Journal articles on the topic 'Data Visualisation'
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1
Garrote, Antonio, and María N. Moreno García. "LinkedVis an Information Visualisation Toolkit for RDF Data." International Journal on Semantic Web and Information Systems 9, no. 4 (October 2013): 1–16. http://dx.doi.org/10.4018/ijswis.2013100101.
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LinkedVis implements a JavaScript and SVG data visualisation toolkit that can be used to generate a wide range of interactive information visualisations from RDF graphs using a grammar of graphics style syntax extended with operations for structural transformation of the RDF data graph. Additionally, LinkedVis visualisations make it possible to embed meta-data about the visualisation and the way different graphic components from the visualisation are related to the original RDF data. Insertion of meta-data transforms the visualisation into a self-describing piece of information that can be processed by an automatic agent to perform different tasks, like extracting data associated to a visual component, following the associated linked URIs or translate the visualisation to an entirely different underlying graphics system other than SVG.
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Meier, Sebastian, and Katrin Glinka. "The Individual in the Data — the Aspect of Personal Relevance in Designing Casual Data Visualisations." i-com 16, no. 3 (December 20, 2017): 247–65. http://dx.doi.org/10.1515/icom-2017-0025.
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AbstractOver the last two decades, data visualisation has diffused into the broader realm of mass communication. Before this shift, tools and displays of data-driven geographic- and information visualisation were mostly used in expert contexts. By now, they are also used in casual contexts, for example on newspaper websites, government data portals and many other public outlets. This diversification of the audience poses new challenges within the visualisation community. In this paper we propose personal relevance as one factor to be taken into account when designing casual data visualisations, which are meant for the communication with non-experts. We develop a conceptual model and present a related set of design techniques for interactive web-based visualisations that are aimed at activating personal relevance. We discuss our proposed techniques by applying them to a use case on the visualisation of air pollution in London (UK).
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Nash, Kathryn, Verity Trott, and William Allen. "The politics of data visualisation and policy making." Convergence: The International Journal of Research into New Media Technologies 28, no. 1 (February 2022): 3–12. http://dx.doi.org/10.1177/13548565221079156.
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Data visualisation has become ubiquitous in everyday life, from seeing images in news media to tracking individual health indicators. While the effects of data visualisation on society and people have been explored within a range of literature, there has been far less attention paid to the interconnectedness of data visualisation and policy making. In this special issue, we explore how data visualisation matters for policy priorities, processes and outcomes; how it reflects the demands and constraints posed by specific policy problems; and finally, what data visualisations reveal about broader political, social, and cultural shifts and the implications for policy.
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Allen, William L. "Visual brokerage: Communicating data and research through visualisation." Public Understanding of Science 27, no. 8 (February 5, 2018): 906–22. http://dx.doi.org/10.1177/0963662518756853.
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Researchers increasingly use visualisation to make sense of their data and communicate findings more widely. But these are not necessarily straightforward processes. Theories of knowledge brokerage show how sociopolitical contexts and intermediary organisations that translate research for public audiences shape how users engage with evidence. Applying these ideas to data visualisation, I argue that several kinds of brokers (such as data collectors, designers and intermediaries) link researchers and audiences, contributing to the ways that people engage with visualisations. To do this, I draw on qualitative focus groups that elicited non-academic viewers’ reactions to visualisations of data about UK migration. The results reveal two important features of engagement: perceptions of brokers’ credibility and feelings of surprise arising from visualisations’ content and design. I conclude by arguing that researchers, knowledge brokers and the public produce – as well as operate within – a complex visualisation space characterised by mutual, bi-directional connections.
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Hill, Rosemary Lucy. "The political potential of numbers: data visualisation in the abortion debate." Kvinder, Køn & Forskning, no. 1 (September 5, 2017): 83–96. http://dx.doi.org/10.7146/kkf.v26i1.109789.
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Data visualisation has been argued to have the power to ‘change the world’, implicitly for the better, but when it comes to abortion, both sides make moral claims to ‘good’. Visualisation conventions of clean lines and shapes simplify data, lending them a rhetoric of neutrality, as if the data is the whole story. It is imperative, therefore, to examine how data visualisations are used to shape women’s lives. This article draws on the findings of the Persuasive Data project . Google Image Scraper was used to locate abortion-related visualisations circulating online. The images, their web locations, and data use were social semiotically analysed to understand their visual rhetoric and political use. Anti-abortion groups are more likely to use data visualisation than pro-choice groups, thereby simplifying the issue and mobilising the rhetoric of neutrality. I argue that data visualisations are being used as a hindrance to women’s access to abortion, and that the critique of such visualisations needs to come from feminists. This article extends discussions of how data is often reified as objective, by showing how the rhetoric of objectivity within data visualisation conventions is harnessed to do work in the world that is potentially very damaging to women’s rights.
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Donohoe, David, and Eamon Costello. "Data Visualisation Literacy in Higher Education: An Exploratory Study of Understanding of a Learning Dashboard Tool." International Journal of Emerging Technologies in Learning (iJET) 15, no. 17 (September 11, 2020): 115. http://dx.doi.org/10.3991/ijet.v15i17.15041.
