Graphical Representation Of Data Research Articles

BSXplorer: analytical framework for exploratory analysis of BS-seq data

BackgroundBisulfite sequencing detects and quantifies DNA methylation patterns, contributing to our understanding of gene expression regulation, genome stability maintenance, conservation of epigenetic mechanisms across divergent taxa, epigenetic inheritance and, eventually, phenotypic variation. Graphical representation of methylation data is crucial in exploring epigenetic regulation on a genome-wide scale in both plants and animals. This is especially relevant for non-model organisms with poorly annotated genomes and/or organisms where genome sequences are not yet assembled on chromosome level. Despite being a technology of choice to profile DNA methylation for many years now there are surprisingly few lightweight and robust standalone tools available for efficient graphical analysis of data in non-model systems. This significantly limits evolutionary studies and agrigenomics research. BSXplorer is a tool specifically developed to fill this gap and assist researchers in explorative data analysis and in visualising and interpreting bisulfite sequencing data more easily.ResultsBSXplorer provides in-depth graphical analysis of sequencing data encompassing (a) profiling of methylation levels in metagenes or in user-defined regions using line plots and heatmaps, generation of summary statistics charts, (b) enabling comparative analyses of methylation patterns across experimental samples, methylation contexts and species, and (c) identification of modules sharing similar methylation signatures at functional genomic elements. The tool processes methylation data quickly and offers API and CLI capabilities, along with the ability to create high-quality figures suitable for publication.ConclusionsBSXplorer facilitates efficient methylation data mining, contrasting and visualization, making it an easy-to-use package that is highly useful for epigenetic research.

Practice-Based Learning in Aesthetic Medicine: Assessing Scientific Literacy Among Cosmetic Practitioners.

The field of aesthetic medicine has expanded substantially in the past decade, with significant practitioner diversification and departure from core-specialty supervision. The increased autonomy of nonphysician practitioners in a rapidly evolving field has raised accentuated the importance of scientific literacy and practice-based learning standards in the delivery of aesthetic medical care. To assess the degree of scientific literacy among aesthetic medicine practitioners of different educational and training backgrounds in the United States and abroad. A cross-sectional survey of 52 national and international aesthetic medicine practitioners employing a validated, 28-item, scientific literacy tool. The average score for all participants was 76% (SD = 18%, range = 43%-100%). Physician practitioners scored higher in all competencies compared non-physicians (86% vs 68%, p < 0.001), with a greater discrepancy among US practitioners (95% vs 71%, p < 0.001). Competencies relating to identification of bias/confounding variables, graphical data representation, and statistical inference/correlation showed the lowest proficiency. Practitioners with a doctorate or equivalent degree were significantly more likely to report frequent engagement with medical literature than non-physicians (p = 0.02). There exists a significant disparity in scientific literacy between physician and nonphysician aesthetic medicine practitioners. This gap underscores the need for enhanced educational programs and continuous professional development to ensure safe and effective patient care in the evolving field of aesthetic medicine.

Evaluating secondary school students’ science literacy with the Test of Scientific Literacy Skills (TOSLS)

As solutions to today’s global challenges, such as climate change and environmental protection, will increasingly depend on technological and scientific innovation, it is essential for Generation Z to gain a solid foundation in science. The Test of Scientific Literacy Skills (TOSLS) was used to assess the level of science literacy of students. This paper presents the results of the TOSLS testing of students aged 16-19 in several grammar schools in the Czech Republic in 2023 and compares them with the results of the TOSLS testing of students in the Slovak Republic in 2015. We found that Czech students in their final year of high school performed statistically significantly better on the TOSLS test in approximately two thirds of the items than Slovak students. For both groups of students, we observed good results in skills focused on evaluating scientific information, reading and interpreting graphical representations of data, and solving problems using quantitative skills, including basic statistical skills. On the contrary, the students had difficulty with skills related to understanding the elements of research design and their impact on scientific findings and understanding and interpreting basic statistical data.

