Information visualisation for science and policy: engaging users and avoiding bias

A Semantic Knowledge Graph of European Mountain Value Chains

The United Nations forecast a significant shift in global population distribution by 2050, with rural populations projected to decline. This decline will particularly challenge mountain areas' cultural heritage, well-being, and economic sustainability. Understanding the economic, environmental, and societal effects of rural population decline is particularly important in Europe, where mountainous regions are vital for supplying goods. The present paper describes a geospatially explicit semantic knowledge graph containing information on 454 European mountain value chains. It is the first large-size, structured collection of information on mountain value chains. Our graph, structured through ontology-based semantic modelling, offers representations of the value chains in the form of narratives. The graph was constructed semi-automatically from unstructured data provided by mountain-area expert scholars. It is accessible through a public repository and explorable through interactive Story Maps and a semantic Web service. Through semantic queries, we demonstrate that the graph allows for exploring territorial complexities and discovering new knowledge on mountain areas' environmental, societal, territory, and economic aspects that could help stem depopulation.

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

BACKGROUND

Exploring metagenomic contigs and "binning" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.

RESULTS

We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena's usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.

CONCLUSIONS

BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.

How to design an art-science program? Self-reported benefits for artists and scientists in the VI4 artist-in-residence program

While many new programs bridge the arts and sciences, a data-based examination of art-science program design can lead to more efficient programming. The Vanderbilt Institute for Infection, Immunology, and Inflammation Artist-in-Residence program is a virtual program that brings together undergraduate student "artists" and faculty-level "scientists" to generate science-art content. We have recruited over 80 artists and 50 scientists to collaborate in creating visual science communication content. Using self-reported data from both groups, we performed qualitative and quantitative analyses to define sources for negative and positive experiences for artists and scientists. We also identify areas for improvement and key features for in producing a positive experience. We found that artists participants had more positive responses about "learning something new" from the program than scientists. We also found that for both artists and scientists the length of the program and the virtual nature were identified as key features that could be improved. However, the most surprising aspect of our analysis suggests that for both "way of thinking" and "science communication to the public or general audience," were seen as significant beneficial gains for scientists compared to artists. We conclude this analysis with suggestions to enhance the benefits and outcomes of an art-science program and ways to minimize the difficulties, such as communication and collaboration, faced by participants and program designers.

Effects of Land Use/Land Cover Changes on Carbon Storage in North African Coastal Wetlands

Healthy wetlands are among the most effective sinks for carbon on the planet, and thus contribute to mitigate climate change. However, in North Africa, coastal wetlands are under high pressure especially from urban sprawl and tourism development, due to the rapid population growth and migration. This paper analyzed the effects of land use/land cover changes on carbon stocks, over 20 years, in six North African coastal wetlands, and estimated the economic value of the carbon sequestered during the considered period. The methodology used combined remote sensing and modeling. The results showed that among the six studied sites, only two (Moulouya and Moulay Bouselham) showed an increase in stored carbon and therefore are potential carbon sinks. In turn, the other four showed a more or less significant loss of carbon, which will likely be released into the atmosphere. The underlying processes that drive changes in carbon dynamics are mainly urban expansion and land use conversion, which often occurs at the expense of the natural habitats surrounding the wetlands. Understanding these processes can provide valuable decision-making information for land use planning, wetlands conservation and carbon reduction policies.

Evaluating the usability and acceptability of a geographical information system (GIS) prototype to visualise socio-economic and public health data

BACKGROUND

Understanding the impact of socio-economic inequality on health outcomes is arguably more relevant than ever before given the global repercussions of Covid-19. With limited resources, innovative methods to track disease, population needs, and current health and social service provision are essential. To best make use of currently available data, there is an increasing reliance on technology. One approach of interest is the implementation and integration of mapping software. This research aimed to determine the usability and acceptability of a methodology for mapping public health data using GIS technology.

METHODS

Prototype multi-layered interactive maps were created demonstrating relationships between socio-economic and health data (vaccination and admission rates). A semi-structured interview schedule was developed, including a validated tool known as the System Usability Scale (SUS), which assessed the usability of the mapping model with five stakeholder (SH) groups. Fifteen interviews were conducted across the 5 SH and analysed using content analysis. A Kruskal-Wallis H test was performed to determine any statistically significant difference for the SUS scores across SH. The acceptability of the model was not affected by the individual use of smart technology among SHs.