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The visualisation of data has become ubiquitous. Visualisations are used to represent data in a way that is easy to understand and useful in our lives. Each data visualisation needs to be suitable to extract the correct information to complete a task and make an informed decision while minimising the impact of biases. To achieve this, the ability to create and read visualisations has become as important as the ability to read and write. Therefore, the Information Visualisation community is applying more attention to literacy and decision making in data vis-ualisations. Until recently, researchers lacked valid and reliable test in-struments to measure the literacy of users or the taxonomy to detect biased judgement in data visualisations. A literature review showed there is relatively little research on data visualisations for different user data literacy levels in authentic settings and a lack of studies that pro-vide evidence for the presence of cognitive biases in data visualisa-tions. This exploratory research study was undertaken to develop a method to assess perceived usefulness and confidence in reporting dashboards within higher education by adapting existing research in-struments. A survey was designed to test perceived usefulness, per-ceived skill and 24 multiple-choice test items covering six data visuali-sations based on eight tasks. The study was sent to 157 potential par-ticipants, with a response rate of 20.38%. The results showed data vis-ualisations are useful, but the purpose of some data visualisations is not always understood. Also, we showed there is a consensus that re-spondents perceive their data visualisation literacy is higher than they believe their peers to be. However, the higher their overconfidence, the lower their actual data visualisation literacy score. Finally, we discuss the benefits, limitations and possible future research areas.
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Sibolla, B. H., T. Van Zyl, and S. Coetzee. "TOWARDS THE DEVELOPMENT OF A TAXONOMY FOR VISUALISATION OF STREAMED GEOSPATIAL DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-2 (June 2, 2016): 129–36. http://dx.doi.org/10.5194/isprsannals-iii-2-129-2016.
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Geospatial data has very specific characteristics that need to be carefully captured in its visualisation, in order for the user and the viewer to gain knowledge from it. The science of visualisation has gained much traction over the last decade as a response to various visualisation challenges. During the development of an open source based, dynamic two-dimensional visualisation library, that caters for geospatial streaming data, it was found necessary to conduct a review of existing geospatial visualisation taxonomies. The review was done in order to inform the design phase of the library development, such that either an existing taxonomy can be adopted or extended to fit the needs at hand. The major challenge in this case is to develop dynamic two dimensional visualisations that enable human interaction in order to assist the user to understand the data streams that are continuously being updated. This paper reviews the existing geospatial data visualisation taxonomies that have been developed over the years. Based on the review, an adopted taxonomy for visualisation of geospatial streaming data is presented. Example applications of this taxonomy are also provided. The adopted taxonomy will then be used to develop the information model for the visualisation library in a further study.
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Sibolla, B. H., T. Van Zyl, and S. Coetzee. "TOWARDS THE DEVELOPMENT OF A TAXONOMY FOR VISUALISATION OF STREAMED GEOSPATIAL DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-2 (June 2, 2016): 129–36. http://dx.doi.org/10.5194/isprs-annals-iii-2-129-2016.
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Geospatial data has very specific characteristics that need to be carefully captured in its visualisation, in order for the user and the viewer to gain knowledge from it. The science of visualisation has gained much traction over the last decade as a response to various visualisation challenges. During the development of an open source based, dynamic two-dimensional visualisation library, that caters for geospatial streaming data, it was found necessary to conduct a review of existing geospatial visualisation taxonomies. The review was done in order to inform the design phase of the library development, such that either an existing taxonomy can be adopted or extended to fit the needs at hand. The major challenge in this case is to develop dynamic two dimensional visualisations that enable human interaction in order to assist the user to understand the data streams that are continuously being updated. This paper reviews the existing geospatial data visualisation taxonomies that have been developed over the years. Based on the review, an adopted taxonomy for visualisation of geospatial streaming data is presented. Example applications of this taxonomy are also provided. The adopted taxonomy will then be used to develop the information model for the visualisation library in a further study.
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Fileborn, Bianca, and Verity Trott. "“It ain’t a compliment”: Feminist data visualisation and digital street harassment advocacy." Convergence: The International Journal of Research into New Media Technologies 28, no. 1 (September 29, 2021): 127–49. http://dx.doi.org/10.1177/13548565211045536.
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In an era of datafication, data visualisation is playing an increasing role in civic meaning-making processes. However, the conventions of data visualisation have been criticised for their reductiveness and rhetoric of neutrality and there have been recent efforts to develop feminist principles for designing data visualisations that are compatible with feminist epistemologies. In this article, we aim to examine how data visualisation is used in feminist activism and by feminist activists. Drawing on the example of digital street harassment activism, we analyse how street harassment is visualised in and through a selection of prominent activist social media accounts. We consider the platform affordances utilised by activists, and how these are harnessed in making street harassment ‘knowable'. Moreover, we critically interrogate which and whose experiences are ‘knowable’ via digital techniques, and what remains obscured and silenced. In analysing digital feminist activists’ practices, we argue that what constitutes ‘data visualisation’ itself must be situated within feminist epistemologies and praxis that centre lived experience as the starting point for knowledge production. Such an approach challenges and disrupts normative constructions of what constitutes data visualisation. Our findings demonstrate how feminist activists are adopting ‘traditional’ practices of speaking out and consciousness-raising to the digital sphere in the creation of a range of visualisations that represent the issue of street harassment. We consider the efficacy of these visualisations for achieving their intended purpose and how they might translate to policy and government responses, if this is indeed their goal. Further, we document a tension between feminist epistemologies and the prevailing logic of datafication or dataism and note how in an attempt to unite the two, some digital feminist activism has contributed to reproducing existing power structures, raising concerning implications at the policy level.
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Cuthbert, Carol E., and Noel J. Pearse. "Strategic Data Pattern Visualisation." Journal of Systemics, Cybernetics and Informatics 20, no. 1 (January 2022): 122–41. http://dx.doi.org/10.54808/jsci.20.01.122.
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Data visualisation reveals patterns and provides insights that lead to actions from management, thereby playing a mediating role in the relationship between the internal resources of a firm and its financial performance. In this chapter, contingent resource-based theory is applied to the analysis of big data, treating its visualisation as a mode of interdisciplinary communication. In service industries in general and the legal industry in particular, big data analytics (BDA) is emerging as a decision-making tool for management to achieve competitive advantage. Traditionally, data scientists have delved into data armed with a hypothesis, but increasingly they explore data to discern patterns that lead to hypotheses that are then tested. These big data analytics tools in the hands of data scientists have the potential to unlock firm value and increase revenue and profits, through pattern identification, analysis, and strategic action. This exploratory mode of working can increase complexity and thereby diminish efficient management decision-making and action. However, data pattern visualisation reduces complexity, as it enables interdisciplinary communication between data scientists and managers through the translation of statistical patterns into visualisations that enable actionable management decisions. When data scientists visualise data patterns for managers, this translates uncertainty into reliable conclusions, resulting in effective management decision-making and action. Informed by contingent resource theory and viewing these primary and secondary resources as independent variables and performance outcomes such as revenue and profitability as dependent variables, a conceptual framework is developed. The contingent resource-based theory highlights capabilities emerging from the interrelationship between primary and secondary resources as being central to competitiveness and profitability. Data decision-making systems are viewed as a primary resource, while complementary resources are (1) their completeness of vision (i.e., strategy and innovation) and (2) their ability to execute (i.e., operational capabilities). Data visualisation is therefore crucial as a resource facilitating actionable decisions by management, which in turn enhances firm performance. The balance between expert agents' self-reliance and central control, the entity's values, task attributes, and risk appetite all moderate the type of data visualisation produced by data scientists.
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Kavaz, Ecem, Anna Puig, and Inmaculada Rodríguez. "Chatbot-Based Natural Language Interfaces for Data Visualisation: A Scoping Review." Applied Sciences 13, no. 12 (June 11, 2023): 7025. http://dx.doi.org/10.3390/app13127025.
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Rapid growth in the generation of data from various sources has made data visualisation a valuable tool for analysing data. However, visual analysis can be a challenging task, not only due to intricate dashboards but also when dealing with complex and multidimensional data. In this context, advances in Natural Language Processing technologies have led to the development of Visualisation-oriented Natural Language Interfaces (V-NLIs). In this paper, we carry out a scoping review that analyses synergies between the fields of Data Visualisation and Natural Language Interaction. Specifically, we focus on chatbot-based V-NLI approaches and explore and discuss three research questions. The first two research questions focus on studying how chatbot-based V-NLIs contribute to interactions with the Data and Visual Spaces of the visualisation pipeline, while the third seeks to know how chatbot-based V-NLIs enhance users’ interaction with visualisations. Our findings show that the works in the literature put a strong focus on exploring tabular data with basic visualisations, with visual mapping primarily reliant on fixed layouts. Moreover, V-NLIs provide users with restricted guidance strategies, and few of them support high-level and follow-up queries. We identify challenges and possible research opportunities for the V-NLI community such as supporting high-level queries with complex data, integrating V-NLIs with more advanced systems such as Augmented Reality (AR) or Virtual Reality (VR), particularly for advanced visualisations, expanding guidance strategies beyond current limitations, adopting intelligent visual mapping techniques, and incorporating more sophisticated interaction methods.
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Hadley, Martin John, and Howard Noble. "Promoting Interactive Visualisation at University of Oxford: The Live Data Network." International Journal of Digital Curation 11, no. 1 (October 28, 2016): 172. http://dx.doi.org/10.2218/ijdc.v11i1.418.
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This article introduces the Live Data project funded by the Research IT Board of the University of Oxford’s IT Services department. The primary aim of the project is to support academics in creating interactive visualisations using a variety of cloud-based visualisation services, which the academic can freely embed within academic journals, blogs and personal websites through the use of iframes. To achieve this the project has been funded from October 2015 to March 2017 to recruit visualisation case studies from across the University and to develop software agnostic workflows for the creation of interactive visualisations. Within this report we present interactive visualisations as a vital component of the academic’s toolkit for engaging potential collaborators and the general public with their research data – thereby bridging the so-called ‘data gap’ between data, publication and researcher.Â
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Engebretsen, Martin. "From Decoding a Graph to Processing a Multimodal Message." Nordicom Review 41, no. 1 (February 18, 2020): 33–50. http://dx.doi.org/10.2478/nor-2020-0004.
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AbstractData visualisation – in the forms of graphs, charts, and maps – represents a text type growing in prevalence and impact in many cultural domains; education, journalism, business, PR, and more. Research on data visualisation reception is scarce, particularly that related to interactive and dynamic forms of data visualisation in digital media. Taking an approach inspired by grounded theory, in this article I investigate the ways in which young students interact with data visualisations found in digital news media. Combining observations from reading sessions with ten in-depth interviews, I investigate how the informants read, interpreted, and responded emotionally to data visualisations including visual metaphors, interactivity, and animation.
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Pereira, Arnaldo, João Rafael Almeida, Rui Pedro Lopes, and José Luís Oliveira. "Semantic Data Visualisation for Biomedical Database Catalogues." Healthcare 10, no. 11 (November 15, 2022): 2287. http://dx.doi.org/10.3390/healthcare10112287.
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Biomedical databases often have restricted access policies and governance rules. Thus, an adequate description of their content is essential for researchers who wish to use them for medical research. A strategy for publishing information without disclosing patient-level data is through database fingerprinting and aggregate characterisations. However, this information is still presented in a format that makes it challenging to search, analyse, and decide on the best databases for a domain of study. Several strategies allow one to visualise and compare the characteristics of multiple biomedical databases. Our study focused on a European platform for sharing and disseminating biomedical data. We use semantic data visualisation techniques to assist in comparing descriptive metadata from several databases. The great advantage lies in streamlining the database selection process, ensuring that sensitive details are not shared. To address this goal, we have considered two levels of data visualisation, one characterising a single database and the other involving multiple databases in network-level visualisations. This study revealed the impact of the proposed visualisations and some open challenges in representing semantically annotated biomedical datasets. Identifying future directions in this scope was one of the outcomes of this work.
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Idrissov, Agzam, Simon Rapp, Albert Albers, and Anja M. Maier. "DEVELOPING SYSTEMS VISUALISATIONS IN DESIGN THROUGH A TYPOLOGY OF VISUAL TASKS: A MECHATRONIC CASE." Proceedings of the Design Society 1 (July 27, 2021): 1213–22. http://dx.doi.org/10.1017/pds.2021.121.
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AbstractVisual representations are essential to design. Data-rich representations such as systems visualisations are gaining prominence in engineering practice. However, as such visualisations are often developed ad-hoc, we propose more systematically to link visual tasks with design-specific tasks for which the visualisations are used. Whereas research on such linking focuses mostly on CAD models and sketches, no such studies are yet available for systems visualisations. Thus, this paper introduces a typology of visual tasks from the Information Visualisation field to aid the development of systems visualisations in design. To build a visualisation using the typology, a case study with engineering students developing an autonomous robot was conducted. Through interviews and analysis of product representations used, design-specific tasks were identified and decomposed into visual tasks. Then, a visualisation that assisted the team in performing their design activities was created. Results illustrate the benefits of using such a typology to describe visual tasks and generate systems visualisations. The study suggests implications for researchers studying visual representations in design as well as for developers of systems visualisations.
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Allen, William. "Making corpus data visible: visualising text with research intermediaries." Corpora 12, no. 3 (November 2017): 459–82. http://dx.doi.org/10.3366/cor.2017.0128.
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Researchers using corpora can visualise their data and analyses using a growing number of tools. Visualisations are especially valuable in environments where researchers communicate and work with public-facing partners under the auspices of ‘knowledge exchange’ or ‘impact’, and corpus data are more available thanks to digital methods. However, although the field of corpus linguistics continues to generate its own range of techniques, it largely remains orientated towards finding ways for academics to communicate results directly with other academics rather than with or through groups outside universities. Also, there is a lack of discussion about how communication, motivations and values also feature in the process of making corpus data visible. My argument is that these sociocultural and practical factors also influence visualisation outputs alongside technical aspects. I draw upon two corpus-based projects about press portrayal of migrants, conducted by an intermediary organisation that links university researchers with users outside academia. Analysing these projects' visualisation outputs in their organisational and communication contexts produces key lessons for researchers wanting to visualise text; consider the aims and values of partners; develop communication strategies that acknowledge different areas of expertise; and link visualisation choices with wider project objectives.
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Wilhelm, Adalbert, and Susan VanderPlas. "Visual Narratives of the Covid-19 pandemic." Journal of Data Science, Statistics, and Visualisation 2, no. 7 (November 28, 2022): 84–113. http://dx.doi.org/10.52933/jdssv.v2i7.64.
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Covid-19 has sparked a worldwide interest in understanding the dynamic evo- lution of a pandemic and tracking the effectiveness of preventive measures and rules. For this reason, numerous media and research groups have produced com- prehensive data visualisations to illustrate the relevant trends and figures. In this paper, we will look at a selection of Covid 19 data visualisations to evaluate and discuss the currently established visualisation tools in terms of their ability to provide a communication channel both within the data science team and between data analysts, domain experts and a general interested audience. Although there is no set catalogue of evaluation criteria for data visualisations, we will try to give an overview of the different core aspects of visualisation evaluation and their competing principles.
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Oosterloo, Tom. "Visualisation of Radio Data." Publications of the Astronomical Society of Australia 12, no. 2 (August 1995): 215–18. http://dx.doi.org/10.1017/s1323358000020294.
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AbstractRadio astronomy software has not quite kept up with recent developments for the display of, and interaction with, data. At the Australia Telescope National Facility we are trying to catch up by investigating how useful visualisation techniques and approaches like visual computing are for the reduction of radio data. I will discuss a few techniques that we have applied to radio data and comment briefly on their merits.
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Bohak, Ciril, Matej Slemenik, Jaka Kordež, and Matija Marolt. "Aerial LiDAR Data Augmentation for Direct Point-Cloud Visualisation." Sensors 20, no. 7 (April 8, 2020): 2089. http://dx.doi.org/10.3390/s20072089.
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Direct point-cloud visualisation is a common approach for visualising large datasets of aerial terrain LiDAR scans. However, because of the limitations of the acquisition technique, such visualisations often lack the desired visual appeal and quality, mostly because certain types of objects are incomplete or entirely missing (e.g., missing water surfaces, missing building walls and missing parts of the terrain). To improve the quality of direct LiDAR point-cloud rendering, we present a point-cloud processing pipeline that uses data fusion to augment the data with additional points on water surfaces, building walls and terrain through the use of vector maps of water surfaces and building outlines. In the last step of the pipeline, we also add colour information, and calculate point normals for illumination of individual points to make the final visualisation more visually appealing. We evaluate our approach on several parts of the Slovenian LiDAR dataset.
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Graham, Martin, and Jessie Kennedy. "A Survey of Multiple Tree Visualisation." Information Visualization 9, no. 4 (November 5, 2009): 235–52. http://dx.doi.org/10.1057/ivs.2009.29.
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This article summarises the current state of research into multiple tree visualisations. It discusses the spectrum of current representation techniques used on single trees, pairs of trees and finally multiple trees, in order to identify which representations are best suited to particular tasks and to find gaps in the representation space, in which opportunities for future multiple tree visualisation research may exist. The application areas from where multiple tree data are derived are enumerated, and the distinct structures that multiple trees make in combination with each other and the effect on subsequent approaches to their visualisation are discussed, along with the basic high-level goals of existing multiple tree visualisations.