THE IMPACT OF RECESS  BREAKS IN THE LEARNING PROCESS ON PRIMARY SCHOOL STUDENTS’ CONCENTRATION SKILLS

Nowadays one of the major problems in education is the lack of a specific strategy for the implementation of breaks (recess policy) in an educational institution. The development of such a strategy in the majority of cases is different for every school, as evaluating several factors is required, e.g., the age of students, interests, learning needs and progress, the location and specialization of the school, etc. However, students` awareness of the necessity for individual recess strategy gains importance as well. The research aim is to investigate and clarify the possibilities and necessity of recess breaks in primary school. There are theoretical research methods and empirical research methods (students’, teachers’ and parents’ surveys), data processing and analysis methods (quantitative, graphical representation of data, data analysis using IBM SPSS v.22 predictive analytics and statistical analysis software package) used in the research. The analysis of students’ survey emphasized that students more often prefer listening to music or socializing during breaks. While parents’ questionnaire highlighted the necessity for their offsprings to spend more time outside in fresh air. They mean it would help their children to better concentrate in lessons. While teachers` survey analysis revealed that students concentration is better if students are more interested in a particular subject.

Validity, reliability, and item characteristics of cell material science literacy assessment instruments

This study aims to examine the validity, reliability, and item characteristics of scientific literacy assessment instruments on cell material. The scientific literacy ability category includes identifying valid scientific arguments, evaluating the validity of a source, evaluating the use and misuse of scientific information, understanding research design elements and how they impact scientific findings, and reading and interpreting graphical representations of data. The research subjects were students of the 5th semester elementary school teacher education study program. The validity test included content validity using Aiken V validity index and construct validity using Exploratory Factor Analysis (EFA). Reliability test is carried out by looking for the price of the reliability coefficient r with correlation product moment test. The characteristic test is carried out by determining the level of difficulty and discriminating power. The results show that the scientific literacy assessment instrument on cell material is a valid instrument based on the analysis of content validity, construct validity, and item characteristics. Thus, the assessment instrument is suitable for use as an assessment instrument in research to measure students' scientific literacy in cell material.

Digitalization Strategies for Marketing Communications to Build Relationship Marketing: Modern Solutions in Brand Management

The content presented in this article explores the emergence and progression of digital marketing on a global scale. This article aims to elucidate the primary drivers behind the evolution of digital marketing, tracing its origins from the inception of early information transmission technologies to the establishment of high-speed Internet platforms operated by prominent companies and the proliferation of online resources offering diverse products and services. Furthermore, this work encompasses a comprehensive chronicle of the evolutionary trajectory of marketing strategies employed by enterprises for engaging with their consumers and prospective buyers. Within the scope of this article, an overview is provided on the contemporary landscape of digital marketing, highlighting its various forms and their utilization within the scientific and theoretical domain as well as practical applications within a diverse spectrum of companies. Additionally, the article presents empirical research findings on the multifaceted interactions between marketing initiatives and their target audience, employing diverse communication channels and methodologies. Statistical metrics and graphical representations are employed to elucidate the growth and maturation of the digital marketing field, offering insights into industry-specific trends, geographical variations, and the financial investments committed to this evolving domain. This article also delves into various Internet platforms that have significantly influenced the evolution of digital communications within the realm of commerce. The author systematically elucidates the distinctive approaches adopted by these platforms in advancing digital marketing strategies. Moreover, the article underscores the manifold advantages of digital marketing, with particular emphasis on the substantial reduction in transaction costs and the mitigation of governmental regulatory interference in economic activities. This reduction in regulatory influence is attributed to the emergence and consolidation of novel formal and informal protocols governing both domestic and international online transactions. Furthermore, it is observed that the digitalization of trade has hastened the globalization of economic relations, simplifying trade interactions and eradicating geographical boundaries between nations, particularly in the context of promoting branded products. In addition, the author underscores the critical importance of adhering to specific guidelines to gain a competitive edge through the utilization of digital communication technologies and tools. These guidelines encompass comprehensive knowledge about consumer and buyer behavior, analytical processing of sales data, rigorous assessment of key performance indicators against financial expenditures, optimization of return on invested capital and intellectual resources, and the development of a crisis model that encompasses challenges related to the synergy between financial operations, resource allocation, and marketing activities. Methodologically, this study employs a range of research methodologies including historiographic description, comparative analysis, synthesis of information and opinions, forecasting, tabular and graphical data representation, as well as modeling to elucidate strategic objectives and development trajectories.

Determination of the Chemical Properties of Honey from Suba Region, Homa Bay County-Kenya

Purpose: The purpose of this study was to determine the chemical properties of honey produced in the Suba region, specifically in the Suba South Sub-County, Gwassi North and South divisions' four regions, Nyandiwa (Western), Tonga (Northern), Magunga (Eastern), and Nyancha (Central) of Homa Bay County, Kenya. The study focuses on assessing the chemical properties of honey such as pH, free acidity, HMF content, proline content, glucose content, fructose content, sucrose content and mineral concentrations (K,Na,Ca,Mg,Fe,Zn,and Mn) to ascertain whether they are within the acceptable limits  as set by the Codex Alimentarius Commissions.&#x0D; Methodology: An experimental approach was used to investigate the various chemical properties of honey sourced from the four regions of the Suba region in Homa Bay County. Codex Alimentarius Commission's defined methods were used to analyze each property. Both primary and secondary data were collected using interviews and purposive sampling techniques to collect a total of 40 honey samples.  A pH meter, UV-visible spectrophotometer, and HPLC instruments were used to measure the pH, free acidity, HMF content, proline content, fructose content, glucose content, and sucrose content of the honey, respectively. The levels of minerals were measured using AAS for Na and K, while Ca, Zn, Mg, Mn, and Fe using a flame photometer. Statistical Package for Social Sciences version 21 was used to perform various statistical tests and generate graphical representations of data. The collected samples were analysed at the Kenyatta University Research Laboratory.&#x0D; Findings: The findings showed that the chemical properties had the following mean values for the honey sample: pH = 4.01± 0.03, free acidity = 35.83±0.45 mEq/kg, HMF = 19.95±1.76 mg/kg, proline = 629.77±9.80 mg/kg, sum of glucose and fructose = 68.37±0.51%. While for the minerals, manganese was the least common and potassium the most common. The mean values result of this study show that honey from the Suba region satisfies the set standards by Codex Alimentarius Commission.&#x0D; Unique Contribution to Theory, Practice and Policy: The study validates the theory of international standards in honey production, emphasizing the positive impact of aligning with global benchmarks on honey quality and market acceptance in the Suba region. It emphasizes the importance of quality certification, which contributes to consumer trust and economic growth. The research also supports the theory through sensitization and education, which increase awareness about honey quality and educate beekeepers on proper production techniques. The study advocates for economic diversification through sustainable apiculture, resulting in improvements in economic stability and financial well-being in the Suba region.

Analysis of Water Consumption during Fire Extinguishing at Objects of Different Functional Fire Hazard Classes

   Introduction. Fire-fighting water supply systems play a primary role in ensuring effective fire extinguishing. Many researchers both in our country and abroad have considered the requirements for fire-fighting water supply and problematic issues in this area. At the same time, in order to update the requirements for fire-fighting water supply, it is necessary to study the actual water consumption on fires, taking into account the characteristics of fire objects.   The aim of this research was to analyze the water consumption for outdoor firefighting depending on the characteristics of the fire object and compare the actual water consumption with the requirements of regulatory documents on fire safety.   Methods and Materials. The authors used statistical data on fires in the Russian Federation for 2019–2021 from the federal state information system "Federal Database "Fires". Methods of statistical data analysis and classification of statistical data were used to determine the actual water consumption for outdoor firefighting, depending on the class of functional fire hazard of the fire object. Visualization of the obtained results was performed by the method of graphical representation of data in the form of histograms and pie charts.   Results. The analysis showed that the highest average water consumption was required for objects of the functional fire hazard class F1.2 "hotels, dormitories (with the exception of apartment-type dormitories), dormitory buildings of sanatoriums and rest homes of general type, campsites" — 10.7 l/s. For apartment buildings, the highest average water consumption was required to extinguish fires that had arisen in the attic — 10 l/s and in the garret — 9.2 l/s.   Discussion and Conclusion. The results of the analysis can be used to clarify the requirements for water consumption for outdoor firefighting, depending on the functional fire hazard class of the object and the number of floors of buildings. In order to meet these requirements, regular monitoring of fire-fighting water supply systems is required, as well as timely maintenance and repair of external and internal fire-fighting water supply systems.