RESULTS

The mean score from the SUS for the prototype mapping models was 83.17 out of 100, indicating good usability. There was no statistically significant difference in the usability of the maps among SH (p = 0.094). Three major themes emerged with respective sub-themes from the interviews including: (1) Barriers to current use of data (2) Design strengths and improvements (3) Multiple benefits and usability of the mapping model.

CONCLUSION

Irrespective of variations in demographics or use of smart technology amongst interviewees, there was no significant difference in the usability of the model across the stakeholder groups. The average SUS score for a new system is 68. A score of 83.17 was calculated, indicative of a "good" system, as falling within the top 10% of scores. This study has provided a potential digital model for mapping public health data. Furthermore, it demonstrated the need for such a digital solution, as well as its usability and future utilisation avenues among SH.

Making time/breaking time: critical literacy and politics of time in data visualisation

Purpose

Representations of time are commonly used to construct narratives in visualisations of data. However, since time is a value-laden concept, and no representation can provide a full, objective account of “temporal reality”, they are also biased and political: reproducing and reinforcing certain views and values at the expense of alternative ones. This conceptual paper aims to explore expressions of temporal bias and politics in data visualisation, along with possibly mitigating user approaches and design strategies.

Design/methodology/approach

This study presents a theoretical framework rooted in a sociotechnical view of representations as biased and political, combined with perspectives from critical literacy, radical literacy and critical design. The framework provides a basis for discussion of various types and effects of temporal bias in visualisation. Empirical examples from previous research and public resources illustrate the arguments.

Findings

Four types of political effects of temporal bias in visualisations are presented, expressed as limitation of view, disregard of variation, oppression of social groups and misrepresentation of topic and suggest that appropriate critical and radical literacy approaches require users and designers to critique, contextualise, counter and cross beyond expressions of the same. Supporting critical design strategies involve the inclusion of multiple datasets and representations; broad access to flexible tools; and inclusive participation of marginalised groups.

Originality/value

The paper draws attention to a vital, yet little researched problem of temporal representation in visualisations of data. It offers a pioneering bridging of critical literacy, radical literacy and critical design and emphasises mutual rather than contradictory interests of the empirical sciences and humanities.

ESPRES: A web application for interactive analysis of multiple pressures in aquatic ecosystems

ESPRES (Efficient Strategies for anthropogenic Pressure Reduction in European waterSheds) is a web-based Decision Support System (DSS) designed to explore management options for achieving environmental targets in European freshwaters. The tool integrates multi-objective optimization (MOO) algorithms for selecting the best management options in a river basin and models assessing the consequent changes in the water quantity (water flow) and quality (nutrient concentration). The MOO engine identifies Pareto front strategies that are trade-offs between environmental objectives for water bodies and the effort required for reducing the pressures. The web interface provides tools to set the effort perceived by different river basin stakeholders considering technical feasibility, political difficulty, and social acceptability of the alternative options. The environmental impact of management options (scenarios) is assessed with models developed at the European scale. ESPRES enables comparison of management solutions and allows quantifying environmental and socio-economic trade-offs inherent to the decision making process.

Scenario processes for socio-environmental systems analysis of futures: A review of recent efforts and a salient research agenda for supporting decision making

This paper reviews the latest research on scenarios including the processes and products for socio-environmental systems (SES) analysis, modeling and decision making. A group of scenario researchers and practitioners participated in a workshop to discuss consolidation of existing research on the development and use of scenario analysis in exploring and understanding the interplay between human and environmental systems. This paper presents an extended overview of the workshop discussions and follow-up review work. It is structured around the essential challenges that are crucial to progress support of decision making and learning with respect to our highly uncertain socio-environmental futures. It identifies a practical research agenda where challenges are grouped according to the process stage at which they are most significant: before, during, and after the creation of the scenarios as products. These challenges for SES include: enhancing the role of stakeholder and public engagement in the co-development of scenarios, linking scenarios across multiple geographical, sectoral and temporal scales, improving the links between the qualitative and quantitative aspects of scenario analysis, addressing uncertainties especially surprise, addressing scenario diversity and their consistency together, communicating scenarios including visualization methods, and linking scenarios to decision making.

