17 research outputs found

    Chatbot-Based Natural Language Interfaces for Data Visualisation: A Scoping Review

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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

    CollabCoder: A GPT-Powered Workflow for Collaborative Qualitative Analysis

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    The Collaborative Qualitative Analysis (CQA) process can be time-consuming and resource-intensive, requiring multiple discussions among team members to refine codes and ideas before reaching a consensus. To address these challenges, we introduce CollabCoder, a system leveraging Large Language Models (LLMs) to support three CQA stages: independent open coding, iterative discussions, and the development of a final codebook. In the independent open coding phase, CollabCoder provides AI-generated code suggestions on demand, and allows users to record coding decision-making information (e.g. keywords and certainty) as support for the process. During the discussion phase, CollabCoder helps to build mutual understanding and productive discussion by sharing coding decision-making information with the team. It also helps to quickly identify agreements and disagreements through quantitative metrics, in order to build a final consensus. During the code grouping phase, CollabCoder employs a top-down approach for primary code group recommendations, reducing the cognitive burden of generating the final codebook. An evaluation involving 16 users confirmed the usability and effectiveness of CollabCoder and offered empirical insights into the LLMs' roles in CQA

    Natural Language Interfaces for Tabular Data Querying and Visualization: A Survey

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    The emergence of natural language processing has revolutionized the way users interact with tabular data, enabling a shift from traditional query languages and manual plotting to more intuitive, language-based interfaces. The rise of large language models (LLMs) such as ChatGPT and its successors has further advanced this field, opening new avenues for natural language processing techniques. This survey presents a comprehensive overview of natural language interfaces for tabular data querying and visualization, which allow users to interact with data using natural language queries. We introduce the fundamental concepts and techniques underlying these interfaces with a particular emphasis on semantic parsing, the key technology facilitating the translation from natural language to SQL queries or data visualization commands. We then delve into the recent advancements in Text-to-SQL and Text-to-Vis problems from the perspectives of datasets, methodologies, metrics, and system designs. This includes a deep dive into the influence of LLMs, highlighting their strengths, limitations, and potential for future improvements. Through this survey, we aim to provide a roadmap for researchers and practitioners interested in developing and applying natural language interfaces for data interaction in the era of large language models.Comment: 20 pages, 4 figures, 5 tables. Submitted to IEEE TKD

    Designing a 3D Gestural Interface to Support User Interaction with Time-Oriented Data as Immersive 3D Radar Chart

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    The design of intuitive three-dimensional user interfaces is vital for interaction in virtual reality, allowing to effectively close the loop between a human user and the virtual environment. The utilization of 3D gestural input allows for useful hand interaction with virtual content by directly grasping visible objects, or through invisible gestural commands that are associated with corresponding features in the immersive 3D space. The design of such interfaces remains complex and challenging. In this article, we present a design approach for a three-dimensional user interface using 3D gestural input with the aim to facilitate user interaction within the context of Immersive Analytics. Based on a scenario of exploring time-oriented data in immersive virtual reality using 3D Radar Charts, we implemented a rich set of features that is closely aligned with relevant 3D interaction techniques, data analysis tasks, and aspects of hand posture comfort. We conducted an empirical evaluation (n=12), featuring a series of representative tasks to evaluate the developed user interface design prototype. The results, based on questionnaires, observations, and interviews, indicate good usability and an engaging user experience. We are able to reflect on the implemented hand-based grasping and gestural command techniques, identifying aspects for improvement in regard to hand detection and precision as well as emphasizing a prototype's ability to infer user intent for better prevention of unintentional gestures.Comment: 30 pages, 6 figures, 2 table

    Transforming the Reading Experience of Scientific Documents with Polymorphism

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    Despite the opportunities created by digital reading, documents remain mostly static and mimic paper. Any improvement in the shape or form of documents has to come from authors who contend with current digital formats, workflows, and software and who impose a presentation to readers. Instead, I propose the concept of polymorphic documents which are documents that can change in form to offer better representations of the information they contain. I believe that multiple representations of the same information can help readers, and that any document can be made polymorphic, with no intervention from the original author. This thesis presents four projects investigating what information can be obtained from existing documents, how this information can be better represented, and how these representations can be generated using only the source document. To do so, I draw upon theories showing the benefit of presenting information using multiple representations; the design of interactive systems to support morphing representations; and user studies to evaluate system usability and the benefits of the new representations on reader comprehension

    Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

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    This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

    Intelligent Transportation Related Complex Systems and Sensors

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    Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data

    The Public Life of Data: Investigating Reactions to Visualizations on Reddit

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    This research investigates how people engage with data visualizations when commenting on the social platform Reddit. There has been considerable research on collaborative sensemaking with visualizations and the personal relation of people with data. Yet, little is known about how public audiences without specific expertise and shared incentives openly express their thoughts, feelings, and insights in response to data visualizations. Motivated by the extensive social exchange around visualizations in online communities, this research examines characteristics and motivations of people's reactions to posts featuring visualizations. Following a Grounded Theory approach, we study 475 reactions from the /r/dataisbeautiful community, identify ten distinguishable reaction types, and consider their contribution to the discourse. A follow-up survey with 168 Reddit users clarified their intentions to react. Our results help understand the role of personal perspectives on data and inform future interfaces that integrate audience reactions into visualizations to foster a public discourse about data

    Supporting Methodology Transfer in Visualization Research with Literature-Based Discovery and Visual Text Analytics

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    [ES] La creciente especializaci贸n de la ciencia est谩 motivando la r谩pida fragmentaci贸n de disciplinas bien establecidas en comunidades interdisciplinares. Esta descom- posici贸n se puede observar en un tipo de investigaci贸n en visualizaci贸n conocida como investigaci贸n de visualizaci贸n dirigida por el problema. En ella, equipos de expertos en visualizaci贸n y un dominio concreto, colaboran en un 谩rea espec铆fica de conocimiento como pueden ser las humanidades digitales, la bioinform谩tica, la seguridad inform谩tica o las ciencias del deporte. Esta tesis propone una serie de m茅todos inspirados en avances recientes en el an谩lisis autom谩tico de textos y la rep- resentaci贸n del conocimiento para promover la adecuada comunicaci贸n y transferen- cia de conocimiento entre estas comunidades. Los m茅todos obtenidos se combinaron en una interfaz de an谩lisis visual de textos orientada al descubrimiento cient铆fico, GlassViz, que fue dise帽ada con estos objetivos en mente. La herramienta se prob贸 por primera vez en el dominio de las humanidades digitales para explorar un corpus masivo de art铆culos de visualizaci贸n de prop贸sito general. GlassViz fue adaptada en un estudio posterior para que soportase diferentes fuentes de datos representativas de estas comunidades, mostrando evidencia de que el enfoque propuesto tambi茅n es una alternativa v谩lida para abordar el problema de la fragmentaci贸n en la investigaci贸n en visualizaci贸n
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