7 research outputs found
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Towards Natural Language Empowered Interactive Data Analysis
The recent advances in natural language based interaction methodologies offer promising avenues to enhance the interactive processes within the human-machine dialogue of visual analytics. We envisage \textit{Multimodal Data Analytics} as a novel approach for conducting data analysis that builds on the strengths of visual analytics and natural language as an expressive interaction channel. We investigate the potential enhancements from such a multimodal approach and discusses the preliminary outline for a structured methodology to study the role of natural language in data analytics. Our approach builds on a simple model of human machine dialogue for interactive data analysis which we then propose to instantiate as visual analytics workflows -- representations to study and operationalise interactive data analysis routines empowered by natural language interaction
How Visualization Supports the Daily Work in Traditional Humanities on the Example of Visual Analysis Case Studies
Attempts to convince humanities scholars of digital approaches are met with
resistance, often. The so-called Digitization Anxiety is the phenomenon that
describes the fear of many traditional scientists of being replaced by digital
processes. This hinders not only the progress of the scientific domains themselves
– since a lot of digital potential is missing – but also makes the everyday work
of researchers unnecessarily difficult. Over the past eight years, we have
made various attempts to walk the tightrope between 'How can we help
traditional humanities to exploit their digital potential?' and 'How can we
make them understand that their expertise is not replaced by digital means, but
complemented?' We will present our successful interdisciplinary collaborations:
How they came about, how they developed, and the problems we encountered. In
the first step, we will look at the theoretical basics, which paint a comprehensive
picture of the digital humanities and introduces us to the topic of visualization.
The field of visualization has shown a special ability: It manages to walk the
tightrope and thus keeps digitization anxiety at bay, while not only making it
easier for scholars to access their data, but also enabling entirely new research
questions. After an introduction to our interdisciplinary collaborations with
the Musical Instrument Museum of Leipzig University, as well as with the
Bergen-Belsen Memorial, we will present a series of user scenarios that we
have collected in the course of 13 publications. These show our cooperation
partners solving different research tasks, which we classify using Brehmer and
Munzner’s Task Classification. In this way, we show that we provide researchers
with a wide range of opportunities: They can answer their traditional research
questions – and in some cases verify long-standing hypotheses about the data
for the first time – but also develop their own interest in previously impossible,
new research questions and approaches. Finally, we conclude our insights on
individual collaborative ideas with perspectives on our newest projects. These
have risen from the growing interest of collaborators in the methods we deliver.
For example, we get insights into the music of real virtuosos of the 20th century.
The necessary music storage media can be heard for the first time through
digital tools without risking damage to the old material. In addition, we can
provide computer-aided analysis capabilities that help musicologists in their work.
In the course of the visualization project at the Bergen-Belsen memorial, we
will see that what was once a small diary project has grown into a multimodal
and international project with institutions of culture and science from eight
countries. This is dedicated not only to the question of preserving cultural
objects from Nazi persecution contexts but also to modern ways of disseminating
and processing knowledge around this context. Finally, we will compile our
experience and accumulated knowledge in the form of problems and challenges
at the border between computer science and traditional humanities. These will
serve as preparation and assistance for future and current interested parties of
such interdisciplinary collaborative project
Women in Artificial intelligence (AI)
This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI
On the relation between body and movement space representation: an experimental investigation on spinal cord injured people
Body Representation (BR) and Movement Space Perception (MSP) are fundamental for human beings in order to move in space and interact with object s and other people. Both BR and space representation change after spinal cord injuries in complete paraplegic individuals (CPP), who suffer from lower limbs paralysis and anesthesia. To date, the interaction between BR and MSP in paraplegic individuals rem ains unexplored. In two consecutive experiments, we tested I ) if the individual\u2019s wheelchair is embodied in BR; and ii) if the embodied wheelchair modifies the MSP. For the first question a speeded detection task was used. Participants had to respond to v isual stimuli flashing on their trunk, legs or wheelchair. In three counterbalanced conditions across participant, they took part to the experiment while: 1) sitting in their wheelchair, 2) in another wheelchair, or 3) with the LEDs on a wooden bar. To in dicate the embodiment, there was no difference in the CPP\u2019s responses for LEDs on the body and personal wheelchair while these were slower in other conditions After this, while sitting in their or another wheelchair, CPPs were asked to judge the slope of a ramp rendered in immersive virtual reality and to estimate the distance of a flag positioned over the ramp. When on their own wheelchair, CPPs perceived the flag closer than in the other wheelchair. These results indicate that the continuous use of a too l induces embodiment and that this i mpact on the perception of MSP
High-Performance Modelling and Simulation for Big Data Applications
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications
High-Performance Modelling and Simulation for Big Data Applications
This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications