Relevant bibliographies by topics / Data Visualisation

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Data Visualisation'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Data Visualisation"

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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 (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 pro
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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 (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
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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 (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
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Allen, William L. "Visual brokerage: Communicating data and research through visualisation." Public Understanding of Science 27, no. 8 (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 o
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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 locati
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Kirsten, Marnell, Marina Joubert, Ionica Smeets, and Winnifred Wijnker. "Off the charts: A comparative analysis of data visualisations in online science news from South Africa and the USA." PLOS ONE 20, no. 2 (2025): e0316194. https://doi.org/10.1371/journal.pone.0316194.

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Terms like ‘big data’, ‘data science’, and ‘data visualisation’ have become buzzwords in recent years and are increasingly intertwined with journalism. Data visualisation may further blur the lines between science communication and graphic design. Our study is situated in these overlaps to compare the design of data visualisations in science news stories across four online news media platforms in South Africa and the United States. Our study contributes to an understanding of how well-considered data visualisations are tools for effective storytelling, and offers practical recommendations for
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ROHIT, SINGH, Kumar Pandya Nitin, Kruti Sutariya Dr., and Amit Barve Dr. "AlgoPedia." International Journal of Innovative Science and Research Technology 8, no. 3 (2023): 1466–85. https://doi.org/10.5281/zenodo.7789144.

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Data visualisation entails presenting information in a graphical or pictorial format that is easy to understand. It aids in the explanation of facts and the formulation of action plans. It will be useful in any field of study that requires novel approaches to presenting large amounts of complex information. The introduction of computer graphics shaped modern visualisation. This paper provides an overview of data visualisation. Data visualisation, information visualisation, scientific visualisation, and big data are all keywords. Information visualisation and scientific visualisation are other
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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 (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, research
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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 de
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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 de
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Dissertations / Theses on the topic "Data Visualisation"

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Long, Elena. "Election data visualisation." Thesis, University of Plymouth, 2013. http://hdl.handle.net/10026.1/1589.

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Visualisations of election data produced by the mass media, other organisations and even individuals are becoming increasingly available across a wide variety of platforms and in many different forms. As more data become available digitally and as improvements to computer hardware and software are made, these visualisations have become more ambitious in scope and more user-friendly. Research has shown that visualising data is an extremely powerful method of communicating information to specialists and non-specialists alike. This amounts to a democratisation of access to political and electoral
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Eyre-Todd, Richard A. "Safe data structure visualisation." Thesis, University of Edinburgh, 1993. http://hdl.handle.net/1842/14819.

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A simple three layer scheme is presented which broadly categorises the types of support that a computing system might provide for program monitoring and debugging, namely hardware, language and external software support. Considered as a whole , the scheme forms a model for an integrated debugging-oriented system architecture. This thesis describes work which spans the upper levels of this architecture. A programming language may support debugging by preventing or detecting the use of objects that have no value. Techniques to help with this task such as formal verification, static analysis, req
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Garda-Osorio, Cesar. "Data mining and visualisation." Thesis, University of the West of Scotland, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.742763.

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Fei, Bennie Kar Leung. "Data visualisation in digital forensics." Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-03072007-153241.

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Basalaj, Wojciech. "Proximity visualisation of abstract data." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620911.

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Anderson, Jonathan. "Visualisation of data from IoT systems : A case study of a prototyping tool for data visualisations." Thesis, Linköpings universitet, Programvara och system, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138723.

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The client in this study, Attentec, has seen an increase in the demand for services connected to Internet of things systems. This study is therefore examining if there is a tool that can be a used to build fast prototype visualisations of data from IoT systems to use as a tool in their daily work. The study started with an initial phase with two parts. The first part was to get better knowledge of Attentec and derive requirements for the tool and the second part was a comparison of prototyping tools for aiding in development of data visualisations. Apache Zeppelin was chosen as the most versat
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Gel, Moreno Bernat. "Dissemination and visualisation of biological data." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/283143.

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With the recent advent of various waves of technological advances, the amount of biological data being generated has exploded. As a consequence of this data deluge, new challenges have emerged in the field of biological data management. In order to maximize the knowledge extracted from the huge amount of biological data produced it is of great importance for the research community that data dissemination and visualisation challenges are tackled. Opening and sharing our data and working collaboratively will benefit the scientific community as a whole and to move towards that end, new developeme
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Simpson, T. "Visualisation of irregular, finite element data." Thesis, Swansea University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.639040.