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Kubrak, Kateryna, Fredrik Milani, and Alexander Nolte. "A visual approach to support process analysts in working with process improvement opportunities." Business Process Management Journal 29, no. 8 (April 3, 2023): 101–32. http://dx.doi.org/10.1108/bpmj-10-2021-0631.
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PurposeWhen improving business processes, process analysts can use data-driven methods, such as process mining, to identify improvement opportunities. However, despite being supported by data, process analysts decide which changes to implement. Analysts often use process visualisations to assess and determine which changes to pursue. This paper helps explore how process mining visualisations can aid process analysts in their work to identify, prioritise and communicate business process improvement opportunities.Design/methodology/approachThe study follows the design science methodology to create and evaluate an artefact for visualising identified improvement opportunities (IRVIN).FindingsA set of principles to facilitate the visualisation of process mining outputs for analysts to work with improvement opportunities was suggested. Particularly, insights into identifying, prioritising and communicating process improvement opportunities from visual representation are outlined.Originality/valuePrior work focuses on visualisation from the perspectives – among others – of process exploration, process comparison and performance analysis. This study, however, considers process mining visualisation that aids in analysing process improvement opportunities.
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Heinrich, Falk. "(Big) Data, Diagram Aesthetics and the Question concerning Beauty." MedieKultur: Journal of media and communication research 31, no. 59 (March 8, 2016): 20. http://dx.doi.org/10.7146/mediekultur.v31i59.20084.
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<p class="falk1">The article investigates whether and in which way artistic artefacts deploying big data can be experienced as beautiful. The question is relevant, because the sentiment of beauty indicates besides an immediate sensory valuation also changes in cultural values and epistemic frameworks. The article focuses on artistic data visualisations. It applies concepts of philosophical aesthetics in order to trace an altered notion of beauty and its artistic and cultural implications.</p><p class="falk1">The article’s introductory part presents some examples of data visualisations and introduces relevant notions of beauty and big data. The main part discusses the changes in our concept of beauty by analysing data visualisation in the light of conceptual art and its aesthetics of the sublime. Data visualizations present potentially unfathomable and complex information that is associated with the sublime, but represent data in a way that allows for understanding by means of imaginations, which are aspects of beauty. The article elaborates on the simultaneity of and oscillation between aesthetic beauty and the aesthetic sublime, by introducing Deleuze’s understandings of the concept of the diagram that is able to mediate between visualisation as representation and diagrams as performative machine of formation and displacement of data relations.</p>
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Bayliss, Richard. "ARCHAEOLOGICAL SURVEY AND VISUALISATION: THE VIEW FROM BYZANTIUM." Late Antique Archaeology 1, no. 1 (2003): 26–313. http://dx.doi.org/10.1163/22134522-90000012.
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This paper will explore the relationship between the methodologies used in archaeology for recording buildings and landscapes and the development of computer visualisation technology, with specific reference to late antique and Byzantine archaeology. The principal aim is to highlight the applicability of visualisation technologies as the critical solutions to the presentation and investigation of survey data and reciprocally to demonstrate that meaningful computer visualisations benefit from a secure underpinning of archaeological survey data. My intention is to show that computer visualisation should not be seen solely as a vehicle for archaeological reconstruction but rather can be viewed as an integral part of the process of interpretation. The first of two case studies is the Anastasian Wall Project, a survey of a massive linear fortification in Turkish Thrace, which presented a series of practical problems both in terms of data capture and representation. The applicability of computer-based techniques for the integration and visualisation of various forms of survey data will be further investigated through the study of the Alacami, a multi-period Byzantine church in Cilicia, before some final comment is made on the current and potential roles of computer visualisation in Byzantine archaeology.
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Schmidt, Breon, Marek Cmero, Paul Ekert, Nadia Davidson, and Alicia Oshlack. "Slinker: Visualising novel splicing events in RNA-Seq data." F1000Research 10 (December 7, 2021): 1255. http://dx.doi.org/10.12688/f1000research.74836.1.
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Visualisation of the transcriptome relative to a reference genome is fraught with sparsity. This is due to RNA sequencing (RNA-Seq) reads being predominantly mapped to exons that account for just under 3% of the human genome. Recently, we have used exon-only references, superTranscripts, to improve visualisation of aligned RNA-Seq data through the omission of supposedly unexpressed regions such as introns. However, variation within these regions can lead to novel splicing events that may drive a pathogenic phenotype. In these cases, the loss of information in only retaining annotated exons presents significant drawbacks. Here we present Slinker, a bioinformatics pipeline written in Python and Bpipe that uses a data-driven approach to assemble sample-specific superTranscripts. At its core, Slinker uses Stringtie2 to assemble transcripts with any sequence across any gene. This assembly is merged with reference transcripts, converted to a superTranscript, of which rich visualisations are made through Plotly with associated annotation and coverage information. Slinker was validated on five novel splicing events of rare disease samples from a cohort of primary muscular disorders. In addition, Slinker was shown to be effective in visualising deletion events within transcriptomes of tumour samples in the important leukemia gene, IKZF1. Slinker offers a succinct visualisation of RNA-Seq alignments across typically sparse regions and is freely available on Github.
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Guo, S., C. Jing, H. Zhang, X. Lv, and W. Li. "SMART CAMPUS ELECTRICITY DATA VISUAL ANALYSIS SYSTEM." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2022 (June 2, 2022): 447–53. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2022-447-2022.