Habitat Models of Focal Species Can Link Ecology and Decision-Making in Sustainable Forest Management

A fundamental problem of sustainability is how to reduce the double complexity of ecological and social systems into simple operational terms. We highlight that the conservation concept of focal species (selected species sensitive to a set of anthropogenic threats to their habitat) links multiple issues of ecological sustainability, and their habitat models can provide a practical tool for solving these issues. A review of the literature shows that most spatial modeling of focal species focuses on vertebrates, lacks the aspect of aquatic and soil habitats, and has been slow in the uptake by actual management planning. We elaborate on a deductive modeling approach that first generalizes the main influential dimensions of habitat change (threats), which are then parameterized as habitat quality estimates for focal species. If built on theoretical understanding and properly scaled, the maps produced with such models can cost-effectively describe the dynamics of ecological qualities across forest landscapes, help set conservation priorities, and reflect on management plans and practices. The models also serve as ecological hypotheses on biodiversity and landscape function. We illustrate this approach based on recent additions to the forest reserve network in Estonia, which addressed the insufficient protection of productive forest types. For this purpose, mostly former production forests that may require restoration were set aside. We distinguished seven major habitat dimensions and their representative taxa in these forests and depicted each dimension as a practical stand-scale decision tree of habitat quality. The model outcomes implied that popular stand-structural targets of active forest restoration would recover passively in reasonable time in these areas, while a critically degraded condition (loss of old trees of characteristic species) required management beyond reserve borders. Another hidden issue revealed was that only a few stands of consistently low habitat quality concentrated in the landscape to allow cost-efficient restoration planning. We conclude that useful habitat models for sustainable forest management have to balance single-species realism with stakeholder expectations of meaningful targets and scales. Addressing such social aspects through the focal species concept could accelerate the adoption of biodiversity distribution modeling in forestry.

Fundamentals of graphic design—essential tools for effective visual science communication

Guidance on improving the visual aspects of science communication range from “recipe”-style instructions to hyper-focused aspects of data visualization. Currently lacking in the peer-reviewed literature is a primer in graphic design tailored to a high-level overview of basic design principles and associated jargon related to layout, imagery, typeface, and colour. We illustrate why these aspects are important to effective communication. Further, we provide considerations on when to solicit professional assistance and what to expect when working with graphic designers. Having the fundamental principles of good design in your toolbox facilitates the production of effective visual communication related to your research and fruitful scientist–designer collaborations.

Towards more effective online environmental information provision through tailored Natural Language Generation: Profiles of Scottish river user groups and an evaluative online experiment

As a result of societal transformations, political governance shifts, and advances in ICT, online information has become crucial in efforts by public authorities to make citizens better stewards of the environment. Yet, their environmental information provision may not always be attuned to end users' rationales, behaviours and appreciations. This study revolves around dynamic river level information provided by an environmental regulator - updated once a day or more, and collected by a sensor network of 333 gauging stations along 232 Scottish rivers. Employing an elaborate mixed methods approach with qualitative and quantitative elements, we examined if profiling of web page user groups and the subsequent employment of a specially designed Natural Language Generation (NLG) system could foster more effective online information provision. We identified profiles for the three main user groups: fishing, flood risk related, and paddling. The existence of well-distinguishable rationales and characteristics was in itself an argument for profiling; the same river level information was used in entirely different ways by the three groups. We subsequently constructed an advanced online experiment that implemented NLG based on live river level data. We found that textual information can be of much value in translating dynamic technical information into straightforward messages for the specific purposes of the user groups. We conclude that tailored NLG could be widely used in more effective online environmental information provision, and we provide five practical recommendations for public authorities and other information providers.

Estimating everyday risk: Subjective judgments are related to objective risk, mapping of numerical magnitudes and previous experience

We aimed to investigate individual differences that associate with peoples' acute risk perception for activities such as walking and giving birth, including objective risk and the mapping of numerical magnitudes. The Amazon Mechanical Turk platform was used, with 284 participants recruited (40% female) ranging between 19 and 68 years. Participants had to indicate the positions of (1) the relative death risk of activities on a horizontal-line with 'very low risk of death' and 'very high risk of death' as left and right anchors respectively and (2), numerical magnitudes on a horizontal-line ranging 0-1000. The MicroMort framework was used to index acute risk of death (one/million chance of dying from an accident). Previous experience with the activities, handedness, along with risk propensity and unrealistic optimism were also measured. Linear mixed-effects modelling was used to investigate predictors of subjective MicroMort judgments. Individuals subjectively judged activities to be riskier if the activity was objectively riskier, if they over-estimated on the numerical task (more so for low-risk activities as compared to high-risk), or if they had not experienced the activity previously. The observed relationship between the number line task and everyday risk judgments is in keeping with the idea of a common magnitude representation system. In conclusion, individuals are able to discriminate between activities varying in risk in an absolute sense, however intuition for judging the relative differences in risk is poor. The relationship between the misjudging of both risks and numerical magnitudes warrants further investigation, as may inform the development of risk communication strategies.

