scholarly journals ASpecD: A Modular Framework for the Analysis of Spectroscopic Data Focussing on Reproducibility and Good Scientific Practice

2021 ◽  
Author(s):  
Jara Popp ◽  
Till Biskup
Keyword(s):  
Data Analysis ◽  
Best Practices ◽  
Spectroscopic Data ◽  
Scientific Practice ◽  
Scientific Software ◽  
Good Scientific Practice ◽  
Viable Approach ◽  
Python Programming ◽  
User Friendly ◽  
Processing Steps

Reproducibility is at the heart of science. However, most published results usually lack the information necessary to be independently reproduced. Even more, most authors will not be able to reproduce the results from a few years ago due to lacking a gap-less record of every processing and analysis step including all parameters involved. There is only one way to overcome this problem: developing robust tools for data analysis that, while maintaining a maximum of flexibility in their application, allow the user to perform advanced processing steps in a scientifically sound way. At the same time, the only viable approach for reproducible and traceable analysis is to relieve the user of the responsibility for logging all processing steps and their parameters. This can only be achieved by using a system that takes care of these crucial though often neglected tasks. Here, we present a solution to this problem: a framework for the analysis of spectroscopic data (ASpecD) written in the Python programming language that can be used without any actual programming needed. This framework is made available open-source and free of charge and focusses on usability, small footprint and modularity while ensuring reproducibility and good scientific practice. Furthermore, we present a set of best practices and design rules for scientific software development and data analysis. Together, this empowers scientists to focus on their research minimising the need to implement complex software tools while ensuring full reproducibility. We anticipate this to have a major impact on reproducibility and good scientific practice, as we raise the awareness of their importance, summarise proven best practices and present a working user-friendly software solution.

scholarly journals ASpecD: A Modular Framework for the Analysis of Spectroscopic Data Focussing on Reproducibility and Good Scientific Practice

2021 ◽  
Author(s):  
Jara Popp ◽  
Till Biskup
Keyword(s):  
Data Analysis ◽  
Best Practices ◽  
Spectroscopic Data ◽  
Scientific Practice ◽  
Scientific Software ◽  
Good Scientific Practice ◽  
Viable Approach ◽  
Python Programming ◽  
User Friendly ◽  
Processing Steps

Reproducibility is at the heart of science. However, most published results usually lack the information necessary to be independently reproduced. Even more, most authors will not be able to reproduce the results from a few years ago due to lacking a gap-less record of every processing and analysis step including all parameters involved. There is only one way to overcome this problem: developing robust tools for data analysis that, while maintaining a maximum of flexibility in their application, allow the user to perform advanced processing steps in a scientifically sound way. At the same time, the only viable approach for reproducible and traceable analysis is to relieve the user of the responsibility for logging all processing steps and their parameters. This can only be achieved by using a system that takes care of these crucial though often neglected tasks. Here, we present a solution to this problem: a framework for the analysis of spectroscopic data (ASpecD) written in the Python programming language that can be used without any actual programming needed. This framework is made available open-source and free of charge and focusses on usability, small footprint and modularity while ensuring reproducibility and good scientific practice. Furthermore, we present a set of best practices and design rules for scientific software development and data analysis. Together, this empowers scientists to focus on their research minimising the need to implement complex software tools while ensuring full reproducibility. We anticipate this to have a major impact on reproducibility and good scientific practice, as we raise the awareness of their importance, summarise proven best practices and present a working user-friendly software solution.

Justifying the data analytical choice in single case research in relation to the expected data pattern

2019 ◽  
Author(s):  
Rumen Manolov
Keyword(s):  
Data Analysis ◽  
Visual Analysis ◽  
Multilevel Models ◽  
Single Case ◽  
Analytical Techniques ◽  
Real Data ◽  
Small Scale ◽  
Data User ◽  
Single Case Research ◽  
User Friendly

The lack of consensus regarding the most appropriate analytical techniques for single-case experimental designs data requires justifying the choice of any specific analytical option. The current text mentions some of the arguments, provided by methodologists and statisticians, in favor of several analytical techniques. Additionally, a small-scale literature review is performed in order to explore if and how applied researchers justify the analytical choices that they make. The review suggests that certain practices are not sufficiently explained. In order to improve the reporting regarding the data analytical decisions, it is proposed to choose and justify the data analytical approach prior to gathering the data. As a possible justification for data analysis plan, we propose using as a basis the expected the data pattern (specifically, the expectation about an improving baseline trend and about the immediate or progressive nature of the intervention effect). Although there are multiple alternatives for single-case data analysis, the current text focuses on visual analysis and multilevel models and illustrates an application of these analytical options with real data. User-friendly software is also developed.

scholarly journals Using Participatory Design to Design an eHealth Well-Being Program