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Abstract. Smart grid is the basic support of smart city development. The application of visual analytics to electricity system helps monitor and analyse the characteristic information in electricity data, which provides a strong guarantee for mastering the operation status of electricity system and achieving effective energy planning. However, as the complexity and size of electricity data continues to grow, it increases the burden on electricity workers to understand and analyse the electricity consumption situation. In response to these problems, a new type of electricity data visualisation and analysis system has been proposed, which enables interactive analysis of large amounts of electricity data. The system has the following advantages. First, A novel visualisation graphic has been designed and implemented to enable electricity workers to visualise a comprehensive picture of electricity consumption at different granularities. Second, designing appropriate visualisations to highlight the characteristics of the data itself, depending on the specific needs and type of data. Finally, the system provides a set of coupled visual views and interactions to support system users to freely explore the campus electricity situation from multiple scales.
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Joseph, Pauline, Aaron Justin Kent, Peter Damian Green, Matthew Robinson, and Amanda Bellenger. "Analysis of EZproxy server logs to visualise research activity in Curtin’s online library." Library Hi Tech 37, no. 4 (November 18, 2019): 845–65. http://dx.doi.org/10.1108/lht-04-2018-0050.
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Purpose The purpose of this paper is to develop data visualisation proof of concept prototypes that will enable the Curtin University Library team to explore its users’ information-seeking behaviour and collection use online by analysing the library’s EZproxy logs. Design/methodology/approach Curtin Library’s EZproxy log file data from 2013 to 2017 is used to develop the data visualisation prototypes using Unity3D software. Findings Two visualisation prototypes from the EZproxy data set are developed. The first, “Global Visualisation of Curtin Research Activity”, uses a geographical map of the world as a platform to show where each research request comes from, the time each is made and the file size of the request. The second prototype, “Database Usage Visualisation”, shows the use of the library’s various subscription databases by staff and students daily, over a month in April 2017. Research limitations/implications The paper has following limitations: working to a tight timeline of ten weeks; time taken to cleanse noise data; and requirements for storing and hosting the voluminous data sets. Practical implications The prototypes provide visual evidence of the use of Curtin Library’s digital resources at any time and from anywhere by its users, demonstrating the demand for the library’s online service offerings. These prototype evidence-based data visualisations empower the library to communicate in a compelling and interesting way how its services and subscriptions support Curtin University’s missions. Originality/value The paper provides innovative approaches to create immersive 3D data visualisation prototypes to make sense of complex EZproxy data sets.
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Roberts, Jonathan C., Peter W. S. Butcher, and Panagiotis D. Ritsos. "One View Is Not Enough: Review of and Encouragement for Multiple and Alternative Representations in 3D and Immersive Visualisation." Computers 11, no. 2 (February 3, 2022): 20. http://dx.doi.org/10.3390/computers11020020.
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The opportunities for 3D visualisations are huge. People can be immersed inside their data, interface with it in natural ways, and see it in ways that are not possible on a traditional desktop screen. Indeed, 3D visualisations, especially those that are immersed inside head-mounted displays are becoming popular. Much of this growth is driven by the availability, popularity and falling cost of head-mounted displays and other immersive technologies. However, there are also challenges. For example, data visualisation objects can be obscured, important facets missed (perhaps behind the viewer), and the interfaces may be unfamiliar. Some of these challenges are not unique to 3D immersive technologies. Indeed, developers of traditional 2D exploratory visualisation tools would use alternative views, across a multiple coordinated view (MCV) system. Coordinated view interfaces help users explore the richness of the data. For instance, an alphabetical list of people in one view shows everyone in the database, while a map view depicts where they live. Each view provides a different task or purpose. While it is possible to translate some desktop interface techniques into the 3D immersive world, it is not always clear what equivalences would be. In this paper, using several case studies, we discuss the challenges and opportunities for using multiple views in immersive visualisation. Our aim is to provide a set of concepts that will enable developers to perform critical thinking, creative thinking and push the boundaries of what is possible with 3D and immersive visualisation. In summary developers should consider how to integrate many views, techniques and presentation styles, and one view is not enough when using 3D and immersive visualisations.
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Wang, Yao, Yue Jiang, Zhiming Hu, Constantin Ruhdorfer, Mihai Bâce, and Andreas Bulling. "VisRecall++: Analysing and Predicting Visualisation Recallability from Gaze Behaviour." Proceedings of the ACM on Human-Computer Interaction 8, ETRA (May 20, 2024): 1–18. http://dx.doi.org/10.1145/3655613.
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Question answering has recently been proposed as a promising means to assess the recallability of information visualisations. However, prior works are yet to study the link between visually encoding a visualisation in memory and recall performance. To fill this gap, we propose VisRecall++ -- a novel 40-participant recallability dataset that contains gaze data on 200 visualisations and 1,000 questions, including identifying the title and retrieving values. We measured recallability by asking participants questions after they observed the visualisation for 10 seconds. Our analyses reveal several insights, such as saccade amplitude, number of fixations, and fixation duration significantly differ between high and low recallability groups. Finally, we propose GazeRecallNet -- a novel computational method to predict recallability from gaze behaviour that outperforms the state-of-the-art model RecallNet and three other baselines on this task. Taken together, our results shed light on assessing recallability from gaze behaviour and inform future work on recallability-based visualisation optimisation.
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Dadzie, Aba-Sah, and Emmanuel Pietriga. "Visualisation of Linked Data – Reprise." Semantic Web 8, no. 1 (November 23, 2016): 1–21. http://dx.doi.org/10.3233/sw-160249.
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Horky, Thomas, and Philipp Pelka. "Data Visualisation in Sports Journalism." Digital Journalism 5, no. 5 (November 17, 2016): 587–606. http://dx.doi.org/10.1080/21670811.2016.1254053.