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This thesis outlines work into the development of efficient techniques for visualisation of datasets generated using finite element analyses. In particular, the work concentrates on datasets that require quadratic interpolation methods to accurately visualise simulation results. Typically for example, this includes simulations into non-Newtonian fluids where the use of quadratic shape functions is necessary to obtain acceptable results. Our first concern is fundamental algorithms for analysing irregular domains, typically constructed from triangular or tetrahedral cells. This includes methods
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Turner, D. "The visualisation of polarimetric radar data." Thesis, University of Edinburgh, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.663102.

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This research forms part of a larger body of work which studies the application of scientific visualisation to the analysis of large multi-valued datasets. Visualisation techniques have historically assumed a fundamental role in the analysis of patterns in geographic datasets. This is particularly apparent in the analysis of remotely sensed data, which, since the advent of aerial photography, has utilised the intensity of visible (and invisible) electromagnetic energy as a means of producing synoptic map-like images. Progress in remote sensing technology, however, has led to the development of
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Loizides, Andreas M. "Intuitive visualisation of multi-variate data sets using the empathic visualisation algorithm (EVA)." Thesis, University College London (University of London), 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407941.

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Books on the topic "Data Visualisation"

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Rahlf, Thomas. Data Visualisation with R. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28444-2.

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Rahlf, Thomas. Data Visualisation with R. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49751-8.

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Shah, Neel. Visualisation of electricity market data. University of Manchester, Department of Computer Science, 1996.

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Hall, Tim. 3D visualisation of mobile robot sensr data. University of Manchester, Department of Computer Science, 1997.

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Bianconi, Francesco. Data and Process Visualisation for Graphic Communication. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57051-3.

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Pryke, Andy Neil. Data mining using genetic algorithms and interactive visualisation. University of Birmingham, 1999.

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Ruddy, David Andrew. Sharing of data visualisation within a virtual organisation. Oxford Brookes University, 2003.

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Ottoson, Patrik. Geographic indexing and data management for 3D-visualisation. Royal Institute of Technology, KTH, 2001.

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Hobbs, Kenneth Frank. The visualisation and rendering of digital elevation data. University of East London, 2000.

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Foreman, Darren. Visualisation of data structures and operations on them. University of Manchester, 1995.

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Book chapters on the topic "Data Visualisation"

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Fox, Charles. "Data Visualisation." In Springer Textbooks in Earth Sciences, Geography and Environment. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72953-4_9.

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Gough, Phillip, and Jack Zhao. "Data Visualisation." In Teaching Science Students to Communicate: A Practical Guide. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-91628-2_7.

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Shardt, Yuri A. W. "Data Visualisation." In essentials. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40299-9_2.

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Irwin, Terry, Julie Terberg, and Echo Swinford. "Data visualisation." In Medical Presentations. CRC Press, 2024. http://dx.doi.org/10.1201/9781003287902-19.

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Dawson, Catherine. "Data visualisation." In A–Z of Digital Research Methods. Routledge, 2019. http://dx.doi.org/10.4324/9781351044677-14.

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Aitkin, Murray. "Data visualisation." In Introduction to Statistical Modelling and Inference. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003216025-9.

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Shardt, Yuri A. W. "Data Visualisation." In Using Excel to Solve Statistical Problems: A Practical Guide to the Book “Statistics for Chemical and Process Engineers”. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65449-7_2.

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Kjeldsen, Thomas Rodding. "Data Visualisation." In Risk and Uncertainty for Civil Engineering. CRC Press, 2025. https://doi.org/10.1201/9781032700373-4.

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Frampton, Michael. "Visualisation." In Complete Guide to Open Source Big Data Stack. Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-2149-5_9.

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Moore, Antoni, Marcos de Oliveira, Carlos Caminha, Vasco Furtado, Victor Basso, and Leonardo Ayres. "Applying Geovisual Analytics to Volunteered Crime Data." In Geospatial Visualisation. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-12289-7_9.

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Conference papers on the topic "Data Visualisation"

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Lourenço, Luis, Paulo Figueiras, Amin Khodamoradi, et al. "Big Data Visualisation in the Maritime Industry." In 2024 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC). IEEE, 2024. https://doi.org/10.1109/ice/itmc61926.2024.10794236.