Temporal degradation of data limits biodiversity research

Spatial and/or temporal biases in biodiversity data can directly influence the utility, comparability, and reliability of ecological and evolutionary studies. While the effects of biased spatial coverage of biodiversity data are relatively well known, temporal variation in data quality (i.e., the congruence between recorded and actual information) has received much less attention. Here, we develop a conceptual framework for understanding the influence of time on biodiversity data quality based on three main processes: (1) the natural dynamics of ecological systems—such as species turnover or local extinction; (2) periodic taxonomic revisions, and; (3) the loss of physical and metadata due to inefficient curation, accidents, or funding shortfalls. Temporal decay in data quality driven by these three processes has fundamental consequences for the usage and comparability of data collected in different time periods. Data decay can be partly ameliorated by adopting standard protocols for generation, storage, and sharing data and metadata. However, some data degradation is unavoidable due to natural variations in ecological systems. Consequently, changes in biodiversity data quality over time need be carefully assessed and, if possible, taken into account when analyzing aging datasets.

Funnel plots and choropleth maps in cancer risk communication: a comparison of tools for disseminating population-based incidence data to stakeholders

BACKGROUND

Population-based cancer registries provide epidemiological cancer information, but the indicators are often too complex to be interpreted by local authorities and communities, due to numeracy and literacy limitations. The aim of this paper is to compare the commonly used visual formats to funnel plots to enable local public health authorities and communities to access valid and understandable cancer incidence data obtained at the municipal level.

METHODS

A funnel plot representation of standardised incidence ratio (SIR) was generated for the 82 municipalities of the Palermo Province with the 2003-2011 data from the Palermo Province Cancer Registry (Sicily, Italy). The properties of the funnel plot and choropleth map methodologies were compared within the context of disseminating epidemiological data to stakeholders.

RESULTS

The SIRs of all the municipalities remained within the control limits, except for Palermo city area (SIR=1.12), which was sited outside the upper control limit line of 99.8%. The Palermo Province SIRs funnel plot representation was congruent with the choropleth map generated from the same data, but the former resulted more informative as shown by the comparisons of the weaknesses and strengths of the 2 visual formats.

CONCLUSIONS

Funnel plot should be used as a complementary valuable tool to communicate epidemiological data of cancer registries to communities and local authorities, visually conveying an efficient and simple way to interpret cancer incidence data.

Familiarity Vs Trust: A Comparative Study of Domain Scientists' Trust in Visual Analytics and Conventional Analysis Methods

Combining interactive visualization with automated analytical methods like statistics and data mining facilitates data-driven discovery. These visual analytic methods are beginning to be instantiated within mixed-initiative systems, where humans and machines collaboratively influence evidence-gathering and decision-making. But an open research question is that, when domain experts analyze their data, can they completely trust the outputs and operations on the machine-side? Visualization potentially leads to a transparent analysis process, but do domain experts always trust what they see? To address these questions, we present results from the design and evaluation of a mixed-initiative, visual analytics system for biologists, focusing on analyzing the relationships between familiarity of an analysis medium and domain experts' trust. We propose a trust-augmented design of the visual analytics system, that explicitly takes into account domain-specific tasks, conventions, and preferences. For evaluating the system, we present the results of a controlled user study with 34 biologists where we compare the variation of the level of trust across conventional and visual analytic mediums and explore the influence of familiarity and task complexity on trust. We find that despite being unfamiliar with a visual analytic medium, scientists seem to have an average level of trust that is comparable with the same in conventional analysis medium. In fact, for complex sense-making tasks, we find that the visual analytic system is able to inspire greater trust than other mediums. We summarize the implications of our findings with directions for future research on trustworthiness of visual analytic systems.