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Gardner, S., N. J. Le Roux, and C. Aldrich. "Process data visualisation with biplots." Minerals Engineering 18, no. 9 (August 2005): 955–68. http://dx.doi.org/10.1016/j.mineng.2004.12.010.
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Bödeker, Bertram, Wolfgang Vautz, and Jörg Ingo Baumbach. "Visualisation of MCC/IMS-data." International Journal for Ion Mobility Spectrometry 11, no. 1-4 (November 11, 2008): 77–81. http://dx.doi.org/10.1007/s12127-008-0011-8.
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Macer, Tim. "Data Visualisation in Market Research." Research World 2014, no. 47 (September 2014): 10–19. http://dx.doi.org/10.1002/rwm3.20123.
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Johansson, Veronica, and Jörgen Stenlund. "Making time/breaking time: critical literacy and politics of time in data visualisation." Journal of Documentation 78, no. 1 (October 19, 2021): 60–82. http://dx.doi.org/10.1108/jd-12-2020-0210.
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PurposeRepresentations 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/approachThis 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.FindingsFour 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/valueThe 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.
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Ruddle, Roy A., Muhammad Adnan, and Marlous Hall. "Using set visualisation to find and explain patterns of missing values: a case study with NHS hospital episode statistics data." BMJ Open 12, no. 11 (November 2022): e064887. http://dx.doi.org/10.1136/bmjopen-2022-064887.
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ObjectivesMissing data is the most common data quality issue in electronic health records (EHRs). Missing data checks implemented in common analytical software are typically limited to counting the number of missing values in individual fields, but researchers and organisations also need to understand multifield missing data patterns to better inform advanced missing data strategies for which counts or numerical summaries are poorly suited. This study shows how set-based visualisation enables multifield missing data patterns to be discovered and investigated.DesignDevelopment and evaluation of interactive set visualisation techniques to find patterns of missing data and generate actionable insights. The visualisations comprised easily interpretable bar charts for sets, heatmaps for set intersections and histograms for distributions of both sets and intersections.Setting and participantsAnonymised admitted patient care health records for National Health Service (NHS) hospitals and independent sector providers in England. The visualisation and data mining software was run over 16 million records and 86 fields in the dataset.ResultsThe dataset contained 960 million missing values. Set visualisation bar charts showed how those values were distributed across the fields, including several fields that, unexpectedly, were not complete. Set intersection heatmaps revealed unexpected gaps in diagnosis, operation and date fields because diagnosis and operation fields were not filled up sequentially and some operations did not have corresponding dates. Information gain ratio and entropy calculations allowed us to identify the origin of each unexpected pattern, in terms of the values of other fields.ConclusionsOur findings show how set visualisation reveals important insights about multifield missing data patterns in large EHR datasets. The study revealed both rare and widespread data quality issues that were previously unknown, and allowed a particular part of a specific hospital to be pinpointed as the origin of rare issues that NHS Digital did not know exist.
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Roberts, Richard, and Robert Laramee. "Visualising Business Data: A Survey." Information 9, no. 11 (November 17, 2018): 285. http://dx.doi.org/10.3390/info9110285.
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A rapidly increasing number of businesses rely on visualisation solutions for their data management challenges. This demand stems from an industry-wide shift towards data-driven approaches to decision making and problem-solving. However, there is an overwhelming mass of heterogeneous data collected as a result. The analysis of these data become a critical and challenging part of the business process. Employing visual analysis increases data comprehension thus enabling a wider range of users to interpret the underlying behaviour, as opposed to skilled but expensive data analysts. Widening the reach to an audience with a broader range of backgrounds creates new opportunities for decision making, problem-solving, trend identification, and creative thinking. In this survey, we identify trends in business visualisation and visual analytic literature where visualisation is used to address data challenges and identify areas in which industries use visual design to develop their understanding of the business environment. Our novel classification of literature includes the topics of businesses intelligence, business ecosystem, customer-centric. This survey provides a valuable overview and insight into the business visualisation literature with a novel classification that highlights both mature and less developed research directions.
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Haslett, S. J., and K. Govindaraju. "Data cloning: Data visualisation, smoothing, confidentiality, and encryption." Journal of Statistical Planning and Inference 142, no. 2 (February 2012): 410–22. http://dx.doi.org/10.1016/j.jspi.2011.07.020.
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Nowosad, Mateusz. "Enviromental data visualisation using Delaunay triangulation." Journal of Computer Sciences Institute 17 (December 30, 2020): 405–11. http://dx.doi.org/10.35784/jcsi.2367.
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Graphical data representation is very helpful when analyzing environmental data. It allows for discovering trends in data and analysis of phenomena occurring in the area. There are many possibilities to represent such values graphically. This article contains visualizations generated using Delauney triangulation to represent data on a map. Strengths and weaknesses, comparative analysis with another solution, performance, and usage suggestions will be presented.
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Mohamad-Matrol, Afrina Adlyna, Siow-Wee Chang, and Arpah Abu. "Plant data visualisation using network graphs." PeerJ 6 (August 31, 2018): e5579. http://dx.doi.org/10.7717/peerj.5579.