RWD7 Graphical Representation of Real-World Data for Analysing Infection Outbreaks Within a Tertiary Hospital Setting: A Data-Driven Approach

RWD7 Graphical Representation of Real-World Data for Analysing Infection Outbreaks Within a Tertiary Hospital Setting: A Data-Driven Approach

The Issue of Selection of Appropriate Methodology and Methods of Graphical Representation of Data in Biomedical Research

Abstract The development of medicine is based on reliable medical research. This is a process that must be planned in detail and performed in accordance with the accepted study protocol, as any negligence – even a small one – or deviation from the protocol may result in distorted research results and – in consequence – to false conclusions. One of the key stages of research is the selection of the appropriate methodology, particularly in terms of tests that verify the posed hypotheses. Each statistical method has a set of assumptions that have to be met in order for the method to be used. This paper explains why the appropriate selection of methods, verification of the required assumptions, and correct graphical representation of the obtained results are so important from the practical perspective.

Learning analytics with iLearn Insights

iLearn Insights is an innovative online application to address the challenge of engaging, motivating and supporting students with automated personalised email for those at risk of failure. It allows academics to identify students who are engaging or otherwise with the Learning Management System (LMS) content, thus allowing early intervention, and ultimately improved retention in units by providing targeted support to a student cohort. In contrast to systems that provide only static data reports, this vendor-independent innovation was built in-house to analyse and visualise student learning data in relation to access patterns, forum activity, learning activity submission and grades to identify a student cohort that needs support, as well as enabling teaching staff to send personalised emails to students on the basis of their level of engagement and/or performance. Feedback has a powerful impact on learning, but students frequently highlight it as an area that can be improved in tertiary education (Dawson and Henderson, 2019). iLearn Insights provides graphical representation of LMS data that enables visual personalised feedback to students. Within three mouse clicks, academic staff can trigger a range of automated communications to commend high-achieving students, offer additional assistance to lower performing students or to recapture disengaged students. These emails can be a targeted to a group of students and configured by the unit convenor to contain motivating information including the top five resources accessed by classmates; a student’s mark in comparison to the class average; number or percentage of students that have already submitted an assignment; clickable links; and support resources for students falling behind. ILearn Insights was developed based on four principals of learning analytics design knowledge: integration, agency, reference frame and dialogue (Wise, 2014). It has been observed that targeted visual feedback with clickable links is the most effective way to engage students quickly.?The positive impact of iLearn Insights is demonstrated by its rapid uptake by teaching staff across Macquarie University. When it launched in Session 1, 2020, after 18 months of piloting, there were 478 users across 763 units (subjects) who sent 125334 targeted personalised emails. In Session 1, 2023 iLearn Insights was used by approximately 808 users across 40 departments and learning support areas and 1237 units, sending over 316576 targeted emails to encourage students to engage with learning activities or offer support. That represents an increase of 169% of users, 162% of units and 253% of emails in three years. These personalised email exchanges have led to enhanced student engagement, which is critical for student success (Kahu and Nelson, 2018; De Villiers and Werner, 2018; McClenney et al, 2012; Klem and Connell, 2004). 

Dimensionality reduction for detection of anomalies in the IoT traffic data

This paper concerns cybersecurity issues in one of the fastest growing fields of modern computer systems the Internet-of-Things (IoT). In this field, intrusion detection plays a significant role in allowing IoT systems’ safe functioning and continuous operation. Visualizing the IoT data using dimensionality reduction allows for an easy and straightforward traffic analysis based on a graphical data representation, eligible for interpretation even by non-experts. We present a study on IoT network intrusion detection using three dimensionality reduction methods, namely, the Self-Organizing Map (SOM), the t-distributed Stochastic Neighbor Embedding (t-SNE), and the Neighborhood Retrieval Visualizer (NeRV). We show that applying them to the IoT traffic allows for reducing the original traffic feature space to a 2-D one, where anomalies may be noticed visually as outliers. The purpose of our study and its original contribution is conducting a comparative analysis of the t-SNE versus NeRV dimensionality reduction approaches in both: theoretical and empirical aspects. We notice and point out specific significant differences between these methods, which, as we claim, are responsible for their different performance in the IoT field, which is validated by our empirical study on real-world IoT traffic datasets. The results of our experimental research provide an interesting insight into the behavior of the investigated techniques and confirm their effectiveness and usability in IoT anomalies detection.