2021 ◽  
Vol 18 (14) ◽  
pp. 7250
Author(s):  
Yannick van Hierden ◽  
Timo Dietrich ◽  
Sharyn Rundle-Thiele
Keyword(s):  
Best Practices ◽  
Health Professionals ◽  
Participatory Design ◽  
Online Community ◽  
Well Being ◽  
Proof Of Concept ◽  
End User ◽  
Ehealth Intervention ◽  
Pilot Intervention ◽  
User Friendly

In recent years, the relevance of eHealth interventions has become increasingly evident. However, a sequential procedural application to cocreating eHealth interventions is currently lacking. This paper demonstrates the implementation of a participatory design (PD) process to inform the design of an eHealth intervention aiming to enhance well-being. PD sessions were conducted with 57 people across four sessions. Within PD sessions participants experienced prototype activities, provided feedback and designed program interventions. A 5-week eHealth well-being intervention focusing on lifestyle, habits, physical activity, and meditation was proposed. The program is suggested to be delivered through online workshops and online community interaction. A five-step PD process emerged; namely, (1) collecting best practices, (2) participatory discovery, (3) initial proof-of-concept, (4) participatory prototyping, and (5) pilot intervention proof-of-concept finalisation. Health professionals, behaviour change practitioners and program planners can adopt this process to ensure end-user cocreation using the five-step process. The five-step PD process may help to create user-friendly programs.

scholarly journals XRD Data Visualization, Processing and Analysis with d1Dplot and d2Dplot Software Packages

Proceedings ◽  
2020 ◽  
Vol 62 (1) ◽  
pp. 9
Author(s):  
Oriol Vallcorba ◽  
Jordi Rius
Keyword(s):  
Data Analysis ◽  
Data Visualization ◽  
X Ray Diffraction ◽  
Specific Data ◽  
X Ray ◽  
Software Packages ◽  
Compound Database ◽  
Synchrotron Light ◽  
User Friendly ◽  
Transformation Processes

The d1Dplot and d2Dplot computer programs have been developed as user-friendly tools for the inspection and processing of 1D and 2D X-ray diffraction (XRD) data, respectively. d1Dplot provides general tools for data processing and includes the ability to generate comprehensive 2D plots of multiple patterns to easily follow transformation processes. d2Dplot is a full package for 2D XRD data. Besides general processing tools, it includes specific data analysis routines for the application of the through-the-substrate methodology [Rius et al. IUCrJ 2015, 2, 452–463]. Both programs allow the creation of a user compound database for the identification of crystalline phases. The software can be downloaded from the ALBA Synchrotron Light Source website and can be used free of charge for non-commercial and academic purposes.

scholarly journals Quality Assessment for the Sustainable Provision of Software Components and Digital Research Infrastructures for the Arts and Humanities

2017 ◽  
Vol 41 (2) ◽  
Author(s):  
Stefan Buddenbohm ◽  
Markus Matoni ◽  
Stefan Schmunk ◽  
Carsten Thiel
Keyword(s):  
Quality Assessment ◽  
Digital Humanities ◽  
Scientific Practice ◽  
Software Components ◽  
Good Scientific Practice ◽  
Arts And Humanities ◽  
Research Publications ◽  
The Arts ◽  
Research Infrastructures ◽  
Digital Research

AbstractInfrastructure for facilitating access to and reuse of research publications and data is well established nowadays. However, such is not the case for software. In spite of documentation and reusability of software being recognised as good scientific practice, and a growing demand for them, the infrastructure and services necessary for software are still in their infancy. This paper explores how quality assessment may be utilised for evaluating the infrastructure for software, and to ascertain the effort required to archive software and make it available for future use. The paper focuses specifically on digital humanities and related ESFRI projects.

scholarly journals A Model for Promoting Inclusive and Sustainable Tourism in Kota Lama Semarang

2020 ◽  
Vol 55 (5) ◽  
Author(s):  
Syaiful Amin ◽  
Suwito Eko Pramono ◽  
Atno ◽  
Ganda Febri Kurniawan
Keyword(s):  
Social Media ◽  
Data Analysis ◽  
Qualitative Analysis ◽  
Qualitative Methods ◽  
Sustainable Tourism ◽  
Development Plan ◽  
Tourism Destination ◽  
New Model ◽  
Descriptive Approach ◽  
User Friendly