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Matsuno, Ryuta, Keita Sakuma, and Masakazu Hirokawa. "Model Accuracy-Oriented Data Sets Visualization for Understanding Temporal Changes in Data." In 2024 28th International Conference Information Visualisation (IV). IEEE, 2024. http://dx.doi.org/10.1109/iv64223.2024.00041.

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Villuendas, Esperanza, Laya Targa, Álvaro Solbes, Inmaculada Coma, Jorge Sebastián, and Cristina Portalés. "USABILITY EVALUATION FOR DATA VISUALISATION OF CULTURAL HERITAGE." In 19th International Technology, Education and Development Conference. IATED, 2025. https://doi.org/10.21125/inted.2025.0786.

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Cotta, Romulo, and Robert Cottis. "Methods for the Visualisation of Electrochemical Noise Data." In CORROSION 2007. NACE International, 2007. https://doi.org/10.5006/c2007-07363.

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Abstract The use of electrochemical noise (EN) measurements for the study of corrosion processes is now well established, but it remains somewhat unclear as to the best methods to use the extract useful information from the measured time records. Many of the simpler methods are based on the calculation of statistical parameters, such as the standard deviation of current, σI, or potential, σE, and the electrochemical noise resistance, Rn. A problem with many parameters derived from EN measurements is they are inherently noisy, which can make interpretation difficult. This paper explores an alte
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Cunha Monteiro, Walbert, Thiago Augusto Soares de Sousa, Anderson Gregório Marques Soares, Tiago Davi Oliveira de Araújo, Carlos Gustavo Resque dos Santos, and Bianchi Serique Meiguins. "Encoding Data Through Tactile Vibrations." In 2024 28th International Conference Information Visualisation (IV). IEEE, 2024. http://dx.doi.org/10.1109/iv64223.2024.00011.

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Williams, Alice, and Boris Kovalerchuk. "Synthetic Data Generation and Automated Multidimensional Data Labeling for AI/ML in General and Circular Coordinates." In 2024 28th International Conference Information Visualisation (IV). IEEE, 2024. http://dx.doi.org/10.1109/iv64223.2024.00054.

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Oliveira, Beatriz, and Jorge Sá. "Data Feminism Influence on Data Visualization." In 23ª Conferência da Associação Portuguesa de Sistemas de Informação. Associação Portuguesa de Sistemas de Informação, APSI, 2023. http://dx.doi.org/10.18803/capsi.v23.365-381.

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Data Visualisation is currently seen as a powerful communication tool, as the human mind is more receptive to visual information than words or raw data. However, most existing visualisations are done from an androcentric perspective. This article proposes Data Visualisation from a feminist perspective. To this end, concepts such as Feminism, Data Visualisation and Data Feminism will be addressed to arrive at the concept of Data Visualisation in Feminism, resulting in a set of guidelines and recommendations to be incorporated when designing Data Visualisations. As part of the work carried out,
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Pinney, Joel, Fiona Carroll, and Esyin Chew. "Enthusiast Versus Antagonist: Exploring the Perceptions of Data Experts on the Visualisation of Uncertainty." In Human Interaction and Emerging Technologies (IHIET-AI 2022) Artificial Intelligence and Future Applications. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100892.

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Despite the copious number of reasons to visualise uncertainty in visualisations, there is still a reluctance to actively represent uncertainties. This paper explores the perceptions of data experts considering uncertainty visualisation and their reasoning behind lacking engagement. By documenting a series of interviews with data experts, the authors uncover the perceptions and constraints faced when contemplating uncertainty visualisation. Through several industries, the authors reveal numerous perceived benefits of uncertainty visualisation but also the strong influence end-users have on the
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Monageng, Keabetswe, Annlizé L. Marnewick, and Carl Marnewick. "Visualisation of Project Data for Informed Decision-Making." In The 33rd IPMA World Congress “Hope for a Sustainable Future: Blending AI&IT, ESG, and Capital Projects”. International Project Management Association – IPMA, International Project Management Association - South Africa NPC (IPMA-SA), 2025. https://doi.org/10.56889/mimn3363.