Simulating social-ecological systems: the Island Digital Ecosystem Avatars (IDEA) consortium

Systems biology promises to revolutionize medicine, yet human wellbeing is also inherently linked to healthy societies and environments (sustainability). The IDEA Consortium is a systems ecology open science initiative to conduct the basic scientific research needed to build use-oriented simulations (avatars) of entire social-ecological systems. Islands are the most scientifically tractable places for these studies and we begin with one of the best known: Moorea, French Polynesia. The Moorea IDEA will be a sustainability simulator modeling links and feedbacks between climate, environment, biodiversity, and human activities across a coupled marine–terrestrial landscape. As a model system, the resulting knowledge and tools will improve our ability to predict human and natural change on Moorea and elsewhere at scales relevant to management/conservation actions.

Explaining Spatial Variation in the Recording Effort of Citizen Science Data across Multiple Taxa

The collation of citizen science data in open-access biodiversity databases makes temporally and spatially extensive species’ observation data available to a wide range of users. Such data are an invaluable resource but contain inherent limitations, such as sampling bias in favour of recorder distribution, lack of survey effort assessment, and lack of coverage of the distribution of all organisms. Any technical assessment, monitoring program or scientific research applying citizen science data should therefore include an evaluation of the uncertainty of its results. We use ‘ignorance’ scores, i.e. spatially explicit indices of sampling bias across a study region, to further understand spatial patterns of observation behaviour for 13 reference taxonomic groups. The data is based on voluntary observations made in Sweden between 2000 and 2014. We compared the effect of six geographical variables (elevation, steepness, population density, log population density, road density and footpath density) on the ignorance scores of each group. We found substantial variation among taxonomic groups in the relative importance of different geographic variables for explaining ignorance scores. In general, road access and logged population density were consistently important variables explaining bias in sampling effort, indicating that access at a landscape-scale facilitates voluntary reporting by citizen scientists. Also, small increases in population density can produce a substantial reduction in ignorance score. However the between-taxa variation in the importance of geographic variables for explaining ignorance scores demonstrated that different taxa suffer from different spatial biases. We suggest that conservationists and researchers should use ignorance scores to acknowledge uncertainty in their analyses and conclusions, because they may simultaneously include many correlated variables that are difficult to disentangle.

Networking Our Way to Better Ecosystem Service Provision

The ecosystem services (EcoS) concept is being used increasingly to attach values to natural systems and the multiple benefits they provide to human societies. Ecosystem processes or functions only become EcoS if they are shown to have social and/or economic value. This should assure an explicit connection between the natural and social sciences, but EcoS approaches have been criticized for retaining little natural science. Preserving the natural, ecological science context within EcoS research is challenging because the multiple disciplines involved have very different traditions and vocabularies (common-language challenge) and span many organizational levels and temporal and spatial scales (scale challenge) that define the relevant interacting entities (interaction challenge). We propose a network-based approach to transcend these discipline challenges and place the natural science context at the heart of EcoS research.

Tailoring the visual communication of climate projections for local adaptation practitioners in Germany and the UK

Visualizations are widely used in the communication of climate projections. However, their effectiveness has rarely been assessed among their target audience. Given recent calls to increase the usability of climate information through the tailoring of climate projections, it is imperative to assess the effectiveness of different visualizations. This paper explores the complexities of tailoring through an online survey conducted with 162 local adaptation practitioners in Germany and the UK. The survey examined respondents' assessed and perceived comprehension (PC) of visual representations of climate projections as well as preferences for using different visualizations in communicating and planning for a changing climate. Comprehension and use are tested using four different graph formats, which are split into two pairs. Within each pair the information content is the same but is visualized differently. We show that even within a fairly homogeneous user group, such as local adaptation practitioners, there are clear differences in respondents' comprehension of and preference for visualizations. We do not find a consistent association between assessed comprehension and PC or use within the two pairs of visualizations that we analysed. There is, however, a clear link between PC and use of graph format. This suggests that respondents use what they think they understand the best, rather than what they actually understand the best. These findings highlight that audience-specific targeted communication may be more complex and challenging than previously recognized.

Multidimensional physical activity: an opportunity, not a problem

Our research shows that no single metric will reflect an individual's physical activity adequately because multiple biologically important dimensions are independent and unrelated. We propose that there is an opportunity to exploit this multidimensional characteristic of physical activity to improve personalized feedback and offer physical activity options and choices that are tailored to an individual's needs and preferences.