Excelet for Simulation of Indium DSC Graph

Abstract Spreadsheets have amazing facilities for graphical representation of data. The computing power and the possibility to get the results without programming, interactivity by using controls make spreadsheets a powerful learning tool. Having as starting point an DSC curve for Indium performed between 120°C and 180°C, the shape of curve was modeled, by using Excel, under assumption that, before and after peak corresponding to melting transition, there is no dependence between specific heat of metal and temperature. Even the peak shape it not perfect symmetrical, it was modeled considering a gaussian distribution. Linear regression has been used for computing the medium values of specific heat in solid and liquid state and was used a spinner as interactive tool for peak shape control. Despite the model deficiencies, starting from specific heats, latent heat of melting and peak apex temperature it has been possible the simulation of DSC curve which was in a good correlation with the real one.

(Keynote) On Interpretation of Impedance Spectroscopy Data

Impedance spectroscopy represents a rich area of science that has been applied to many research disciplines, including those associated with corrosion and corrosion control, energy systems, and biological systems. In laboratory settings, impedance has been used to study the kinetics and mechanisms of electrochemical reactions. Impedance spectroscopy has also been applied in industrial applications to quality control and corrosion monitoring and constitutes the basis of a class of sensors [1].Impedance spectra are easily measured by used of modern instrumentation. The difficulty lies in interpretation of impedance spectra in terms of physically meaningful information. While graphical methods [2], distribution of relaxation times analyses [3], and measurement model analyses [4] can guide model development, interpretation is generally based on use of a deterministic model that describes the physics of the system under study [5]. Such models may be coupled with electrical circuits that account for the double layer formed at the electrified interface and for the electrolyte resistance. The deterministic model approach is often perceived as being much more complicated than use of electrical circuits alone because it requires mathematical expertise.In general, interpretation of the impedance response requires both a quantitative evaluation of the error structure of the impedance measurement and insight into the physics and chemistry of the system under study. Analysis of the error structure yields a standard deviation for the stochastic errors, which can be used to weight subsequent regressions. The error analysis also identifies the range of frequencies that are consistent with the Kramers–Kronig relations and are, therefore, suitable for regression analysis. The physical insight is used to guide the interpretation model development. It should be noted that interpretation models are not unique. The models may suggest other experiments which can be used to reject the proposed model. Greater confidence may be assigned to a model that explains a variety of experimental observations.The objective of this paper is to review our work on interpretation of impedance data, including the identification and quantification of the error structure associated with impedance spectroscopy measurements. The presentation makes use of a program that allows users to access the power of the measurement model concept and to fit custom process models [6].References S. Wang, J. Zhang, O. Gharbi, V. Vivier, M. Gao, and M. E. Orazem, “Electrochemical Impedance Spectroscopy,” Nat. Rev. Methods Primers, 1, 41 (2021), 1-21.M. E. Orazem, and N. Pébère, and B. Tribollet, “Enhanced Graphical Representation of Electrochemical Impedance Data,” J. Electrochem.Soc., 153 (2006), B129-B136.B. A. Boukamp, “Distribution (Function) of Relaxation Times, Successor to Complex Nonlinear Least Squares Analysis of Electrochemical Impedance Spectroscopy?” J. Phys. Energy, 4 (2020), 042001.H. Liao, W. Watson, A. Dizon, B. Tribollet, V. Vivier, and M. E. Orazem, “Physical Properties Obtained from Measurement Model Analysis of Impedance Measurements,” Electrochim. Acta, 354 (2020), 136747.V. Vivier and M. E. Orazem, “Impedance Analysis of Electrochemical Systems,” Chem. Rev., 122 (2022), 11131-11168.W. Watson and M. E. Orazem, EIS: Measurement Model Program, ECSArXiv, 2020, https://ecsarxiv.org/kze9x/.