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Data creates opportunities for project managers to visualise the data which is valuable in project management decision-making. Without a thorough view of the data, project managers are unable to make informed decisions. Data visualisation presents data in pictures or graphs that summarise the information in a comprehensible manner with the purpose of gaining insights and drawing conclusions. A questionnaire consisting of four sections was completed by 39 respondents. One section focused on the usage and influences of data visualisations. Another section focused on specific data visualisation t
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Ivancic, M., Z. Mihajlovic, and I. Ivancic. "Seismic data visualisation." In 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE, 2015. http://dx.doi.org/10.1109/mipro.2015.7160287.

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Reports on the topic "Data Visualisation"

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Mironova, Irina. Data Visualisation in Excel for Beginners. Instats Inc., 2025. https://doi.org/10.61700/iev6djpm8rb3t1604.

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This four-day workshop offers a comprehensive introduction to data visualization in Excel, with a focus on energy transition and sustainable energy futures. Participants will work with sample datasets covering topics such as global energy investments, electrification, and coal consumption. The workshop will guide attendees through creating bar, line, pie, and area charts, helping them enhance their research and policy analysis skills in energy economics.
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Caldwell, T. G., and H. M. Bibby. Visualisation of Tensor Time Domain Electromagnetic Data. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/895937.

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Valero Sancho, JL, J. Catalá Domínguez, and BE Marín Ochoa. An approach to the taxonomy of data visualisation. Revista Latina de Comunicación Social, 2014. http://dx.doi.org/10.4185/rlcs-2014-1021en.

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Marín Ochoa, BE. Treatment of post-conflict Colombia through infographics and data visualisation. Revista Latina de Comunicación Social, 2018. http://dx.doi.org/10.4185/rlcs-2018-1277en.

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Kirkby, A. L., F. Zhang, J. Peacock, R. Hassan, and J. Duan. Development of the open-source MTPy package for magnetotelluric data analysis and visualisation. Geoscience Australia, 2020. http://dx.doi.org/10.11636/132198.

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Zhan, Peng. Statistical Analysis and Data Visualization in R. Instats Inc., 2022. http://dx.doi.org/10.61700/dizyg5iq1mqj5469.

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This seminar provides a gentle introduction to R for those looking to use it for applied statistics and visualisation, covering a range of essential topics on basic data manipulation, regression analysis, and visualizing data and results. Examples from multiple fields are used to demonstrate the applications. An official Instats certificate of completion is provided at the conclusion of the seminar.
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Pălici, Bogdan, Alin Savu, Maria Trifon, et al. Mapping - Interactive Tool for Exploring Statistical Data about Cultural Infrastructure in Romania. National Institute for Cultural Research and Training, 2021. http://dx.doi.org/10.61789/mod.cdi.crtg.en.21.

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The Cartographic Module is an instrument for data selection, structuring, visualisation and analysis. It provides for multiple selection functionalities both at geographical area level (county, locality) and at data level (category of indicators and indicators). Three types of dynamic graphs are available on the indicator pages: comparison/evolution, ranking and frequency.
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Gruber, Peter. Using ChatGPT for Advanced Data Analysis. Instats Inc., 2023. http://dx.doi.org/10.61700/pmgm4wmm7ffer469.

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This workshop teaches researchers, from PhD students to professors, how to use ChatGPT and its Advanced Data Analytics tool for statistical analysis without writing a line of code or even knowing how to use a statistics program. The seminar covers a range of topics from data preparation and descriptive statistics to regression analysis, advanced statistical tests and visualisation. Special emphasis is placed on understanding the workings and limits of AI models such as ChatGPT and reflecting on its implications for data analysis.
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Toutin, Th, A. Redmond, E. Hoeppner, D. Hoja, and C. King. RADARSAT and DEM Data Fusion for 3D Visualisation Over the Reunion Island for Geoscientific Applications. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1998. http://dx.doi.org/10.4095/219317.

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Gruber, Peter H. Using ChatGPT for Advanced Data Analysis. Instats Inc., 2023. http://dx.doi.org/10.61700/zqir2dzchct5b469.

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This 2-day workshop teaches researchers, from PhD students to professors, how to use ChatGPT and its Advanced Data Analytics tool for statistical analysis without writing a line of code or even knowing how to use a statistics program. The seminar covers a range of topics from data preparation and descriptive statistics to regression analysis, advanced statistical tests and visualisation. Special emphasis is placed on understanding the workings and limits of AI models such as ChatGPT and reflecting on its implications for data analysis.
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