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BackgroundThe amount of plant data such as taxonomical classification, morphological characteristics, ecological attributes and geological distribution in textual and image forms has increased rapidly due to emerging research and technologies. Therefore, it is crucial for experts as well as the public to discern meaningful relationships from this vast amount of data using appropriate methods. The data are often presented in lengthy texts and tables, which make gaining new insights difficult. The study proposes a visual-based representation to display data to users in a meaningful way. This method emphasises the relationships between different data sets.MethodThis study involves four main steps which translate text-based results from Extensible Markup Language (XML) serialisation format into graphs. The four steps include: (1) conversion of ontological dataset as graph model data; (2) query from graph model data; (3) transformation of text-based results in XML serialisation format into a graphical form; and (4) display of results to the user via a graphical user interface (GUI). Ontological data for plants and samples of trees and shrubs were used as the dataset to demonstrate how plant-based data could be integrated into the proposed data visualisation.ResultsA visualisation system named plant visualisation system was developed. This system provides a GUI that enables users to perform the query process, as well as a graphical viewer to display the results of the query in the form of a network graph. The efficiency of the developed visualisation system was measured by performing two types of user evaluations: a usability heuristics evaluation, and a query and visualisation evaluation.DiscussionThe relationships between the data were visualised, enabling the users to easily infer the knowledge and correlations between data. The results from the user evaluation show that the proposed visualisation system is suitable for both expert and novice users, with or without computer skills. This technique demonstrates the practicability of using a computer assisted-tool by providing cognitive analysis for understanding relationships between data. Therefore, the results benefit not only botanists, but also novice users, especially those that are interested to know more about plants.
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Graham, Elyse. "Introduction: Data Visualisation and the Humanities." English Studies 98, no. 5 (July 4, 2017): 449–58. http://dx.doi.org/10.1080/0013838x.2017.1332021.
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Afonso, Carlos, Mark P. Barrow, Antony N. Davies, Marc-André Delsuc, Timothy Ebbels, Francisco Fernandez-Lima, Caroline Gauchotte-Lindsay, et al. "Data mining and visualisation: general discussion." Faraday Discussions 218 (2019): 354–71. http://dx.doi.org/10.1039/c9fd90044f.
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Fyfe, Colin. "Two topographic maps for data visualisation." Data Mining and Knowledge Discovery 14, no. 2 (January 26, 2007): 207–24. http://dx.doi.org/10.1007/s10618-006-0047-5.
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Crennell, K. M. "The visualisation of neutron scattering data." Physica B: Condensed Matter 180-181 (June 1992): 951–54. http://dx.doi.org/10.1016/0921-4526(92)90519-x.
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Atkinson, Anthony C., and Marco Riani. "The forward search and data visualisation." Computational Statistics 19, no. 1 (February 2004): 29–54. http://dx.doi.org/10.1007/bf02915275.
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Rink, Karsten, Lars Bilke, and Olaf Kolditz. "Visualisation strategies for environmental modelling data." Environmental Earth Sciences 72, no. 10 (January 8, 2014): 3857–68. http://dx.doi.org/10.1007/s12665-013-2970-2.
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Cheshire, James, and Michael Batty. "Visualisation Tools for Understanding Big Data." Environment and Planning B: Planning and Design 39, no. 3 (January 2012): 413–15. http://dx.doi.org/10.1068/b3903ed.
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Hedley, Alison. "Florence Nightingale and Victorian data visualisation." Significance 17, no. 2 (April 2020): 26–30. http://dx.doi.org/10.1111/1740-9713.01376.
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Hüsch, Marc. "Thomas Rahlf: Data Visualisation with R." Statistical Papers 59, no. 2 (April 20, 2018): 847–48. http://dx.doi.org/10.1007/s00362-018-1003-3.
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Venkatraman, Sitalakshmi, and Mamoun Alazab. "Use of Data Visualisation for Zero-Day Malware Detection." Security and Communication Networks 2018 (December 2, 2018): 1–13. http://dx.doi.org/10.1155/2018/1728303.
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With the explosion of Internet of Things (IoT) worldwide, there is an increasing threat from malicious software (malware) attackers that calls for efficient monitoring of vulnerable systems. Large amounts of data collected from computer networks, servers, and mobile devices need to be analysed for malware proliferation. Effective analysis methods are needed to match with the scale and complexity of such a data-intensive environment. In today’s Big Data contexts, visualisation techniques can support malware analysts going through the time-consuming process of analysing suspicious activities thoroughly. This paper takes a step further in contributing to the evolving realm of visualisation techniques used in the information security field. The aim of the paper is twofold: (1) to provide a comprehensive overview of the existing visualisation techniques for detecting suspicious behaviour of systems and (2) to design a novel visualisation using similarity matrix method for establishing malware classification accurately. The prime motivation of our proposal is to identify obfuscated malware using visualisation of the extended x86 IA-32 (opcode) similarity patterns, which are hard to detect with the existing approaches. Our approach uses hybrid models wherein static and dynamic malware analysis techniques are combined effectively along with visualisation of similarity matrices in order to detect and classify zero-day malware efficiently. Overall, the high accuracy of classification achieved with our proposed method can be visually observed since different malware families exhibit significantly dissimilar behaviour patterns.
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Gastner, Michael T. "Podučavanje vizualizacije podataka i osnovnih vještina izrade karata na Liberal Arts Collegeu." Kartografija i geoinformacije 22, no. 39 (July 21, 2023): 42–60. http://dx.doi.org/10.32909/kg.22.39.3.
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Communicating data has become vital in an increasingly data-dependent society. Because data are often communicated graphically, many colleges and universities are offering courses that teach the principles of data visualisation. In this article, the author reflects on his experience of teaching such a course at a liberal arts college. The course introduced students to the tidyverse suite of packages for the programming language R, including the data visualisation package ggplot2, which implements Wilkinson’s (2005) ‘grammar of graphics’. The packages sf and tmap were used to extend the capabilities of the tidyverse packages for analysing geospatial data and producing thematic maps. This article provides insights into effective teaching strategies, including intended learning outcomes, the core syllabus, pedagogy and assessment. Sample tasks and visualisations are also presented to demonstrate how essential cartographic skills were imparted to students.