Statistical and numerical analysis of unsteady hybrid nanoliquid flows over an elongating surface with oblique Lorentz force: A comparison of Cu–Al2O3/H2O, Cu–Al2O3/CH3OH and Cu–Al2O3/H2O–EG

The current work investigates the effects of oblique Lorentz force and Navier’s slip boundary condition on unsteady hybrid nanoliquid flow with three different base liquids (H2O, CH3OH and H2O–EG) across a nonlinearly elongating surface set in a porous medium. This research considers the effects of viscous–Ohmic dissipation, nonlinearly variable thermal radiation, internal heat source, the Soret effect, first-order chemical reaction and thermal and solutal jump conditions at the boundary. Proper thermo-physical relationships for the hybrid nanoliquid have been established. Rosseland’s estimate for an optically thick regime is used when calculating the heat flow owing to radiation. The dimensional governing equations are translated into nondimensional forms using appropriate similarity transformations. The velocity, energy and concentration fields are numerically solved using a shooting strategy based on the secant iteration and the Runge–Kutta–Fehlberg method. The physical implications of several essential parameters on the hybrid nanoliquid velocity, temperature and concentration are investigated using graphical and tabular representations of numerical data. Furthermore, the multiple (quadratic) regression analysis reveals that physical parameters strongly influence the local skin friction coefficient, Sherwood and Nusselt numbers. For continuously growing values of the unsteadiness parameter, the velocity, thermal and concentration scattering declined everywhere within the boundary layer region.

Theoretical basis of accounting payments to employees of health care institutions

The subject of research: theoretical and organizational aspects of personal military accounting at enterprises and directions for their improvement. The purpose of the study of issues of organization and maintenance of military records in Ukraine in the conditions of modern challenges and threats. Method or methodology for conducting research. The methodological basis of the research is the general scientific dialectical method, methods of induction, deduction. When studying the theory and current practice of military accounting at domestic enterprises, the methods of evaluation, comparison, comparison, grouping, and classification were used. When researching the normative and legal foundations of the organization of military accounting in Ukraine, its role in the implementation of the state's mobilization policy, the following were used: for the purpose of comprehensive knowledge of the object of research - dialectical method, methods of analysis and synthesis; to identify the advantages and disadvantages of various types of military accounting - the method of comparison and logical generalization; for the purpose of visual representation of the material, theoretical and practical provisions - a method of observation, generalization and graphic representation of data. The results of research and conclusions. The article examines current issues regarding the organizational and legal support of the organization and keeping military records in Ukraine. The peculiarities of the organization and maintenance of military accounting at enterprises were analyzed and critically evaluated, taking into account modern conditions. The components of the mechanism of effective interaction with the district (city) territorial centers of recruitment and social support in matters of military record keeping are defined, problems are outlined and ways to solve them are proposed.

Genomics data analysis via spectral shape and topology.

Mapper, a topological algorithm, is frequently used as an exploratory tool to build a graphical representation of data. This representation can help to gain a better understanding of the intrinsic shape of high-dimensional genomic data and to retain information that may be lost using standard dimension-reduction algorithms. We propose a novel workflow to process and analyze RNA-seq data from tumor and healthy subjects integrating Mapper, differential gene expression, and spectral shape analysis. Precisely, we show that a Gaussian mixture approximation method can be used to produce graphical structures that successfully separate tumor and healthy subjects, and produce two subgroups of tumor subjects. A further analysis using DESeq2, a popular tool for the detection of differentially expressed genes, shows that these two subgroups of tumor cells bear two distinct gene regulations, suggesting two discrete paths for forming lung cancer, which could not be highlighted by other popular clustering methods, including t-distributed stochastic neighbor embedding (t-SNE). Although Mapper shows promise in analyzing high-dimensional data, tools to statistically analyze Mapper graphical structures are limited in the existing literature. In this paper, we develop a scoring method using heat kernel signatures that provides an empirical setting for statistical inferences such as hypothesis testing, sensitivity analysis, and correlation analysis.

