a vital biological process playing an essential role in genomes structural and functional dynamics. Genomes exhibit highly various recombination profiles along chromosomes associated with several chromatin states. However, eu-heterochromatin boundaries are not available nor easily provided for non-model organisms, especially for newly sequenced ones. Hence, we miss accurate local recombination rates, necessary to address evolutionary questions.ResultsHere, we propose an automated computational tool, based on the Marey maps method, allowing to identify heterochromatin boundaries along chromosomes and estimating local recombination rates. Our method, called BREC (heterochromatin Boundaries and RECombination rate estimates) is non-genome-specific, running even on non-model genomes as long as genetic and physical maps are available. BREC is based on pure statistics and is data-driven, implying that good input data quality remains a strong requirement. Therefore, a data pre-processing module (data quality control and cleaning) is provided. Experiments show that BREC handles different markers density and distribution issues. BREC’s heterochromatin boundaries have been validated with cytological equivalents experimentally generated on the fruit fly Drosophila melanogaster genome, for which BREC returns congruent corresponding values. Also, BREC’s recombination rates have been compared with previously reported estimates. Based on the promising results, we believe our tool has the potential to help bring data science into the service of genome biology and evolution. We introduce BREC within an R-package and a Shiny web-based user-friendly application yielding a fast, easy-to-use, and broadly accessible resource.AvailabilityBREC R-package is available at the GitHub repository https://github.com/ymansour21/BREC.


Author(s):  
Cecilia Avila-Garzon

Advances in semantic web technologies have rocketed the volume of linked data published on the web. In this regard, linked open data (LOD) has long been a topic of great interest in a wide range of fields (e.g. open government, business, culture, education, etc.). This article reports the results of a systematic literature review on LOD. 250 articles were reviewed for providing a general overview of the current applications, technologies, and methodologies for LOD. The main findings include: i) most of the studies conducted so far focus on the use of semantic web technologies and tools applied to contexts such as biology, social sciences, libraries, research, and education; ii) there is a lack of research with regard to a standardized methodology for managing LOD; and iii) a plenty of tools can be used for managing LOD, but most of them lack of user-friendly interfaces for querying datasets.


Author(s):  
Paula Díaz ◽  
Joan Masó

Users are playing an increasingly relevant role in geospatial data production. The traditional procedure for creating cartography, mainly by experts in official mapping agencies, has evolved into a more participative process for generating data: neogeography. Technology and the Internet are now user-friendly for a wide range of people who have become active users of global networks, such as GEOSS, INSPIRE, Eye On Earth, and EarthCube, and official producers need to adapt to the new era of openness, collaboration, and hybrid maps by adopting open standards. Although the creation of geospatial information is notably growing worldwide, and is enhanced by user-generated content, we may wonder whether this is a feasible alternative to official cartography. This chapter reviews the main geospatial networks based on both bottom-up and top-down data creation approaches, as well as the potentialities and limitations of user-generated content in the scientific field and in decision-making organisms.


2019 ◽  
Vol 34 (5) ◽  
pp. 551-561 ◽  
Author(s):  
Lakshman Abhilash ◽  
Vasu Sheeba

Research on circadian rhythms often requires researchers to estimate period, robustness/power, and phase of the rhythm. These are important to estimate, owing to the fact that they act as readouts of different features of the underlying clock. The commonly used tools, to this end, suffer from being very expensive, having very limited interactivity, being very cumbersome to use, or a combination of these. As a step toward remedying the inaccessibility to users who may not be able to afford them and to ease the analysis of biological time-series data, we have written RhythmicAlly, an open-source program using R and Shiny that has the following advantages: (1) it is free, (2) it allows subjective marking of phases on actograms, (3) it provides high interactivity with graphs, (4) it allows visualization and storing of data for a batch of individuals simultaneously, and (5) it does what other free programs do but with fewer mouse clicks, thereby being more efficient and user-friendly. Moreover, our program can be used for a wide range of ultradian, circadian, and infradian rhythms from a variety of organisms, some examples of which are described here. The first version of RhythmicAlly is available on Github, and we aim to maintain the program with subsequent versions having updated methods of visualizing and analyzing time-series data.


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