Kota Lama Semarang, also known as Semarang Old Town in Central of Java Province, Indonesia, has the potential to become an inclusive and sustainable tourism destination, in accordance with the Indonesian government’s development plan. However, its potential has not been promoted publicly in the best ways. The aim of this research is to describe and develop a model for promoting inclusive and sustainable tourism in the area. The research applies qualitative methods and takes a descriptive approach. The data were collected using observation and interviews, while data analysis was performed using Creswell's descriptive qualitative analysis. The Sejarah di Dekatku (History Near Us) application (the new model), together with social media promotion, provides an alternative way of promoting tourism. During a trial launch, the application was appreciated by the tourists who used it. The application is considered easy to use and suitable for the needs of the community. It features themes of inclusivity and education, and it is considered important for the promotion of historical areas of Semarang. The advantages of using the application to help develop Kota Lama Semarang tourism are that it is easy to use and navigate, it has attractive features, and it provides easy-to-understand information. Our research suggests that the application should be launched immediately and used as a way of promoting the area. In addition, features and interfaces should be developed further to make the application even more attractive and user-friendly. This can be done by researching and developing the features and the interface of the application to make it more attractive and user-friendly.

scholarly journals Online Integrated Development Environment (IDE) in Supporting Computer Programming Learning Process during COVID-19 Pandemic: A Comparative Analysis

2020 ◽  
Vol 9 (2) ◽  
pp. 66-71
Author(s):  
Kartikadyota Kusumaningtyas ◽  
Eko Dwi Nugroho ◽  
Adri Priadana
Keyword(s):  
Comparative Analysis ◽  
Computer Programming ◽  
Learning Material ◽  
Integrated Development Environment ◽  
Development Environment ◽  
Integrated Development ◽  
Data Usage ◽  
Study Programs ◽  
Python Programming ◽  
User Friendly

COVID-19 has spread to various countries and affected many sectors, including education. New challenges arise in universities with study programs related to computer programming, which require a lot of practice. Difficulties encountered when students should setting up the environment needed to carry out programming practices. Furthermore, they should install a text editor called Integrated Development Environment (IDE) to support it. There is various online IDE that supports computer programming. However, students must have an internet connection to use it. After all, many students cannot afford to buy internet quotas to access online learning material during the COVID-19 pandemic. According to these problems, this study compares several online IDEs based on internet data usage and the necessary supporting libraries' availability. In this study, we only compared eleven online IDEs that support the Python programming language, free to access, and do not require logging in. Based on the comparative analysis, three online IDEs have most libraries supported. They are REPL.IT, CODECHEF, and IDEONE. Based on internet data usage, REPL.IT is an online IDE that requires the least transferred data. Moreover, this online IDE also has a user-friendly interface to place the left and right sides' code and output positions. It prevents the user from scrolling to see the results of the code that has been executed. The absence of advertisements also makes this online IDE a more focused appearance. Therefore, REPL.IT is highly recommended for users who have a limited internet quota, primarily to support the learning phase of computer programming during the COVID-19 pandemic.

scholarly journals Extraction and Determinationof Chemical Structure from flower Dicholomethane Extract of Catharanthus roseus

2021 ◽  
Vol 68 (2) ◽  
Author(s):  
Shahin Aziza ◽  
Koushik Sahab ◽  
Md. Abdus Satter Miac ◽  
Md. Hemayet Hossaina
Keyword(s):  
Data Analysis ◽  
Oleanolic Acid ◽  
Catharanthus Roseus ◽  
Spectroscopic Data ◽  
Chemical Structure

Catharanthus roseus is considered a cooling medicine. Two compounds: ?-sitosterol (1) and 3?-Hydroxy-lup-20 (29)-en-28-oic acid or Oleanolic acid (2) have been isolated from flowers from Dicholoromethane extract of Catharanthus roseus. By different spectroscopic data analysis the structures of the compounds have been established.

scholarly journals FastqCleaner: an interactive Bioconductor application for quality-control, filtering and trimming of FASTQ files

2018 ◽  
Author(s):  
Leandro Gabriel Roser ◽  
Fernán Agüero ◽  
Daniel Oscar Sánchez
Keyword(s):  
Quality Control ◽  
Data Analysis ◽  
The Novel ◽  
Web Environment ◽  
Ngs Data Analysis ◽  
Novel Concept ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Analysis Platform

AbstractBackgroundExploration and processing of FASTQ files are the first steps in state-of-the-art data analysis workflows of Next Generation Sequencing (NGS) platforms. The large amount of data generated by these technologies has put a challenge in terms of rapid analysis and visualization of sequencing information. Recent integration of the R data analysis platform with web visual frameworks has stimulated the development of user-friendly, powerful, and dynamic NGS data analysis applications.ResultsThis paper presents FastqCleaner, a Bioconductor visual application for both quality-control (QC) and pre-processing of FASTQ files. The interface shows diagnostic information for the input and output data and allows to select a series of filtering and trimming operations in an interactive framework. FastqCleaner combines the technology of Bioconductor for NGS data analysis with the data visualization advantages of a web environment.ConclusionsFastqCleaner is an user-friendly, offline-capable tool that enables access to advanced Bioconductor infrastructure. The novel concept of a Bioconductor interactive application that can be used without the need for programming skills, makes FastqCleaner a valuable resource for NGS data analysis.

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