DO EMOTIONAL RESPONSES TO DATA VISUALISATION MOBILISE PEOPLE TO ACT? A CASE STUDY OF CLIMATE CHANGE VISUALISATIONS IN DIFFERENT NATIONAL CONTEXTS

This paper offers original insights into social media audiences’ emotional responses to data visualisations about climate change and how these responses play a role in mobilising participation in different national and geographical contexts. Understanding the role emotions play in engagements with graphic representations of data is important, because there is an increased circulation of data through visual representations in everyday life, and because emotions are vital components for making sense of data and for eliciting engagement. Despite this, sociological research has yet to explore emotional experiences of datavis and where they can lead. This paper uses a comparative mixed qualitative methods approach, incorporating semiotic analysis of thirteen datavis about climate change, nine semi-structured interviews with ten data visualisation professionals from six organisations who design, commission and/or disseminate data visualisations about climate change, thirty-four semi-structured interviews and thirteen follow-up interviews with diverse audience participants from the United Kingdom and Poland who responded to these data visualisations on social media. The paper argues that datavis can be seen as what I have called an ‘emotional repository’ of dynamic and complex emotional experiences. It can trigger multiple, simultaneous, and often contradictory emotions, relating mainly to the data that is the subject of the visualisation or aesthetic form. These emotions play an important role in mobilising audiences to participate in datafied democracies, more often on an individual and daily level, and less frequently on a collective and public scale. However, they do so in different ways, depending on geographical context and demographic characteristics.

Analysis of Flaws in Graphical Representations of Statistical Data in the Field of Occupational Safety and Health

A relevância dos dados estatísticos, na sociedade, impôs a urgência de garantir a literacia estatística de todos os indivíduos. Desta necessidade resultou um reforço do estudo da Estatística, com reflexo em todos os níveis de ensino, e com particular incidência na formação de profissionais cuja atividade envolverá o tratamento de dados estatísticos. Na área da segurança e saúde no trabalho, como noutras áreas, os profissionais envolvidos no processo de recolha, organização, análise e reporte de dados estatísticos, recorrem a diversos métodos e ferramentas estatísticas, que, no desfecho do processo, lhes permitirão apreciar, traduzir, revelar e comunicar a informação contida nos dados. Pelo importante contributo que os gráficos estatísticos proporcionam na tarefa de organização e apresentação de dados em relatórios, melhorando a eficácia na transmissão de informação, é imperioso garantir a correção e adequação destas representações. Na presente pesquisa, despoletada pela preocupação dos autores com a desadequação de muitos dos gráficos produzidos no âmbito de pesquisas no domínio da segurança e saúde no trabalho, analisámos os gráficos estatísticos presentes em três relatórios técnicos, no contexto da segurança e saúde no trabalho, focando os aspetos que violam os princípios orientadores da construção de gráficos estatísticos. Com este intuito assumimos uma investigação de abordagem exploratória, com recurso a métodos qualitativos, e recolha bibliográfica de dados. Os resultados revelam a presença de inúmeras debilidades nos gráficos, com violação de alguns dos mais importantes princípios que devem reger a construção de gráficos estatísticos, e que poderão comprometer a validade e utilidade desses gráficos.

Development of human-machine language interfaces for the visual analysis of complex biologics and RNA modalities and associated experimental data

The advent of recombinant protein-based therapeutic agents in the 1980s and subsequent waves of innovation in molecular biology and engineering of biologics has permitted the production of an increasingly broad array of complex, high molecular weight constructs. While this has opened a powerful new toolbox of molecular scaffolds with which to probe and interdict biological processes, it also makes deciphering the architectural nuances between individual constructs intuitively difficult. Key to downstream data processes for the detection of data trends is the ability to unambiguously identify, compare, and communicate the nature of molecular compositions. Existing small molecule orientated software tools are not intended for structures such as peptides, proteins, antibodies, and RNA, and do not contain adequate atomistic or domain-level detail to appropriately convey their higher structural complexity. Similarly, there is a paucity of large molecule-focused data analysis and visualization tools. This article will describe four new approaches we developed for the graphical representation and analysis of complex large molecules and experimental data. These tools help fulfill key needs in scientific communication and structure-property analysis of complex biologics and modified oligonucleotide-based drug candidates.